Datalink Approach for DTN and Fair Allocation of Resources...
Transcript of Datalink Approach for DTN and Fair Allocation of Resources...
Aircraft’s Datalink Approach for DTN
Applications and Fair Allocation of Resources Model
CCSR Research Symposium 2011 – Mohammed AL Siyabi, PhD Student
Abstract/ScopeUsing aircrafts in scheduled routes for data
transportation is proposed as a novel Delay
Tolerant Network carrier. Fair Allocation of
Resources Model (FARM) is proposed which
works as a complementary mechanism to
many DTN routing algorithms.
Introduction Links and contacts in DTN environment are
limited and scarce. Aircrafts fly daily routes and pass over
remote locations. The notion of Quality of Service QoS
in DTN
is difficult. FARM is an resource allocation mechanism
based on collecting node’s local information.
Motivations/Objectives Objective 1: Analyse and explain the
advantage of using aircrafts as data carrier. Objective 2: Identify the quality of service
notion in DTN. Objective 3: Introduce (FARM) which will
enhance the delivery probability and the
fairness index of the DTN.
System Model/Definitions The selected nodes: the ones who satisfy the highest admission qualification metrics. Metrics data are generated and updated by nodes and contacts.Main Ideas:The decision metrics: past rejected requests, past accepted requests, CoS
and FIFO orders.
Sample Results The comparison of delivery
probability results between buses,
ferries and aircrafts proved better results
for aircrafts due to their high coverage
area.Applying the model will enhance the
delivery probability and the fairness of
the network.
Summary/ConclusionsMore appropriate for poor
communication infrastructure areas. Higher delivery probability will
indicate better resource utilizations. Higher fairness index will indicate
better resource sharing. QoS
in DTN is more of a resources
management and allocation.
Future works Further
analysis
of
the
aircrafts
as
a
DTN bundle carrier. Enhancing
the
model
to
consider
the
size of the data transmitted by each user
as an extra decision metric.
Subcarrier and Power Allocation forLDS‐OFDM System
CCSR Research Symposium 2011 – Mohammed AL‐Imari, PhD Student
ScopeLow Density Signature‐OFDM (LDS‐
OFDM).
Introduced recently as an efficient multiple access technique.
Subcarrier and power allocation scheme for uplink LDS‐OFDM system.
Greedy and iterative algorithm to maximize the weighted sum‐rate.
Introduction
LDS‐OFDM technique combines the benefits of OFDM with LDS spreading.
High degree of flexibility in radio resource management.
No exclusivity in subcarrier allocation.Several users can share a subcarrier.MotivationsFairness among the users with high spectral efficiency.
Promising multiple access techniquefor next generation mobile systems.
System Model:Single cell uplink LDS‐OFDM system.Maximize the system throughput and ensure
fairness among the users (weighted sum‐rate).Performance metrics: Spectral efficiency and
outage probability.Comparison with OFDMA system.Main Ideas:Iterative subcarrier and power allocation.For each subcarrier that has not been fully loaded, we allocate the subcarrier to the user who has the
maximum utility value.
Simulation Results:
Conclusions: Higher spectral efficiency. Low Outage probability. Competitive candidate as air interface technology.
5 10 15 20 25 301
1.5
2
2.5
3
3.5
4
Number of Users
Spec
tral E
ffic
ienc
y (B
it/s/H
z)
LDS-OFDM-WFLDS-OFDM-EPLDS-OFDM-StaticOFDMA-WFOFDMA-EP
LDS-OFDM
OFDMA
ScenarioNumber of Users
5 10 15 20 25 30
LDS‐OFDM‐WF 0 0 0 0 0 0
LDS‐OFDM‐EP 0 9e‐4 7e‐3 25e‐3 0.05 0.09
OFDMA‐WF 27e‐4 0.06 0.15 0.22 0.3 0.36
OFDMA‐EP 0.02 0.1 0.18 0.25 0.32 0.37
Table I: Outage Probability
Fig. 3: Spectral efficiency comparison for LDS‐OFDM and OFDMA.
Contribution to Distributed Dynamic Spectrum Sharing with Interference Management
CCSR Research Symposium 2011 – Ghassan Alnwaimi, PhD Student
IntroductionIn the context of competitive and cooperative
communication environment, efficient radio
resource allocation become more intractable
and and remains an open problem in which
interference is detrimental and this precisely
constitutes the main motivation setting out the
scope of this research.
Motivations
ObjectivesIn the context of multi‐operators co‐exist and networks heterogeneity,
particularly for scenarios in which LTE and UMTS are used, the work will
focuses on: “Designing distributed dynamic spectrum sharing techniques“The ultimate goals:Exploit temporal and special variation. Enhance spectrum utilization. Achieve minimum interference level on communications environment.Insure fairness among multiple operators.The Key feature:Competitive and Cooperative Environment.Address analytically the impact of multi‐cell, multi‐operator interference.Distributed scheme.Deploy by means of self‐organization and machine learning functionalities.
System Model
Results:
0123456789
10111213141516171819
Cel
l num
ber
(a) Current Spectrum Allocation
0123456789
10111213141516171819
Cel
l num
ber
(b) New Spectrum Allocation
opt.1Carrier 3
opt.2opt.1Carrier 2
opt.2Carrier 1
opt.2opt.1Carrier 3Carrier 2Carrier 1
opt.1 opt.2opt.1opt.2 opt.2opt.1
100 200 300 400 5000.92
0.94
0.96
0.98
1
Qua
lity
of S
ervi
ce (Q
oS)
30
32
34
36
38
40
42
BS
Pt(d
Bm)
50 100 150 200 250 300 350 400 450 500
0.4
0.6
Util
isat
ion
Inde
x (U
I)
Mobile User Density (MU/Km2)
Operator 1Operator 2
Avg. Pt FSA
Avg. Pt DSA
QoS DSA
QoS FSA
UI
Spectral efficiency gain
50 100 150 200 250 300 350 400 450 5000.92
0.93
0.94
0.95
0.96
0.97
0.98
0.99
1
Mobile User Density (MU/Km2)
Qua
lity
of S
ervi
ce (Q
oS)
forD=500m
forD=750m
Opt. 1 FSAOpt. 1 DSA
Opt. 2 DSAOpt. 2 FSA
D
Operator 1
Operator 2
CELL DSA Controller
CELL DSA Controller
CELL DSA Controller
Centralized Approach
Distributed Approach
Med
ium
-term
Shor
t-ter
m
Cellular Network (UMTS)
X2
X2X2
Femtocells:
Cellular Network (LTE)
An envisaged technical solutions could be found in the interaction between three
strategies;
Intra-DSA
BWopt2BWopt1
BW RAT 2BW RAT 1 BW RAT 2BW RAT 1
RAT 1 RAT 2 RAT 1 RAT 2
Inter‐DSA
Intra-JRRM
Intra-DSA
Operator Network 1 Operator Network 2
Intra-JRRM
Inter‐
JRRM
SON
Methodology
Joint Radio Resource Management:
Intra‐JRRM.
Inter‐JRRM.
Self‐Organizing Networks (SON),
Self‐configuration and Self‐planning.
Self‐Optimization and Self‐managing.
Self‐
healing.
Dynamic Spectrum Assignment:
Intra‐DSA.
Inter‐DSA.
Artificial scarcity
Spectrum under-utilization
Significant reuse opportunities
Introduce more flexibility on spectrum
Resolve spectrum scarcity
Cost Reduction
Better coverage
Distributed
algorithm,
machine
learning
and
self‐
organization
on
the
context
of
two‐layer
network
deployment
have
been
little
exploited
and
thus
constitutes
a
main novelty of this work.
Operator 1
Operator 2
Operator N ExecutionFramework
KPI
Analysis
DSATriggering
DSAAlgorithm
Feasibility Test
Several competing operators simultaneously co‐exist and share a common pool of radio
resources.
• Address the impact of multi-cell, multi-operator interference.• Distributed medium-term DSA algorithm among different
RATs, cells or operators. • Trigger DSA framework and execute the DSA algorithm to
find the optimal carrier allocation.
Co-located operators Displaced operators
The DSA algorithm improves the QoS
level and achieves
around 30% spectral efficiency gain compared with the FSA for
both operator networks.
The
utilization
index
shows
that
both
operators
have
fair
access to the spectrum resources.
The
algorithm
reduced
the
average
required
transmission
power of the BS by more than 4dB.
Summary
The
work
till
now
has
focused
on
dynamic
spectrum
assignment
strategies
over
a
DL
radio
interface
based
on
UMTS systems.
Cell‐Cell interaction based approach has been introduced.
Simple
medium‐term
DSA
algorithm
has
been
employed
in
order
to
enhance
the
spectrum
utilization
given
a
minimal interference level shared among multi‐operators.
the
DSA
algorithm
has
been
investigated
for
co‐located
and displaced cellular networks.
• Cooperative/non-cooperative deployment
• Short-term scheduler among users within a cell.• Extract main key performance indicators.
Priority-based and non-priority-based schemes.
Energy and Spectrum Efficient Adaptive Modulation for Cellular Systems
CCSR Research Symposium 2011 ‐ Talal
A. Alsedairy, Phd
Student
Abstract/Scope:•Increasing concern about the energy
consumption of cellular networks.•Optimise
energy utilisation
without sacrificing
user experience.•Spectrum
is
divided
with
rigid
boundaries
resulting in spectrum under‐utilisation.
•Introduction:Spectrum
sharing
between
operators
with
the
objective
of
energy‐efficient
operation. •Increasing
the
modulation
index
to
achieve
a
higher
data
rate
for
a
targeted
QoS,
which
increases the demand on energy. •Operator cooperation for energy minimisation.
System Model:•In order to minimise
the energy consumption, all
signal processing blocks need to be considered.
Spectrum Efficiency of Adaptive Modulation:•Operators
have
an
under‐utilised
spectrum
and
willing to share some of their spectrum.
Spectrum Sharing Simulation:•By
adding
under
utilized
spectrum
to
the
system.•New operating regions emerge. •The
system
can
serve
more
users
without
increasing
the
modulation
index = saving
operational
energy
=
best
region
for
the
system
to operate.
Conclusions:•All
signal
processing
blocks
need
to
be
considered
when
minimising
the
energy
consumption.
•By adding a fourth element to the problem new
regions of operation emerge.
•Operator
cooperation
can
benefit
all
operators
in
terms
of
energy
consumption
and
spectrum
utilization.
Transmitter Circuit Blocks
Energy-per-Bit Simulation:For a fixed SNR target, energy consumption per bit
increases exponentially with modulation index.
Receiver Circuit Blocks Symbol error rate increases
Frequency allocation over time for different operators
Constellation size
Spectrum
Energy Consumption
Adaptive Mobile Web Services
CCSR Research Symposium 2011 – Feda AlShahwan, PhD Student
Abstract/Scope
Reliable provisioning of complex Mobile Web
Services (MWSs) is a challenging task having to
cope with the limitations of mobile hosting
devices and wireless environment resources.
IntroductionMWSs
are self‐contained modular
applications that are defined, published and
accessed across the Internet, in a mobile
communications environment using standard
protocols.
Few research on adaptive MWSs
is based on
either partial or complete distribution
approaches
Motivations/ObjectivesInvestigating distribution mechanisms which facilitate continuous provision of complex
MWSs
in a light‐weight processing manner
provide instant information before it
becomes obsoletecompensate for the lack of mobile
resources
State of Art
Offload Execution Tasks:
light‐weight processing
Problem:
1.
Intermittent
connections (MH‐stationary
node) 2. Drains Battery Power
Offload Service Logic:
continuous provision of web
services.
Problem: 1. BW limitation
2.Heavy‐weight process
ImplementationTwo distinct prototypes have been
implemented and their performance
evaluated. The prototypes implement: Backend Bounce Offload BBO Frontend Forward Offload FFO
Results MH consumes less memory and
transmission capacity in BBO than its
corresponding FFO.
Summary/ConclusionsAdaptive MWSs
can be achieved by
exploring mechanisms for service
offloading and data migration.
Two different distribution strategies
proposed and investigated.
Basing distributed MWSs
on BBO is
more suitable for mobile environments.
System Model
Figure1:Backend Bounce Offload
Figure2:Frontend Forward Offload
Figure 3Amount of Memory Consumption for BBO and FFO
Figure4:Amount of data exchanged for BBO and FFO
Collaborative Spectrum Sensing Optimisation Algorithms
CCSR Research Symposium 2011 – Dr Kamran Arshad, Research Fellow
ObjectiveTo propose optimisation strategies for
collaborative spectrum sensing in terms of
fusion rule at an access point
To state collaboration requirements for
optimal fusion at cognitive access point
Major ContributionsHard decision fusion (HDC) is attractive but
we answer this simple question: for optimal
decision fusion does fusion centre needs only
1‐bit decision?
Study the impact of correlated shadowing
on decision fusion at fusion centre
Genetic algorithm (GA) based sensing
strategy for soft decision (SDC) is proposed by
incorporating both sensing and reporting
channels.
System Model
Observations and ConclusionsHDC: Considered different scenarios for
the problem of optimal fusion in the presence of channel fading. Conclusion is
only 1‐bit information is not enough for optimal fusion.
SDC: Finite reporting channel has direct impact on decision fusion. Proposed GA
based optimisation strategy gives superior than existing schemes.
HDC Results
Metho
dology
Case 1 - All users have similar SNRCase 2 – Half of the users have high SNRCase 3 – Only one user have high SNR
SDC Results
CR1
CR2
CRM
X
X
X
+
+
+
X
X
X
.
.
.
Fusion Rule
u1
u2
uM
g1
g2
gM
n1
n2
nM
w1
w2
wM
Sensing Environment
x1
x2
xM
Reporting Channels Fusion Centre
y1
y2
yM
ycGenetic Algorithm (GA)
10-3 10-2 10-1 10010-3
10-2
10-1
100
Probability of False Alarm, Qf
Pro
babi
lity
of M
iss
Det
ectio
n, Q
m
Pf vs Pm in AWGN channel with different SNR
EGC, no channel gainsSC, no channel gainsEGC, with channel gainsSC, with channel gainsOPT, with channel gainsOPT, no channel gains
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.80
0.1
0.2
0.3
0.4
0.5
Probability of False Alarm, Qf
Pro
babi
lity
of M
iss
Det
ectio
n, Q
m
OPT (case 2)PC (case 2)EGC (case 3)PC (case 3)EGC (case 2)OPT (Case 3)EGC (case 1)PC (case 1)
Pd and Pf are local probabilitiesS0 = group of users decided signal is absentS1 = group of users decided signal is present
Case 1 - All users have good channelsCase 2 – All users have bad channelsCase 3 – Two users have good channels
1-user Rule
HDC SDC
10-4 10-2 1000.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Pro
babi
lity
of d
etec
tion,
Qd
Case 1
10-4 10-2 1000.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Probability of false alarm, Qf
Case 2
10-4 10-2 1000
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1Case 3
OR - SimulationsOR - Analytical1 user - Analytical1 user - SimulationsVoting - AnalyticalVoting - SimulationsAND - AnalyticalAND - Simulations
10-4
10-2
100
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Pro
babi
lity
of d
etec
tion,
Qd
Case 1
10-4
10-2
100
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Probability of false alarm, Qf
Case 2
10-4
10-2
100
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1Case 3
1 user - Simulations1 user - AnalyticalOR - AnalyticalOR - SimulationsVoting - SimulationsVoting - AnalyticalAND - SimulationsAND - Analytical
QoS provisioning in MANETs
using Flow Aware Admission
Control protocol
CCSR Research Symposium 2011 – Muhammad Asif, PhD Student
Abstract/ScopeFlow Aware Admission Control (FAAC)
protocol maintains guaranteed throughput to the applications requiring QoS. FAAC
protocol implemented in two stages: Search the cache for untested path Check the local and neighbour resourcesIntroductionMobility and lack of centralized control
make QoS challenging
Reactive Routing protocols provide best effort services
FAAC ensures guaranteed throughput to the applications.
FAAC protocol is partially coupled with Dynamic Source Routing (DSR) protocol
Data sessions are admitted according to
the capacity of the networkMotivations/ObjectivesTo provide guaranteed throughput to the
applications requiring QoS and maximize
the session completion ratio.
System Model/DefinitionsEvery node act as source/destination as well
as router. Random Waypoint Model is used as mobility model. Carrier sensing range is
double of the transmission range.Main IdeasUse of untested route in cache Test the local and neighbours resources
during session requestTest the resources with full knowledge of
contention count
ResultsThe above figures show that the
session completion ratio of FAAC, DSR and CACP are 85%, 11% and 18%
respectively. The aggregate useful throughput are 157kbps, 18.8kbps and 28kbps for FAAC ,DSR and CACP.
Summary/ConclusionsFAAC protocol assures guaranteed
throughput Session completion ratio of FAAC is
very high comparatively to other analyzed protocol.
The protocol will extend to multipath
Route repair will be included
Figure 1. Capacity test at local and neighbor nodes
Improving Fairness by Cooperative Communications and Selection of Critical Users
CCSR Research Symposium 2011 – Juan Awad, PhD Student
Scope Selection of critical users Evaluation
of
metrics
to
choose
critical
users Exploring
new
techniques
to
improve
fairness and rates for the critical users
Introduction Critical
users
are
the
most
vulnerable
users in the system Critical
Users
can
be
VIP
users
with
higher service priority Known
solutions
cause
a
big
drop
in
spectral efficiency
MotivationsMany users fall in a critical region Can
Benefit
from
the
similar
proximity
to other base stations Aim
to
increase
fairness
without
a
big
loss in spectral efficiency.
System Model Three cooperating base stations OFDM DownlinkMaximal ratio transmission (MRT)
Main Ideas 3 BSs
constitute a distributed MISO
MRT eliminate interference Choosing critical users Critical users are served by MRT scheme
Sample Result
Figure 2: Empirical CDF of average users rates
Conclusions Improved Fairness for critical
users Limited loss in spectral
efficiency Flexibility and adaptability in
choosing critical users
System Model
Figure 1: System model frequency division
0 0.5 1 1.5 2 2.5
x 105
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
CD
F
Empirical CDF
Average Users Rates (bps)
J = 0.37
J = 0.827
Feature Descriptions for Automated Knowledge Derivation
CCSR Research Symposium 2011 – Hasini De Silva, PhD Student
AbstractKnowledge derivation is situation
dependentA Feature Description
scheme is
proposed to enable the automation of knowledge derivation
It specifies how knowledge regarding a particular feature should be derived
Introduction & Motivation:Automated adaptation of generic
applications requires deriving knowledge about target environments
Allowing target environments to govern the process of knowledge derivation
makes it simpler and efficientA mechanism is required to specify how
knowledge is to be derivedExisting approaches (e.g. query languages,
rule‐based methods) rely on a pre‐defined vocabulary which limits the
descriptiveness of the derivations
Feature DescriptionValue space
of the feature described using
an extendable base ontologyRules for metrics
defined in Fun RuleML
User‐defined functions used in rulesQualifiers to bind a domain of values to
variables in functions
ValidationPrototypes modules that utilise
feature descriptions to derive knowledge in terms of metrics were
developed in different environments (Jess and Prolog)
ConclusionThe integration of functional and
logic paradigms provides a comprehensive environment for
specifying metric derivation methods
The inclusion of user‐defined functions enhances the
descriptiveness of rulesThe use of qualifiers to describe
arguments of functions enables functions with an arbitrary number
of arguments
EnvironmentKnowledge derivation is addressed in terms
of deriving metrics from feature values (e.g. distance
metric of two values of the location
feature)
Aligning the SensorWeb with the IoT
vision
CCSR Research Symposium 2011 – Suparna De, Research Fellow
ScopeThe Internet of Things concept envisions a
multitude of sensors interacting with the physical
environment and providing real‐world services.
Development of sensor technology has involved
diverse sensor types, with varied capabilities. The
relevant wireless sensor networks also feature
heterogeneous protocols.
IntroductionSensor services can be identified as atomic
functionalities, e.g. reading a sensor value. Current
efforts to offer sensor measurement data in a
homogeneous and application‐processible
way
include:OGC’s
XML Schemas for sensor descriptions and
web service interface definitions for accessing
data.Sensor gateway implementations employing a
limited set of web service standards.
ObjectivesKnowledge in the virtual world needs to be
integrated with the real‐time state of the physical
world. Bringing a large number of networked,
resource limited sensors to the IoT
vision requires:providing semantics to measured sensor values to
create situation awarenessoffering sensor services in a lightweight manner.
Main IdeasSemantic Sensor Description Raw sensor measurement values
annotated in RDF: metadata (data type, unit of measurement, time stamp)
includes information to interpret value RESTful
sensor access
Lightweight mechanism using HTTP to
access sensor values. RESTful web service
interface for retrieving sensor data.
ImplementationRESTful
client application retrieves
semantically annotated temperature
sensor valuesMetadata used to process average
temperatureThreshold value manipulated
through GUI (HTTP PUT to REST
client)Actuator triggered if average
temperature < threshold
ConclusionsRESTful
services suitable for offering
basic functionalities of embedded
sensorsUniversal web‐based API for
sensors ‐> real world services offered to the virtual world
Semantics will allow enhanced reasoning capabilities
Web enablement will allow horizontal collaboration of sensorservices with enterprise services
Sensor data
MySQL sensor database
RESTful sensor application
Annotate measurementsUnits ontologyXML data types
REST client
HTTP GetSemantic sensor observation (RDF
envelope)
Get observed value
Create RDF envelope
REST client GUI
Dual Circular Polarisation Multiplexing for the Satellite Component of DVB‐NGH Systems
CCSR Research Symposium 2011 – Unwana M. Ekpe, PhD Student
AbstractDual Circular Polarisation multiplexing (DCPM) has been
proposed
for
use
in
2x2
land
mobile
satellite
(LMS)
multiple‐input
multiple‐output
(MIMO)
channels
to
increase capacity/spectral efficiency.
Motivation and ObjectivesIncreasing demand for wireless multimedia services has
brought
about
the
terrestrial
deployment
of
spectral
efficient
MIMO
techniques.
However,
the
LMS
channel
is peculiar , giving rise to the following question:
can
eigen
beamforming
or
other
MIMO
techniques
work for 2x2 LMS MIMO channels, since these channels
are
predominantly
line‐of‐sight
(LOS)
and
are
devoid
of
scatterers
close to the satellite?
The objective of this work is:
to determine the type of MIMO technique that best
suits LOS LMS channels and how much capacity increase
is derivable.
Work Done and Main Research Ideas
Two orthogonal circular polarised antennas on a
satellite and a mobile terminal creates a 2x2 MIMO
channel.
Zero
forcing,
a
simple
receiver
based
equalisation
scheme, is used in removing interference.
Two
bit
streams
sent
through
the
available
channels
are multiplexed at the receiver, doubling capacity. Single satellite DCPM can complement DVB‐NGHbroadcasts where terrestrial network is non existent.
Channel Capacity ResultsThe
diagram
below
shows
average
DCPM
capacity
compared
with
that
of
conventional
MIMO
in
a
highly
correlated
LOS
channel,
labelled
channel
1,
and
in
an
obstructed
LOS
channel
with
reduced
channel
correlation,
labelled
channel
2.
In
channel1,
observe
that
when
receiver
SNR
is
less
than
12dB,
DCPM
outperforms
MIMO.
Decreased
channel
correlation
adversely
affects
DCPM
capacity
but
has less effects on MIMO.
DCPM System Architecture
ΣY11
ΣY22
Weight W22
Y1
Y2LHCP
antenna
RHCP antenna RHCP
LHCP
hRR
hRLhLR
hLL
Weight W11
Weight W12
Weight W21ConclusionsIt
has
been
found
that
the
mobile
terminal
based
DCPM
provides
superior
channel
capacity
to conventional MIMO at low receiver SNRs.This
favours
the
adoption
of
DCPM
in
the
on‐
going DVB‐NGH standardisation process.land mobile
terminal
satellite
Conventional MIMO – Modify for Satellite
Systems?
Multiple antennas, rich scattering – spatial multiplexing
Multiple
antennas,
no
scattering
at
one
link‐end
– eigen
beamforming
Two
antennas
at
both
link‐ends,
no
scattering
at
one
link‐end, LOS conditions –
what can be done?
Eigenvalue
The dual polarised LOS MIMO channel has two
strong eigenmodes
in which independent bit
streams can be sent through
P(eigenvalue
< abscissa)
Smart Middleware for Wireless Sensor Networks
CCSR Research Symposium 2011 – Frieder
Ganz, PhD Student
AbstractSensors will play an important role in our future daily life.
Ongoing
research
areas
such
as
Smart
Homes,
Healthcare
and
the
Future
Internet
leverage
the
use
of
sensors
in
combination
with
Web
data
and
services.
Utilising
and
integrating
this
information
are
the
key
issues
to
enable
future
environment
and
user
aware
networks
and
applications.
Gateway for Sensor NetworksWe
introduce
a
middleware
design
which
addresses
the
emerging
issues
by
constructing
a
homogeneous
framework
to
connect
heterogeneous
sensor
networks
and providing decision making mechanism to optimise and
utilising
resource
constrained
wireless
sensor
networks
in
distributed environments.
MotivationsCurrent
key
approaches
such
as
GSN
and
the
OGC
Standard
lack
of
several
self‐*
features.
Our
approach
includes such reflective features such as self‐configuration
and
discovery.
Most
available
platforms
are
not
proper
designed for distributed environments.
Key Contributions:
Easy discovery and association of nodes as in
802.11 networks
Distributed device registry with update and
query mechanisms
Integration with CCSR Linked Data platform
to create Networked Knowledge.
Caching and Prediction of values (nodes) to
save energy
Integration into CCSR Linked Data Platform
Future WorkIn
future
one
interesting
point
is
to
make
the
information
available
to
the
user. We
will
introduce solutions to provide flexible and scalable
data access from wireless sensor networks to
high
level
applications/users.
Another
aspect
is
integration
of
data
into
business
environments
and
providing
discovery
and
search
mechanisms
for
distributed
sensor
data
and
sensor
observation.
Architecture
A Fuzzy Reinforcement Learning Approach for Pre‐Congestion Notification based Admission Control
CCSR Research Symposium 2011 – Dr Stylianos Georgoulas, Research Fellow
ScopeThe
aim
of
this
work
is
to
introduce
fuzzy reinforcement
learning
to
the
Pre‐Congestion
Notification
(PCN) framework for admission control.
IntroductionAdmission
control
(AC)
is
a
control
function that
attempts
to
control
Quality of
Service
(QoS)
by
rejecting
new flow requests when/if needed.The
major
drawback
of
existing
approaches is
that
they
rely
on
very
rigid assumptions
about
the
traffic
and
network characteristics.
Therefore,
manual tuning
is
needed
whenever
these assumptions stop being valid.
ObjectivesIntroduce
self‐x
behaviour
to
PCN‐
based admission
control.
Develop
schemes that are able to self‐adapt.
System ModelPCN
applies
to
core
network
segments.
It requires the existence of a traffic class that receives preferential treatment and relies
on
packet
marking
to
deduce
the
AC decision.
Main IdeasUse
fuzzy
Q‐learning
(FQL)
to
drive
the
threshold reconfiguration
that
affects
the packet marking behaviour.
ResultsThe FQL modules are being
developed and integrated in the ns‐2 simulator.
SummaryOnce
fine‐tuned,
this
approach
will allow
for
fully
autonomic
PCN AC
mechanisms,
able
to
continuously learn
and
adapt
based on previous actions.
PLR/traffic
highmedlow
trend of PLR/traffic
positiveneutralnegative
neutralnegative
threshold adjustment
positive
Example rule : If {PLR is low and trend of
PLR is negative} (S1) then: threshold
adjustment is {positive Q(S1,A1), neutral
Q(S1,A2), positive Q(S1,A3)}
Design verification of future networks architectures
CCSR Research Symposium 2011 – Dr Majid Ghader, Research Fellow
Abstract/Scopea formal method for evaluation of the
correctness of components’ design and
stability of control loops within the
self‐organised network architecture
IntroductionAcme
Architecture Description
Languages (ADL) To enable formalisation
and
verification of the architecture of
systems Aiming at identification
and
resolution of design problems
in the
early stages of development.
To validate a scenario modelling a
typical control loop in Acme Studio
Motivations/ObjectivesRectifying
initial design problems at
the early stages to avoid
costly
corrections at the development
stage
System Model/Definitions‐Families‐Elements‐Components‐ConnectorsMain IdeasModelling the system in terms of the
above components Verifying validation of the rule Potential analysis of the system
Sample ResultsHow the Acme
and Armani
constraints help in verifying the correctness of a scenario
Extensible to other rules
Inappropriate for performance
analysis, scalability evaluation and network simulations
Summary/Conclusions Shown formalities
for describing
control loop architecture, expressed in text interpreted into a proper
predicate language Shown a network architect
verifying validity of a scenario
based on the components of proposed network architecture, and
checking the fulfilment of different
principles and properties in terms of the rules of the particular formal
languages (Acme and Armani)
Scenario, implementation and screenshot
Governance
NetworkResource
Knowledge
rule rule01 = invariant forall s1 : AbstractStratum in self.COMPONENTS | forall s2 : AbstractStratum in self.COMPONENTS |
forall ssp1 : SSPType in s1.PORTS | forall ssp2 : SSPType in s2.PORTS | declaresType(s1,KnowledgeStratum)
AND declaresType(s2, GovernanceStratum)AND connected(ssp1, ssp2) -> ssp1.direction == output AND ssp2.direction == input;
‐Ports‐Roles‐Properties
Asynchronous Multi‐channel MAC Protocol for VANETs
CCSR Research Symposium 2011 – CHONG HAN, PhD Student
Abstract/ScopeA new multi‐channel MAC protocol for
VANETs
is proposed, namely, Asynchronous
Multi‐Rendezvous Multi‐Channel MAC
(AMCMAC) to improve network
performance in large scale vehicular
networks in terms of large number of
nodes in the complex vehicular
environment.
IntroductionIn a multi‐channel system, both non‐safety
and safety related applications could be
provided on different channels, which
could help improve QoS
support for
different application types by allocating
them to different channels.
Motivations/ObjectivesCurrent multi‐channel MACs
performs poor
in terms of system throughput, and
penetration rate of successfully broadcast
emergency messages. Multi‐channel
hidden terminal problem is not solved
properly.
System Model/DefinitionsEmergency messages are broadcast on
control channel, which is used for channel negotiations as well. Other
categories of traffic are arranged to service channel.
Main Ideas Avoid unnecessary renegotiations Use the LBT and channel selection
mechanism to avoid collisions on service channels
Sample ResultsThe proposed AMCMAC
protocol outperforms the IEEE 1609.4 and AMCP scheme in
terms of system throughput, channel occupation time and the penetration rate of
successfully broadcast emergency messages.
Summary/ConclusionsImprove the system
performanceOutperform the IEEE
1609.4 (Synchronous), and AMCP (Asynchronous)
Solve the multi‐channel hidden terminal problem
Solve the missing receiver problem in multi‐channel
scenarios
Sensing and Emulation Hardware for Advanced IOT Experimentation
CCSR Research Symposium 2011 – Dr William Headley, Research Fellow
Abstract/ScopeThe
work
described
herein
seeks
to
develop
sensing
and
emulation
hardware
for
use
in
the
Internet
of
Things
and
Persuasive
Technologies
experimentation.
This
hardware
will
be
utilised
to
ascertain
a
user’s
energy
consumption
patterns
whilst
also
providing
a
context of how that energy is being used.
IntroductionA
hardware
platform
has
been
developed
which
will
allow
researchers
from
various
disciplines
to
study
how
efficiently
energy
consumers
utilise
their
energy
consumption. This
hardware
platform
comprises
a
multitude
of
nodes
named
Persuasive
Energy
Nodes
(PENs)
(see
Figure
1). These
PEN’s
are
capable
of
measuring
the
energy
consumption
of
any
device
plugged
into
it. Additionally,
a
sensor
array
has
been
built
into
the
unit
in
order
to
measure
certain
environmental
aspects
of
the
area
around
where
the
energy
is
being
consumed
(topmost
box
in
Figure
1).
The
PEN’s
house
a
TelosB
mote
to
allow
for
the
capture of the sensor data as well as the capability to
transmit
data
wirelessly
to
either
nearby
motes
or
a
local
gateway
(see
Figure
2). The
PEN’s
also
house
a
USB
hub,
PIC
and
current
sensing
circuitry
to
further
enhance the capabilities of the unit.
Motivations/ObjectivesThe
motivation
behind
the
development
of
this
hardware
platform
is
to
allow
researchers
to
monitor
and
identify
inefficient
energy
consumption
patterns
of a user
System Model/DefinitionsBy determining some basic aspects of an energy consumer’s
environment, one can attempt to determine if this energy is
being consumed efficiently and in doing so, possibly affect a
change in their behaviour.
Main Ideas
Define the context of a user’s energy consumption by
monitoring: Noise (amplitude sample and slow decay circuit)Movement (PIR sensor) Lighting (visible light photodetector) Temperature (solid state temperature sensor) Energy consumed (commercial energy monitoring unit)
Sample ResultsInitial
prototypes
of
the
PEN’s
have
been
realised
and
a
small
number
of
units
(10)
have
been
deployed
in
order
to
test
their
ability
to
create
a
useful
context
of
energy
consumption
by
a
user
in
an
office
environment. The
unit
requires
approximately 100mA of current
to
function
properly (which includes the sending of data
wirelessly). Figure
4
demonstrates
the
concept of monitoring the energy consumed
by
a
user
(black
line)
as
a
function
of
time
and
in
relation
to
the
time
the
user
is
actually
in
the
room
(greyed
area). Thus
energy
consumption
in
the
white
areas
is
energy
that
has
been
potentially
wasted
as
the
user
was
not
present
when
the
energy
was consumed.
Summary/ConclusionsMass
fabrication/deployment
of
a
second
generation
of
PEN
unit
is
currently
underway. Future work on these devices will
seek to incorporate:
RFID technologyActuator and corresponding intelligenceLower cost/lower energy consumption
sensors
Figure 2. TelosB mote (left) and optocoupler board (right) which are housed within the
PEN.
Figure 3. USB hub, PIC, current sensing and virtual sensor
circuitryFigure 1. The
Persuasive Energy Node (PEN)
Figure 4. Energy consumption as a function of time and user presence
(data compiled by M. Nati)
Efficient Pairing non‐interactive Key Distribution Protocol for the Internet of Things
CCSR Research Symposium 2011 – Dr Dan He, Research Fellow
Abstract/ScopeKey distribution is a challenge in the
Internet of Things(IoT) due to the limited resources of networked
devices. PKI based approach is neither efficient nor secure. This paper
proposes a lightweight pairing based non‐interactive key distribution
protocol with provable security.
IntroductionKey distribution has two issues in IoT:
Restrict to use the advanced cryptographic algorithm; PKI inapplicable. Key distribution protocols
usually involve message exchanges.
Motivations/ObjectivesNon‐interactive key distribution
reduces the message exchange overhead. This can be done by identity‐
based cryptography.
DefinitionsIf an efficient algorithm A can solve BDHP
problem at time slot t, then the probability
of computing bilinearity
is the same as A.
Main Ideas
Our protocol is based pairing secure
primitives on the hardness of bilinear Diffie‐
Hellam
Problem(BDHP).
Each sensor node can perform the
protocol above to establish the shared
security.
Performance ResultsThe protocol is secure to prevent type I
and II attackers.Execution time where r and q are group
order of finite fields
ConclusionsPairing based key distribution is
a new approach. It is efficient and secure for IoT. Future work
will be implementation on real sensor board. In summary, this protocol is:
Non‐interactiveSave bandwidthSimple and Secure Efficient and fast
Key Distribution Protocol
Space‐Time Cooperative Positioning in Mobile Networks
CCSR Research Symposium 2011 – Ziming He, PhD Student
Abstract/ScopeThis work proposes a novel mobile
network based cooperative positioning approach, which can jointly exploit
spatial cooperation and temporal cooperation. Numerical results show that
the proposed approach can significantly improve the accuracy of position
information.
IntroductionCooperative positioning is an emergingparadigm that circumvents the needs for
high‐power, high‐density access point
(AP) deployment and offers additional positioning
accuracy by enabling the
mobile terminals (MTs) to help each
other in estimating their positions.
Motivations/ObjectivesCurrent work on cooperative positioning
only considers spatial cooperation
System ModelWe consider a mobile network, where a
mobile can communicates with access points and neighbouring mobiles (see above figure).
Main IdeasAs depicted in the above figure, the main
idea is to employ an embedded odometer or pedometer to measure the travelled
distance between adjacent states.
Sample Results
the proposed approach can improvepositioning accuracy with high
mobility of the MTs.
Summary/ConclusionsThis work proposes a novel
mobile network based cooperative positioning
approach, which can jointly exploit spatial cooperation and
temporal cooperation.
the APs
(A, B, C and D) communicate with two MTs. p1,k−1 and p1,k−1
denote position of MT 1 at the (k −
1)‐th and the k‐th
states, respectively;
p2,k−1 and p2,k−1 denote position of MT 2 at the (k−1)‐th and the k‐th
states, respectively. At the k‐th
state, either MT can estimate its
positions based on the signal from its neighbouring nodes, as well as the
travelled distance between the (k −
1)‐th and the k‐th
states.
A
B D
C
p1,k
p2,k
p2,k-1p1,k-1
communication linkstraveled distance
Sample Results
Summary/ConclusionsBy intelligently organizing beam
vectors with one‐bit feedback, the achievements can be summarised :
The sum‐rate of primary microcell has been additionally increased.
Inter‐cell interference can be eliminated with suitable variables.
For keeping the sum‐rate of secondary microcell, the number of
MTs in it has to be sufficient large.
Base Station
khkb
1K
k
.. ..
Relay Station 2(RS-2)
....
N
Relay Station 1(RS-1)
1
n
.. ..
....
ng
na
Intra-cell Overlay OpportunisticSpectrum Sharing Network
Primary microcell Secondary microcell
Intra‐cell Overlay Opportunistic Spectrum Sharing By Employing One‐bit Feedback Beamforming
CCSR Research Symposium 2011 – Jiancao Hou, PhD Student
Abstract/ScopeWe propose a novel strategy for intra‐cell
overlay opportunistic spectrum sharing where one‐bit feedback beamforming
is
available. By optimizing the beam vectors, secondary transmitter can help primary
users send useful messages while eliminating inter‐cell and intra‐cell interferences.
IntroductionRapid growth of wireless services
continues to overload the spectrum resources. Cognitive MIMO beamforming
with limited feedback is an intelligent method to enable opportunistic spectrum
reuse. One of fundamental problems on this topic is how to optimize the beam
vectors with limited feedback in crosstalk environments?
Motivations/ObjectivesFacing up overloaded spectrum, how to
reuse it by employing one‐bit feedback beamforming?
System Model/DefinitionsBase station
broadcasts messages to RS‐1 and RS‐
2, both RS‐1 and RS‐2 can decode their own messages and the messages from the other, and
then forward the selected messages to the appropriate mobile users.
Main IdeasRS‐2 iteratively constructs the first beam vector for
helping RS‐1 send useful messages, and then it
produces the rest orthogonalized
beam vectors to be
orthogonal with the first one, in order to suppress
inter‐cell interferences.
Distributed Load Balancing through Self Organisation of Coverage
CCSR Research Symposium 2011 – Ali Imran, Research Fellow
Abstract/Scope:A novel distributed traffic load balancing solution Reduces call rejection probability (close to globally optimal)Based on an analytical framework Inspired from principles of self organization in nature
Introduction:State of the art: [Glenn, Imran et Al 2011]
1) Resource Adaptation based LB2
) Traffic Shaping based LB3)RS based LB4)Coverage Adaptation based LBcentral control/ heavy signalling low scalability and agility that are the desired features of SO.
Our Solution : Load balancing through BSOF (LB‐BSOF)System wide self organisation of coverage in distributed manner
such that the load remains balanced in face of medium to long term
dynamics keeping the blocking close to the minimumDo not require central control/global signalling
Motivations/Objectives:System Model/Definitions:‐Multi cell wireless system ‐Circuit switched, no queuing‐system wide blocking:
Main Ideas:
Sample Results:
Conclusions:Over 270% reduction in blocking Near optimal performanceVery low complexity Very low signallingCopes with ever changing demographyFuture Work: Investigating LB‐BSOF with
handover and packet switching
Biomimmetic Self organisation
Framework (BSOF)Extracted design and operational principle of self organisationAnalysis of case study of flock of Common Cranes
CCSR Research Symposium 2011 – Bahareh
Jalili, PhD Student
Abstract/Scope
IntroductionAdjacent base station coordination is an efficient
technique in radio resource allocation:Reduces interference, particularly in the cell edges
• Improves spatial diversity gain• Allows more effective power allocation
Traditionally, coordinated resource allocation
schemes are implemented in BSC/RNC.Modern cellular systems (4G and beyond) eliminate
BSC/RNC from their network architectures in order to
reduce latency in resource allocation
Motivations/ObjectivesTo
investigate
the
feasibility
and
performance
of
distributed
implementation
of
coordinated
radio
resource allocation in modern cellular networks.
System ModelThree adjacent 3‐sector BSs
Area covered by 3 most interfering Sector
Antennas (SA)
SAs
collaborate in
resource allocation using back
haul links
S11
S21S23
S22
S12
S13
S31
S33
S32
Underlying Complex ProblemMaximize Total system throughput
(Over different SAs
, Resource Blocks
(RB) and power allocations) Subject to:Only one user served on each RBTotal allocated power Fairness constraints
......
Conceptual Radio Resource Management Systems for
the Packet Radio Network:Collaborative radio resource allocation and scheduling
is the main focus
Principle Scheduling Policy Proportional Fair Scheduling
A set of Resource Blocks are dedicated for the
users in the common area of the cell edges.
Proposed Heuristic Solution Break the problem into two sub‐problems: RB
allocation Power allocation Equal Power Allocation
Serial RB selection and power allocation using
Water‐Filling
Distributed RB selection with Centralized
Water‐Filling
Distributed RB selection with Distributed
Water‐Filling
Distributed Collaborative Scheduling Scheme
Each SA independently : Calculates a ”Scheduling Coefficient” (SC) for each user
on each RB These coefficients are placed in a ”Scheduling Coefficient
Matrix” (SCM) A matrix of highest SCs
on each RB is prepared (Best
Matrix) Best Matrix is shared with neighboring SAs
Local Scheduling Decision
Each SA appends all the 3 Best Matrices For each
RB, the SA that has the highest SC will serve the user
on that RB
Total System Throughput Gini Fairness Index
Distributed and Collaborative Radio Resource Allocation in the Downlink of OFDMA Systems
Asymmetric Users Around the Cell Edge Area:
Results /SummarySignificant gain can be achieved even by
implementing sub‐optimal distributed
collaborative
schemes.
Resource‐Friendly Authentication Scheme for Disruption Tolerant Networks
CCSR Research Symposium 2011 – Enyenihi
Henry Johnson, PhD Student
Abstract/ScopeAn
authentication
scheme
for
disruptive
networks based on Delay/Disruption Tolerant
Networking
(DTN)
concept
is
proposed. Its
comparison
with
existing
schemes
is
made
and its comparative advantages established.
IntroductionDisruption
tolerant
networks
are
networks
with intermittent connectivity caused by high
node
mobility,
short
range
of
radio
frequency, low battery power, no line of sight
etc.
Existing
authentication
schemes
perform
poorly
in
these
networks
due
to
either
their
interactive
and
resource
exhaustive
nature,
design
principle
or
operational
complexity.
This calls for a new concept in authentication
as illustrated in the figure.
Motivations/ObjectivesTo address authentication issues in disruptive
networks while preserving network and node
resources.
System Model/DefinitionsEach entity generates its key pair and must
be registered
and
authenticated
before
communications. Registration
Authority
(RA) and
Network
Administrator
(NA)
are
trusted and must not be compromise. Main Ideas• Use
symmetric
based
hash
message
authentication code (HMAC)• Use
third
party
certified
asymmetric
mechanism for source authentication
Comparative AnalysisAs
shown
above
in
the
table
is
the
comparative
analysis
of
our
scheme
with
existing
schemes
assuming
one
intermediate
node
between
source
and destination.
Summary/ConclusionsOur proposed scheme:Is more resource efficientPlaces no load on the serverCan operate without
continuous network connectivityValidation will be carried out
through simulation in connected and disruptive environment.
Registration Phase: Once1. Alice →
RA: PbRA
{devIDA
, rtjDTN network}
2a. RA →
Alice: PbA
{devIDA
, secInfoA
, IDNA
, secInfoNA
, PbNA
}2b. RA →
NA: PbNA
{nfa, devIDA
, secInfoA
}
Authentication Phase: Once3. Alice →
NA: PbNA
{rtj, devIDA
, secInfoA
, PbA
}4. NA→Alice: PbA
{auConf, IDNA,
, secInfoNA
, Kdtn
, APassA
}
Data Exchange: Anytime after Authentication5. Alice →
Bob: [PbB
{Hello} |{APassA
,NA
} | {Tstmp, IDA
, IDB
}]∙hmac5b.Alice→Bob: [{KR
(BkMesg), PbB
(KR
)} | {APassA
, NA
} | {Tstmp, IDA
, IDB
} ]∙hmac6.Bob→Alice: {isAccepted, APassB
, NA
}∙hmac
Analysis Metrics Authentication Protocols
Kerberos N‐S‐L Asokan Our
Protocol
Total number of exchanges 8 12 8 4
No of recipient contacts with
the server1 3 2 0
No of cryptographic operations
by server10 6 4 0
No. of cryptographic operations
by intermediate Nodes6 7 7 5
No. of keys used 7 8 6 4
Performance study of GLOSA using an integrated cooperative ITS simulation platform
CCSR Research Symposium 2011 – Konstantinos
Katsaros, PhD Student
Abstract/ScopeThis
project
is
an
application
for
the
communication
between
traffic
lights
and
vehicles
in
order
to
gather
and
process
information
about
traffic
light
timing
and
provide
an
advisory
speed
to
the
vehicle
driver to reduce fuel consumption.
IntroductionVehicular
communications
can
assist
to
reduce average fuel consumption especially
under
high
traffic
density
and
long
traffic
light
cycles.
We
investigate
the
impacts
of
V2I
communications
on
fuel
efficiency
and
traffic
efficiency
using
an
integrated
cooperative ITS simulation platform
ObjectivesIncrease traffic efficiency (less stopping
time)Reduce fuel consumption and emissionsin urban areas through C2X
communications.
GLOSA (Green Light Optimal Speed Advisory)The application scenario has two elements, the traffic light and the vehicle. Each of them equipped with a unit: RSU (roadside unit) in the traffic light and OBU (onboard unit) on the vehicle. The RSU gets information from the traffic light about timing, position etc and broadcasts it periodically. On receipt of that message the OBU calculates the time needed to reach the traffic light. From the information of the message it calculates the status of the traffic light at the time it reaches it. If it is green, it can continue its journey. If it is red, it calculates the remaining time for red phase, and provides the driver with an advisory speed in order to reach the next traffic light in a green phase. This information will be provided to the driver through a visual or audible HMI.
Summary/ConclusionsResults
suggest
that
GLOSA
application
has
a
positive
effect
on
both fuel consumption and stopping
time.
Thus,
such
an
application
can
be
incorporated
into
future
vehicles
to reduce their carbon footprint and
accommodate
their
drivers
with
a
smoother trip. Future work includes:Dynamic Traffic Light AdaptationTaking into account traffic
congestion
eXtended User Interfaces (xUIs)
CCSR Research Symposium 2011 – Dr Ralf KeNJƴŎƘŜƴΣ wŜǎŜŀNJŎƘ CŜƭƭƻǿ
Abstract/ScopexUIs
present a service front‐ends concept to intelligently
incorporate real‐world objects, such as digital appliances, networks of displays, user interaction devices, etc. for
ubiquitous services delivery.
Service
Service
Service
Bob’s display
Ralf Kernchen, Stefan Meissner, Klaus Moessner, Pablo Cesar, Ishan Vaishnavi, Matthieu Boussard, and Cristian Hesselman, "Intelligent Multimedia Presentation Delivery in Ubiquitous Multi-Device Scenarios," IEEE MultiMedia, vol. 17, no. 2, pp. 52-63, Apr. 2010, doi: 10.1109/MMUL.2009.75
Ying Du, Ralf Kernchen, Klaus Moessner, Christian Räck, Oliver Sawade, and Stefan Arbanowski, "Context-aware Learning for Intelligent Mobile Multimodal User Interfaces," in Proceedings of the 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2007), Athens, Greece, 2007, pp. 1 - 5.
Introduction
Idea stems from research in Human Computer Interaction and
Ubiquitous/Pervasive ComputingAllowing users to interact more
natural with Internet of Things applications
Motivations/Objectives
Allow applications to “surround” the user by integrating
seamlessly in the environment vs. single point of entry (mobile devices, web)
Integrate context information by leveraging the Internet of Things
Support users to retrieve relevant information in and about their current environment
Flexible Frequency Reuse schemes for heterogeneous networks (macrocell and femtocell)
CCSR Research Symposium 2011 – Valantis Kosta, PhD Student
AbstractA
flexible
frequency
re‐use
scheme
to
increase
the
capacity
of
heterogeneous
cellular
system
i.e.
macrocell
cell‐edge
and
femtocell
overall
throughput.
Simulation
results
confirm
the
effectiveness
of
the
proposed
scheme
in
both
macrocell
and
femtocell
networks
compared
to
a
number
of
schemes
in
the
literature.
MotivationThe
Interference
problem
is
a
major
issue
for
multi‐cell
OFDMA networks (macrocell and femtocell)An
interference
aware
radio
resource
management
(RRM)
algorithm in a multi‐cell system is prohibited complexFrequency‐partitioning
schemes
for
OFDM‐based
network
are
feasible
and
low
complexity
practical
solutions
for
multi‐
cell environmentCurrent state‐of‐art re‐use frequency allocation schemes do
not benefit heterogeneous cellular networks Our
flexible
re‐use
scheme
aims
for
heterogeneous
cellular
systems to enhance the cell‐edge and overall throughput
System Model
Results
Increase of eNB
cell‐edge throughput.
Increase of overall HeNB
throughput.
Minimum reduction of overall eNB
throughput
SummaryA flexible frequency re‐use scheme was proposed
to benefit heterogeneous networks.
Simulation results show the effectiveness of the
proposed scheme
Future WorkExtend the research to semi‐static/dynamic
schemes in order to exploit the dynamics of the
network
Investigate distributed frequency allocation
algorithm with /without learning capabilities
Investigate more indoor multi‐cell environments
i.e. 5x5 grid and dual stripe
Technical Approach
1
2
3
4
5
6
7
cell edgeP cell centerP
Frequency
Pow
er
1
2
3
4
5
6
7
cell centerP
cell edgeP
Frequency
Pow
er
7
23
3 72 2 3
7
4
67
7 46 6 7
43
56
6 35
5 6
36
12
2 61 1 2
65
71
1 57
7 1
51
34
4 13 3 4
1
2
45
5 24 4 5
2
7
23
3 72 2 3
7
4
67
7 46 6 7
43
56
6 35
5 6
36
12
2 61 1 2
65
71
1 57
7 1
51
34
4 13 3 4
1
2
45
5 24 4 5
2
FFRSFR
Graphical Illustration of the sub‐cell regions of the flexible frequency reuse scheme. Each sub‐cell
is associated with a frequency group which is orthogonalized
with other groups through power
amplification (SFR)/ reduction or through frequency restriction (FFR).
Parameters Values
Total Bandwidth 20 MHz
Site-to-Site Distance 500 m Antenna model Berger
eNB Power 43 dBm HeNB Power 10 dBm
Main fading loss parameter Path loss model Outdoor path loss model L = 128.1 + 37.6 log10D Indoor path loss model L = 127 + 30 log10D
External wall loss 10dB Inter-distance of UEs 1 per 20m2 Inter-distance of FEs 1 per 61m2
CQI No
Modulation & Coding Scheme
Spectral Efficiency (bps/Hz)
SINR Threshold
1 QPSK 78/1024 0.1523 -6.94 dB 2 QPSK 120/1024 0.2344 -5.14 dB 3 QPSK 193/1024 0.3770 -3.18 dB 4 QPSK 308/1024 0.6016 -1.25 dB 5 QPSK 449/1024 0.8780 0.76 dB 6 QPSK 602/1024 1.1758 2.67 dB 7 16QAM 378/1024 1.4766 4.69 dB 8 16QAM 490/1024 1.9141 6.52 dB 9 16QAM 616/1024 2.4063 8.57 dB
10 64QAM 466/1024 2.7305 10.36 dB 11 64QAM 567/1024 3.3223 12.29 dB 12 64QAM 666/1024 3.9023 14.17 dB 13 64QAM 772/1024 4.5234 15.88 dB 14 64QAM 873/1024 5.1152 17.81 dB 15 64QAM 948/1024 5.5547 19.83 dB
50 100 150 200 250 300 350 400 450
50
100
150
200
250
300
350
400
0
5
10
15
20
50 100 150 200 250 300 350 400 450
50
100
150
200
250
300
350
400 -25
-20
-15
-10
-5
0
5
10
15
20
25
Table of SINR mapped with Spectral Efficiency Main Simulation Parameters
SINR in a 19‐cell layout with tri‐sectorized antenna Shadowing experience by central base station
Re-use scheme
Average HeNB T-put in Mbps
(% change)
Average eNB T-put in Mbps
(% change)
Average eNB cell-edge T-put in Mbps (% change)
FR1 70.06 46.70 19.30
FR3 72.67 (+3.74%) 35.68 (-23.6%) 23.73 (+23%)
SFR 1/3 92.74 (+32.38%) 42.49 (-9%) 37.45 (+94%)
FFR 1/3 79.18 (+13.03%) 39.76 (-14.9%) 44.28 (+129.4%)
SFR 3/7 99.60 (+42.18%) 41.86 (-10.4%) 39.73 (+105.8%)
FFR 3/7 98.18 (+40.14%) 44.41 (-4.9%) 38.97 (+101.9%)
Performance Evaluation of Energy Detection in Cognitive Radio
CCSR Research Symposium 2011 – Xing LIU, PhD Student
Abstract/ScopeSpectrum
sensing
plays
an
important
role
in
cognitive
radio
systems.
Results
of
spectrum
sensing
depend
on
the
performance
of
employed
sensing
techniques.
My
current
work
focuses on novel performance evaluation of the
most
common
spectrum
sensing
techniques
–
energy detection.
IntroductionUp to now, various spectrum sensing techniques
have
been
proposed
among
which
the
energy
detection is noted for its simplicity and requiring
no
a
priori
information.
The
performance
of
energy detector has been extensively studied in
the
past.
Its
high
performance
under
good
channel
conditions
and
severely
decreased
performance
due
to
system
model
uncertainty
and low SNR have been shown in many papers.
Motivations/ObjectivesAlthough there have been many generic studies
of
the
energy
detection,
there
has
been
little
detailed study of its application in more realistic
scenarios.
So
a
new
analysis
and
performance
for the energy detection is desired.
System Model/DefinitionsA
radio
spectrum
usage
model
consisting
of
two
elements,
primary
system
and
secondary
cognitive
system.
The
cognitive
radio
network
consists
of
one
energy
detector
and
the
primary
system consists of one transmitter/ receiver pair.
Main IdeasNew
features
and
characteristics
of
energy
detection
is
derived
mainly
by
simulation.
We
provide
some
more
realistic
wireless
environment to evaluate the energy detection.
Sample ResultsWe
found
that
the
energy
detector
exhibits
best
performance
when
the
target
primary
signal
is
QPSK
and
degrades
for
16
and
64QAM.
However,
the
performance
deterioration
due
to
the
non‐constant
amplitude
signal
can
be
alleviated
by
increasing
the
number
of
samples
used
for
detection.
We
also
found
that
correlated
Rayleigh
fading
channel
significantly
degrades
the
performance of the energy detector.
Summary/ConclusionsThe
energy
detector
suffers
from
the
non‐constant
amplitude
problem
and
correlated channel problems.
Future Work:Performance comparison of spectrum
sensing techniquesValidate cooperative sensing model
using energy detectorsWork on using heterogeneous
sensors and compare with homogenous
curves ‐
performance/complexity etc.
Figure 1 Performance comparison of energy detector
for different modulation signals.
0.2 0.25 0.3 0.35 0.4 0.45 0.50.75
0.8
0.85
0.9
0.95
Prob. False Alarm
Prob
. Det
ectio
n
SNR = -2dB
Modulation type: QPSK16QAM64QAM
0.2 0.25 0.3 0.35 0.4 0.45 0.50.75
0.8
0.85
0.9
0.95
Prob. False Alarm
Prob
. Det
ectio
n
SNR = -2dB
Modulation type: QPSK16QAM64QAM
0 0.2 0.4 0.6 0.8 10
0.2
0.4
0.6
0.8
1
Prob. False Alarm
Prob
. Det
ectio
n
SNR -2dB
AWGM channelAWGN + Rayleigh(Independent)AWGN + Rayleigh(Correlated)AWGN + Lognormal Shadowing(6dB)AWGN + Lognormal Shadowing(12dB)
Figure 2 Performance comparison of energy
detector for different modulation type with
increased number of samples.
Figure 3 ROC curve under different channel condition
Spectrum Sensing for ODFM System by Exploiting Frequency‐ Domain Pilot Polarity
CCSR Research Symposium 2011 – Zhengwei
Lu, PhD Student
Abstract/ScopeThis
work
presents
a
novel
spectrum
sensing approach
for
OFDM
system
by
exploiting
frequency‐domain
pilot polarity in scope of signal processing.
IntroductionSpectrum sensing is a type of advanced
signal processing
technique
for
the
future wireless networks, e.g. cognitive radios or self‐organizing networks. Lots of
work
has
been
developed
since
1940s, where each scheme has its own character;
and
the
energy
detection
is
the most well‐known approach.
Motivations/ObjectivesTo
propose
a
new
spectrum
sensing
approach which
can
achieve
a
good
trade‐off between
reliability,
latency
and computational cost.
System Model/DefinitionsPilot‐embedded
OFDM
system
with
an
assumption that
the
receiver
knows
the
standard of the primary system.
Main IdeasThe polar difference between pilot
symbols can result in a diversity on the frequency domain by doing auto‐
correlation on the time domain.
Sample Results
The proposed approach can offer a fast convergence rate, while the
compared approaches need more information and computational
power to gain its performance.
Summary/ConclusionsNew approach by exploiting
frequency‐domain pilot polarity. Fast convergence rate and small
computational cost. No noise information required.
-20 -18 -16 -14 -12 -10 -8 -6 -4 -2 00
0.1
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0.4
0.5
0.6
0.7
0.8
0.9
1
SNR (dB)
Prob
abilit
y of
Det
ectio
n
PFA=10%
The Proposed Approach, 10 blocksThe Proposed Approach, 20 blocksThe Proposed Approach, 50 blocksTDSC-MRC Approch, 10 blocksTDSC-MRC Approch, 20 blocksTDSC-MRC Approch, 50 blocksTDSC-NP Approch, 10 blocksTDSC-NP Approch, 20 blocksTDSC-NP Approch, 50 blocks
Block diagram of the proposed detector
An example of spectrum sensing scenario
IoT‐Service Clustering by Geographic Location
CCSR Research Symposium 2011 – Stefan Meissner, PhD Student
Abstract/ScopeIn this work an approach is described
that reduces the search space containing IoT
services by clustering
services by location. It is assumed that IoT
users are mostly interested in
services related to the location they are in at the time of service request.
IntroductionAssuming an Internet of Things (IoT) in
which billions of sensors are deployed it becomes a challenge for lookup
systems to find IoT services that are
suitable to user’s requests. So far service lookup systems exist for small
domains of the IoT only, but not for
inter‐domain searches in a global scale. Motivations/ObjectivesIn a fully deployed IoT
the search space
for query engines will be very large leading to unacceptable response times
for user queries.
System Model/Definitions•users are interested in services related to
the location they are in•services are deployed mostly in areas with
dense populationMain Ideasreducing the service lookup search space: • the space is divided into clusters• only the relevant clusters are scanned
during lookup• to find a suitable clustering criterion
ResultsClustering over average urban
areas leads to a number of 26,240 clusters
all over the
world. Given 1 billion services available such a fragment of
the search space contains only 38110 services
to be scanned.
Summary/ConclusionsIt has been demonstrated thatlookup of IoT
services is
more efficient by clustering the search space
clustering over geographic location is a suitable criterion
further clustering can be achieved by using observed phenomena as clustering
criterion (temperature, etc.)
Biggest urban areas on every continent
Urban area Population Area in km2
Tokyo‐ Yokohama
36.7 million 9,065
New York City 20.7 million 11,264
Cairo 17.6 million 1,709Moscow 13.7 million 4,533Sydney 3.8 million 1,788Average 18.5 million 5,676
global area: 148.94 million km2
Secure Network Entry Process for WIMAX Mesh
CCSR Research Symposium 2011 – Shahab Mirzadeh, Research Fellow
IntroductionIn order to join the WiMAX mesh network, a
Candidate Node (CN) has to perform the
network entry process. In network entry
process, the CN chooses one of the active or
operational nodes as Sponsor Node (SN), get
synchronized with network, negotiates its
capabilities, authorizes itself and registers
itself as member of network. Unfortunately
in the current standard, this important stage
is not well secured and the adversary can
impersonate valid sponsor nodes, lunch
different attacks such as topological and
Denial of Service (DoS) attack, result in
weaker security links, and disturb registration
process.
Source of the problem • Lack of mutual authenticationCN → SN: Operator Authentication Value SN → CN: ‐CN → AN: X.509 Certificate AN → CN:‐CN → NN: Operator Shared Secret (OSS)
Threats & Attacks
MSH‐NCFG messages are neither encrypted nor
authenticated → network topology attacks
Malicious sponsor node can change PKM‐REQ
messages → Security Level Rollback Attack
Possibility of intercepting OSS key →
Adversary
can using network resources
Modifying OSS key in Auth‐RSP message
→
Denial of Service (DoS) attack
REG‐REQ message is authenticated by a derived
key from AK →Malicious sponsor node can
modify the REG‐REQ messages or even drop them
Assumptions Every node has a X.509 certificate
Every node has also operator’s
authorization server’s public key
Mesh certificates are short term → no
need for certificate revocation list (CRL)
Proposed Solution
SNs
sign their NetEntryOpen
messages with their public keys certified
by mesh certificates
CNs
authenticate themselves to the
SNs
as defined in standard
CN and AS sign the authorization
request and the authorization reply
AS issues mesh certificates on CNs’
public keys and send them in the
authorization reply messages
OSS keys are encrypted by CN’s
public
key in the authorization reply messages
CN and RS sign the registration
request and registration reply
Mesh certificates are also used in
authenticating neighboring nodes and
establishing pairwise keys.
Modified network entry process
Alamouti STTD For Energy Efficient Femtocells
CCSR Research Symposium 2011 – Dave Muirhead, PhD Student
Abstract/ScopeThis
work
forms
part
of
ongoing
research
into the
use
of
multiple
antenna
techniques, applied
to
femtocell
base
stations, Fig
1.,
to
improve the
energy
efficiency of the femtocell’s transmissions.
Introduction Deployment of femtocells
expected to
reach 49 million by 2014. Essential that ‘green’
measures are taken
to control the potentially huge carbon footprint of such networks.
Important for operators (OPEX) and
consumers.
Motivations/Objectives Determine applicability of Alamouti
STTD
for femtocell systems.
4G systems will rely on multiple antennas
so form part of future embodiments. Low complexity and cost are important.
System Model/Definitions
Main Ideas Simulate and compare energy used by
STTD in femtocell channel models, Fig 3.,
compared to SISO scheme. Apply deployment usage pattern
(residential, enterprise, public) to determine suitability of approach.
Sample Results: STTD scheme required transmit
power, to maintain a QOS, is reduced by around 4dB compared
to a SISO scheme. Obvious benefits of additional
transmitter are shown for enterprise and public deployments
in particular.
Summary/Conclusions:The
use
of
simple
STTD
offers
some
scope to
reduce
power
in
a
femtocell. The suitability
of
such
a
scheme is likely to be determined by deployment
type. The
solution
offers:Power reduction/efficiencyLow complexity solutionZero Touch, low overhead
STTD Encoder(Femto BS)
STTD Decode
(UE)B
As0 s1
*0
*1 ss
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-4
10-3
10-2
10-1
12.2KBits/s Single Antenna vs STTD Indoor A
SNR before despreading (dB)
BE
R
Fig 1 Fig 2
Fig 3 Fig 4
Towards Reliable Routing for 6LoWPAN Wireless Sensor Networks
CCSR Research Symposium 2011 – Dr Michele Nati, Research Fellow
Abstract/Scope•Wireless Sensor Networks (WSN) are
becoming active part of the Internet world
•Implementation of IPv6 stack in resources constrained mote is not easy
•A routing protocol able to cope with the dynamicity of such networks is
missingIntroduction•Few IPv6 stack (6LoWPAN) for WSN
are now available:• UDP, IMCPv6, Neighbors
Discovery
• Routing protocols should be:- Very lightweight
- Resilient to lossy
environment
- Self‐adapting to topology
dynamicityMotivations/ObjectivesA standardized 6LoWPAN stack for
WSN will facilitate the deployment of new applications for smart services
System Model/DefinitionsCross‐layer approach (energy‐efficient MAC
and geo‐forwarding routing)Position information required (localization
errors resilient)Nodes follow asynchronous awake/asleep
scheduleMain IdeasNext‐hop relay selected at TX time (RTS/CTS
and priority index)Relay searched in F region then in FCSequence of colours for a path to the Sink
Greedy
forwarding
fails due to the
lossy
environment
(node 2)
ROME
increases
packet delivery
ratio with no
performance
degradation
Node Failure Node Addition
Sample Results
Summary/ConclusionsROME features:Routing for static and mobile
WSNsEfficiently copes with lossy
link
and network dynamicsSmall code foot print for easy
integration in 6LoWPAN stackPoint‐to‐point routing support
The CCSR Future Internet Experimental Facilities
CCSR Research Symposium 2011 – Dr Adetola Oredope ‐
Research Fellow
Abstract/ScopeThe CCSR, European Union and the
research community as a whole are actively
involved in various researches around the
Future Internet theme. However there is
there is a demand within CCSR to converge
all FI related outputs via a unified
demonstration platform. The paper
provides a high level overview on the
requirements and approach aimed at
building the CCSR FI platform
IntroductionAs experimentally driven research plays a
key role in the development of Future
Internet (FI) technologies, the CCSR Future
Internet Platform aims to consolidate all
existing and future testbeds within CCSR
into a single dynamically reconfigurable
platform that can support the R&D of
future Internet technologies
Motivations/ObjectivesOne of the key aims of the FI platform
is modularity, as this will allow for the
easier integration of new and future
technologies with existing
technologies. Also, it is important to
have a structured way for both
external and internal users for using
the platform. Figure 1 shows a
proposed approach on how the key
blocks can be connected in a modular
way.
Summary/ConclusionsThe Future Internet platform will
provide new opportunities for CCSR
and the University as whole as it will be
the first research driven future
Internet platform that allows for third
party researchers, developers, and
companies to carry out experiments
and trials using real environments
within a diverse community such as
the University Campus.
A High Level Overview of the FI Platform
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0.5
0.6
0.7
0.8
0.9
1
Downlink SINR (dB)
CD
F
Lw= 0 dB Lw= 5 dBLw=10 dB
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0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Downlink SINR (dB)
CD
F
Scenario 3aScenario 3bReference Scenario B
A semi‐analytical study of inter‐cell interference in femtocell networks
CCSR Research Symposium 2011 – E. Pateromichelakis, PhD Student
Abstract/ScopeScope: Quantification of the impact of co‐tier interference in Femtocells
through a semi‐analytical approach.
Rationale: Radio Access parameters (Path loss model, Shadowing, Wall
penetration Loss, Location of Femtocells and User Distribution)
Key
elements that can potentially affect the femtocell‐to‐femtocell
interference in a multi‐femtocell deployment.
Introduction Inter‐cell Interference denotes a major challenge in Femtocell
Networks
Motivations/Objectives A semi‐analytical model has been introduced in literature to study the
effect of interference for Femtocells Concluded that Co‐Tier
Interference is viable in case of wall separating Femtocells:
•
High natural isolation between the Femtocells, Low nominal
transmission powers. • Symmetric Assumptions on the relative locations of Femtocells
Our objective is to revisit the problem of Co‐tier Interference in
Femtocells with more detailed analysis and evaluation studies of
all the
radio access parameters that can affect co‐tier interference.
Our purpose is to quantify the co‐tier interference to evaluate the
requirements of interference mitigation algorithms for Femtocells.
System Model A semi‐analytical approach has been introduced to approximate the CDF of
the SINR in presence of lognormal shadowing. The severity of interference is
measured by the outage probability which can be extracted from the CDF of SINR
considering a certain minimum threshold.
Main IdeasWe further examine the effect of radio access parameters on the performance in
a cluster of Femtocells. • Effect of Path Loss Model• Effect of Wall Penetration Loss• Effect of Lognormal Shadowing• Location of Femtocells and User Distribution
Sample ResultsWall Penetration Losses:
In Reference Scenario B (Figure 4) outage probability in
case there are no separating walls is 44.7%. This probability
drops to 15.9% 5 dB and 4.2%
10 dB wall separation.
Location‐Based Worst Cases:
For different snapshots of UE and serving HeNB locations
in worst case interference, the outage probability is
unacceptably high (64%‐100%).
Location‐Independent Worst Cases:
The results (Figure 5) show that the outage probability is
quite high in case that serving HeNB is at the cell‐edge
(90%) while it decreases when the serving HeNB is located
at the centre (67%). Reference scenario B shows the least outage (15.9 %)
which is consistent with the previous observations in the
literature.
Summary/Conclusions In symmetric deployments of Femtocells, the effect of
co‐tier interference can be viable due to the natural
isolation factor of wall penetration loss
By considering random deployment of Femtocells and
some worst case scenarios, the impact of co‐tier
interference can be drastically amplified.
This study highlights the importance of an interference
mitigation mechanism to be adapted for arbitrary
deployment of Femtocells.
Figure 2 Location‐based Worst Cases
Figure 3 Location‐independentWorst Cases
BS
Service
Gateway
Local Entity
HeNB
Internet
Femtocell Network
Co‐tier
Cross‐tier
Interferer HeNB
Femto UEServing HeNB
Minimum distance
Figure 1 Reference Scenarios A, B
Figure 4 Effect of Wall penetration Losses
Figure 5 Location Independent Worst Cases
Energy‐Aware Adaptive Sectorization in LTE Systems
CCSR Research Symposium 2011 – Yinan Qi, Research Fellow
Abstract/ScopeA novel energy‐aware adaptive
sectorization strategy is proposed for
an event‐based traffic model in LTE systems. The target QoS
constraints
including coverage and blocking probability are also taken into
consideration.IntroductionNetwork management is an efficient
way to save energy in system level. Two shortcomings for SOTA network
management strategies:
•Quality of Service (QoS) constraints are missing.
•Transmission power of eNodeBs
is assumed
to be adjustable in a large dynamic range. Motivations/ObjectivesIn our strategy, instead of switching off
the entire eNodeB, we turn off certain sectors and widen the opening angle of the remaining ones to maintain the
QoS level.
System Model/Definitions•19 eNodeBs, 57 sectors. •Event‐based MMPP/M/1/D‐PS queuing model.•Power amplifier, main supply, DC part, RF
link, BB processing and cooling. Main IdeasAdaptive sectorization
+ QoS
constraints.
• High traffic: all sectors on•
Low traffic: one sector off, opening angle of the
other two sectors is increased to maintain the
QoS
level.
Sample ResultsBlocking probability (BP) &
Coverage: one sector off →the coverage area of the other two sectors increases →BP
increases, coverage loss. Adaptively widened opening
angle: coverage is maintained at the same level.
Selection of switching off point: target BP is guaranteed +
maximized energy saving. Summary/ConclusionsAdaptive sectorization
is
proposed to improve the energy efficiency of a LTE system with
certain QoS constraints. Future
directions include:Single type traffic →multi‐
type trafficHandover energy
Traffic Demand Blocking Probability
Coverage Energy Efficiency
μsav
= Energy consumption of benchmark LTE system/ Energy consumption of adaptive
sectorisation
system
Sample Result
The proposed opportunistic algorithm can
efficiently coordinate the interference on
macro cell.
Macro users maintain close performance
to the benchmark plain case
The femto
users achieve reasonable
throughput without consuming any
additional resources.
ConclusionsThe proposed method can alleviate the
effect of femto
interference on the macro
performance and can be adaptively tuned
based on the service requirements.
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.1
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0.3
0.4
0.5
0.6
0.7
0.8
0.9
1CDF
Normalized User T-put
Macro / OpportunisticFemto / OpportunisticMacro / No CoordinationFemto / No CoordinationPlain Macro
Opportunistic Spectrum Reuse for Femtocell Networks
CCSR Research Symposium 2011 – Dr Mehrdad Shariat, Research Fellow
AbstractIn this work a novel approach is proposed
for resource allocation for femtocells
that
opportunistically identifies low‐cost
resources (in terms of interference) in a
way that would cause minimal impact on
the service level of primary macro users.
Introduction
Femtocells
are envisioned to address the
classical problem of indoor coverage.
This Requires a massive deployment of
femtocells.
The classical network planning approaches
would be less efficient at such scales
Objective
To adopt a proper radio resource allocation
scheme in presence of femtocells
in order to
avoid the undesirable impact on macro cells.
This enables the operation of femtocells
in
the licensed band and in an unplanned manner.
Main Idea• To
exploit
the
isolation
factor
from
a
transmitting
node
to
the
users
served
by
another
node
to
do
concurrent transmission.
• This method
effectively
provides
some
low‐cost
resources (in terms of interference) in frequency to be
scheduled by secondary node to its own users.
• The isolation
factor
is
highly
dependent
to
the
channel
quality
gap
of
a
transmitting
node
to
its
own
users
compared
to
the
links
to
users
served
by
other
transmitting nodes.
The Concept of opportunistic reuse
Macro-UE1
Femto-UE2
eNB HeNBF1
Capability to reuse F1
1UEHeNBh
Opportunistic reuse in a multinode‐multiuser
environment based on the isolation factor among
different pairs of transmitting node‐user
An Energy‐efficient Clustering Solution for Wireless Sensor Networks
CCSR Research Symposium 2011 – Dr Serdar Vural, Research Fellow
AbstractThe
EC
clustering
algorithm
for
Wireless
Sensor Networks: 1.Equalizes
node energy levels ,
2.Reduces
energy
consumption
in
multihop data collection.
Problem StatementNodes
in
network
hot‐spots
deplete
energy
resources
quickly
under
heavy
traffic load:1.Cluster
Head
(CH)
nodes
have
higher
processing and traffic relay load. 2.As
the
hop
distance
to
the
sink
decreases,
nodes
have
higher
traffic
relay load.
MotivationExisting works are insufficient due to:•Single
hop
transmissions
need
high
transmission power.•Finding
suitable
transmission
ranges
is
NP‐Hard!•Improper
selection
of
cluster
sizes
cause high message overhead.
Energy EqualizationRegions based on hop distances to the sink
• HEED
cannot
equalize
node energy
levelsW : Network widthX : Network lengthσ
: Network density
RR
R
X
W
R
R1 R 2 3
4
5
6Sink
a
Stable Operation
Period (SOP) :The length of time
until the first node
in the network runs
out of battery
energy.
Extension of network lifetime
EC has the highest SOP
• UCR
suffers
from control
message
overhead
• EC
provides
energy
equalization &
conservation
For a given network
width: Higher node density
Higher SOP
EC is the most
scalable solution
for a given hop
distance.
EC provides
the highest
SOP even for
high node
density
Host Identity Protocol based Mobility Management Scheme for 3GPP Evolved Packet System
CCSR Research Symposium 2011 – Meng Wang, PhD Student
Abstracta
Host
Identity
Protocol
(HIP)
based
mobility management
scheme
and
a
context
caching
based
handover optimization is
proposed
for
the
3GPP
Evolved Packet System (EPS) to improve its handover performance.
IntroductionThe
3GPP
EPS
adapts
Proxy
Mobile
IPv6
(PMIPv6) and
GPRS
Tunnelling
Protocol
(GTP) based
mobility
management
schemes to
support
the
seamless
mobility in
the
core
network.
But
the
hierarchical management of PMIPv6 and GTP
is
not
the
best
solution
for
the
flat
IP architecture of EPS.
MotivationsHIP
integrates
mobility,
security,
multi‐
homing and
multi‐access,
and
also
supports peer‐to‐peer
networking.
How
HIP could be integrated to EPS and how is the performance?
Main Ideas• HIP
based
distributed
mobility
management architecture
based
on
the S1‐flex interface of the EPS. • eNB
to
Serving
GW
routing
update
for HIP micro‐mobility management.• Mobility
context
cache
on
eNB
from MME, to enable eNB to be able
to directly send the control signalling to Serving GW for user plane update.
Sample ResultsThe proposed scheme can reduce the
total signalling
for
more
than
22.6%,
reduce the
handover
latency
for
more than 27.9% comparing with the original 3GPP design.
ConclusionsThe proposed scheme improves both
signalling load
and
handover
latency
for 3GPP
EPS,
which
implies
the
improvement
of
the
network scalability , handover performance.
0.00E+00
5.00E+01
1.00E+02
1.50E+02
2.00E+02
2.50E+02
3.00E+02
3.50E+02
4.00E+02
4.50E+02
5.00E+02
0 70 140 210 280 350 420
UE Speed (km/h)
Sign
allin
g Lo
ad (b
ps)
GTP+GTP
GTP+PMIP
enhanced HIP
Optimised enhanced HIP
0
50
100
150
200
250
300
GTP+GTP GTP+PMIP enhanced HIP
Optimised GTP+GTP
Optimised GTP+PMIP
Optimised enhanced
HIP
Average Total Handover Signalling Delay (ms)
Average Handover Preparation Time
Average Handover Execution Time
Average Handover Completion Time
Average Post‐Handover Procedure Time
Fig. 1 HIP based Distributed Mobility Management Architecture
Fig. 2 Break Down of Average Handover Signalling Delay
Fig. 3 Total Network Signalling Load
0.00E+00
1.00E+01
2.00E+01
3.00E+01
4.00E+01
5.00E+01
6.00E+01
7.00E+01
8.00E+01
0 70 140 210 280 350 420
UE Speed (km/h)
Sign
allin
g Lo
ad (b
ps)
GTP+GTP
GTP+PMIP
enhanced HIP
Optimised enhanced HIP
Fig. 4 Average Signalling Load per MME
0.00E+00
2.00E+00
4.00E+00
6.00E+00
8.00E+00
1.00E+01
1.20E+01
1.40E+01
1.60E+01
1.80E+01
0 70 140 210 280 350 420
UE Speed (km/h)
Sign
allin
g Lo
ad (b
ps)
GTP+GTP
GTP+PMIP
enhanced HIP
Optimised enhanced HIP
Fig. 5 Average Signalling Load per Serving GW Fig. 6 Average Signalling Load per PDN GW
0.00E+00
5.00E+00
1.00E+01
1.50E+01
2.00E+01
2.50E+01
3.00E+01
3.50E+01
4.00E+01
0 70 140 210 280 350 420
UE Speed (km/h)
Sign
allin
g Lo
ad (b
ps)
GTP+GTP
GTP+PMIP
enhanced HIP
Optimised enhanced HIP
Improving an approach to DTN
CCSR Research Symposium 2011 – Dr Lloyd Wood, Research Fellow
ScopeDelay‐Tolerant Networking (DTN)
encompasses a wide range of disrupted and disconnected networks
with varied conditions. The Bundle Protocol is one approach to DTN.
IntroductionThe Bundle Protocol was tested in
space on the UK‐DMC satellite for the first ‘Interplanetary Internet’
tests. A
number of problems were discovered in this protocol design, particularly
with its lack of error detection and reliability, and with its dependence on
synchronised clocks for delivery.
MotivationsImproving communication for mobility
is an active research area. Better approaches to routing, addressing and
connectivity are still needed.
System ModelThe Bundle Protocol’s architecture relies
on a complex security model, which gives reliability only as a side‐effect. Bundle
Protocol deployments do not implement this security model, and so lack reliability.
Main ProblemThe Bundle Protocol ignores the well‐
known ‘end‐to‐end principle’ that dictates
how reliability must be implemented.
ResultsWe have now proposed a
workaround to address the lack of reliability in the Bundle
Protocol. This workaround uses the existing security architecture,
requiring security mechanisms to support basic protocol reliability.
SummaryWe have identified shortcomings
in the Bundle Protocol that will prevent its widespread adoption
in DTNs. We are exploring other, different, approaches to DTN
networking which do not have the drawbacks of the Bundle
Protocol. Generic one‐size‐fits‐ all‐solutions are unlikely to be the best for a particular scenario,
while custom engineering suited to that scenario can improve
overall performance.
A wide range of different DTN scenarios
prop
agat
ion
dela
y/t
link stability or uptime/tlow
(< m
s)hi
gh (>
day
s)
link up for very long periods;any down periods are scheduled
Fixed conditions, long delay
favour strong FEC
increasingdelay tolerance
needed
scheduleddeep space
Varying conditions,short delay leads to
ARQ + FEC
increasingdisruption tolerance
needed
unscheduledad-hoc
link intermittently up/down;not known in advance
Internetcore InternetBGP routers, cloud services
SaVi satellite constellation visualization
CCSR Research Symposium 2011 – Dr Lloyd Wood, Research Fellow
ScopeSaVi
is an open source, cross‐platform,
software package for visualizing and explaining orbital geometry. SaVi
simulates and animates satellite motion, and shows the coordinated
movement and coverage that results from multiple satellites orbiting to form
a particular satellite constellation.
IntroductionAfter development was begun at the
Geometry Center at the University of
Minnesota, SaVi is now maintained and
enhanced at the University of Surrey for the international community.
ObjectivesTo provide useful simulations of
satellites and constellations for research and teaching purposes.
System ModelSaVi
relies on the J2 orbital model, which
is useful for simulating and explaining basic satellite motion. More detailed
perturbation is simulated by other tools.
Main Ideas Show and animate satellite movementand coverage in various constellations. Use these to explain, teach and research satellite constellations and orbits.
ResultsSimulation output from SaVi
has
now appeared in over twenty conference and journal papers,
and has also been used by companies planning commercial
communication systems using satellite constellations.
SummarySaVi
provides a useful tool for
satellite constellation and orbit simulation, for both research and
teaching purposes. Being freely available, with an open codebase
that can be easily customised, eases maintenance and
portability, and makes SaVi attractive to its users and to
educators and researchers.
SaVi is available from:
http://savi.sf.net/
user interface showing Globalstar
Distributed Resource Reservation for Real Time Sessionsin Wireless Mesh Networks
CCSR Research Symposium 2011 – Xiaobo Yu, PhD Student
Abstract/ScopeWe propose an distributed MAC
protocol with reservation scheme. By using Super‐frame (SF) based
scheduling and concurrent transmission mechanism, Quality of
service (QoS) guarantee for real‐time sessions (RTSNs) can be achieved.
Introduction• Guaranteeing QoS
for RTSN in IEEE
802.11‐based distributed networks is challenging.
•Existing schemes based on prioritization can not provide QoS
assurances for RTSNs.•Bandwidth efficiency is suffered
among existing schemes.Motivations/ObjectivesTo guarantee QoS
for RTSNs
in a
distributed manner while pledging the fairness toward other types of sessions.
System Model/DefinitionsThe protocol uses a service interval which can
divide the channel airtime into contention‐ free period and contention access period.
Main Ideas• Signalling process with interference probing• Concurrent transmission within contention‐
free period (CFP)• Logical cluster (LC) establishment for
alleviating signalling overhead
Sample Results
Summary/Conclusions Guaranteed QoS
can be
provided for RTSNs. Fairness towards other
sessions is implemented. Bandwidth efficiency can be
improved by concurrent transmission mechanism.
CT groupCT group CT membersCT members TXOPTXOP
11 <1, 4, 7><1, 4, 7> T11T11
22 <2, 5, 8><2, 5, 8> T12T12
33 <3, 6, 9><3, 6, 9> T13T13
An Agent‐based Scheme for Supporting Service in Wireless Cloud
CCSR Research Symposium 2011 Yanbo Zhou, PhD Student
AbstractWireless
Cloud
has
emerges
as
a
new
paradigm
and
extension
of
cloud
computing.
It
intends
to
make
the
advantages
of
cloud
computing
available for wireless users and provides more possibilities for
accessing
cloud
services
conveniently.
However,
Wireless
Cloud
concept
relies
on
on‐demand
connectivity
and
will
need
to
provide
a
scalable
and
high‐
quality
mobile
access.
In
this
work,
we
propose
a
novel
agent‐based
scheme
to
meet
these
requirements
and
support
cloud
service
(e.g.
multimedia)
in
wireless
cloud
system.
This
scheme
is
based
on
service
availability
and
the
use
of
agent
server,
which
enable
the
adaptive
and
concurrent
use
of
different
wireless
access
network
interfaces
during
the
communication.
A
wireless
cloud
environment
is
treated
as
the
infrastructure
to
supporting
the
cloud
service,
in
accordance
with
the
user requirements and preferences within wireless cloud environment.
IntroductionWireless Cloud is emerging as one of the most important paradigm in cloud computing.
It
combines
wireless
communication
and
cloud
computing
technologies
to
enable
wireless users to access the cloud services on a wireless cloud platform from anywhere
in the world. Figure 1 shows the overview of a wireless cloud system and to realize the
mentioned
visions.
In
this
work,
we
describe
a
novel
agent‐based
scheme
to
meet
application
requirements
and
enable
a
wireless
terminal
(WT)
to
adaptive
select
dynamic
wireless
access
network
(AN).
Basically,
the
agent‐based
server
(ABS)
agent
offers
on‐demand
cloud
services
availability
and
exploits
all
the
wireless
access
network
resources
available
to
the
user.
An
ABS
is
need
for
each
corresponding
wireless
user
agent
(WUA),
even
if
a
given
ABS
may
serve
more
than
one
WUA
simultaneously. The agent software resides on the wireless user terminal contains the
AN selection strategy, which is based on a combination
of
measured
parameters
such
as
signal
strength,
transmission
rate,
channel
load
and
service
requirement
of
user
demand. This scheme aims to guarantee continuity of the communication between WT
and wireless cloud service provider. It has been implemented as part of wireless cloud
service infrastructure which offers the possibility of communication flow generated by
some distributed application service provider.
ObjectivesThe objective of this work is as following:
To allow wireless users to access cloud services with mobility support and considered
service availability.
To efficient support and exploit wireless communication to offer seamless
service
to
wireless users.
To
ensure
the
quality
of
service
of
user’s
application
and
efficiency
resources
utilization
System ModelFigure
2
shows
the
interactivity
of
entities
in
an
agent‐based
scheme
for
supporting
cloud service to wireless platform users. In the scheme includes different entities: user
WT is equipped with a wireless user agent (WUA), agent‐based server (ABS) acts
as
a
gateway
entity
and
that
enable
to
discover
the
demand
service
from
the
application
server providers, application server providers offers such as data, storage, multimedia
and/or
other
cloud
resources.
ABS
provides
information
to
WUA
regarding
to
all
application
services
available
to
that
user.
WUA
selects
and
allocates
optimal
resources to supporting and maintaining the user’
application.
Entities in the schemeThe following functions of entities in the scheme can explains: WUA
simply
issues
one
single
service
request
message
by
connect
to
reachable
the
ABS
through
AN
via
wireless
links.
It
supports
optimized
resource
selection
and
monitors
the
service QoS
covering the entire lifecycle of the service provision.ABS deals with the problems: such as how to discover application
service meet the demand of
users
and
efficiency
utilize
and
manage
cloud
resources
(data,
storage,
network,
etc),
and
update the information of selected and allocated resources fairly among users, and finally, acts
as gateway of the delivery of cloud service at Internet scale. Application Server Provider consists of an ABS in each edge components and some non‐agent
application
server
components
like
application
server
or
storage
server.
It
offers
application
content to be accessed and WT user across the internet.
SummaryThis
work
presents
the
agent–based
scheme
that
is
a
solution
for
one
of
the
most
critical
challenges
of
wireless
cloud computing. It provides supporting and maintaining the
service
for
wireless
user’s
application
in
wireless
platforms
with respect to efficiency resource utilization.
Since
the
on‐demand
availability
and
scalability
of
the
wireless connectivity is a key requirement for wireless cloud
concepts, the ”quality”
of service is crucial for the purpose of
agent‐based
scheme,
especially
with
regard
to
delay,
accuracy, relevance, and confidence.
It
still
remains
largely
open
how
this
scheme
can
be
integrated
in
to
specified
hybrid
wireless
network
and
support
service‐oriented
application
based
on
user’s
application requirement .
Future
works
are
planned
to
prove
the
efficiency
of
energy‐awareness
resource
selection
and
management
algorithm under mainstream wireless cloud environment.
Figure 1: Overview of wireless cloud system
Figure 2: Agent‐based scheme design