MH-DEEC: Towards Efficient Energy Utilization in Wireless...
Transcript of MH-DEEC: Towards Efficient Energy Utilization in Wireless...
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MH-DEEC: Towards Efficient Energy
Utilization in
Wireless Sensor Networks (Thesis Final Presentation)
By
Muhammad Yousaf Khan
FA11-REE-030
Supervised by
Dr. Nadeem Javaid
Dr. Mahmood Ashraf Khan
Centre for Advanced Studies in Telecommunications
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Publication
M. Y. Khan, N. Javaid, M. A. Khan, ”Hybrid DEEC: Towards Efficient
Energy Utilization in Wireless Sensor Networks”, Published in World
Applied Science Journal (ISI Indexed), Volume:22, Issue:1, Page no. 126-
132, 2013.
Centre for Advanced Studies in Telecommunication (CAST), CIIT, Islamabad 2
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Outline
Summary
Related Work/ Past Work
Motivation
Radio Model
Proposed Schemes
Simulation Results
Applications
Conclusion
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Summary
Wireless sensors are limited energy devices
Reduce the energy consumption
Lifetime and scalability need to be increased
Energy efficient protocol should be designed
Proposed Schemes (H-DEEC and MH-DEEC) aims at fulfilling all these
requirement
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Related Work/ History
Deployment Scenarios (Planned, Random, Fixed and Dynamic)
Position of BS
Communication Standards for WSNs (Bluetooth, WiFi, ZigBee and
DASH7)
Heterogeneous Routing Schemes (SEP and DEEC)
Clustering Schemes(LEACH, SEP and DEEC)
Multi Hoping/Chain Forming Approaches (PEGASIS, EEPB, IEEPB)
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Related Work/ History…
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Deployment Scenario
Planned Deployment
Random Deployment
Fixed Deployment
Dynamic or Mobile
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Related Work/ History…
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Communication Standards
ZigBee (IEEE 802.15.4, Low Powered, @ 2.4GHz , 250KB/s)
Wi-Fi (IEEE 802.11, High Powered, @ 2.5GHz , 54MB/s)
DASH7 (ISO 18000-7, Low Powered, @ 433MHz , 200KB/s)
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Journey of WSNs in Routing Layer
Classical Routing Schemes
Direct Transmission (DT)
Minimum Transmission Energy (MTE)
Clustering Schemes
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(i) Random Deployment (ii) MTE (iii) DT
Centre for Advanced Studies in Telecommunication (CAST), CIIT, Islamabad
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Journey of WSNs in Routing Layer…
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Clustering Schemes
LEACH (Homogeneous, Periodical selection of Cluster Heads)
SEP (2-level Heterogeneity, Periodical Selection of Cluster Heads)
DEEC (Multi-level Heterogeneity, Energy aware clustering)
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Journey of WSNs in Routing Layer…
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LEACH (Homogeneous, Periodical selection of Cluster Heads)
(i) At time t=0 (ii) At time t+α
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Journey of WSNs in Routing Layer…
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SEP (2-level Heterogeneity, Periodical Selection of Cluster Heads)
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Journey of WSNs in Routing Layer…
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DEEC (Multi-level Heterogeneity, Energy aware clustering)
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Journey of WSNs in Routing Layer…
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Chain Based Routing Schemes
PEGASIS (Greedy Approach Based Algorithm)
EEPB (Distance and Energy Based Leader Selection)
IEEPB (Weighting Factor Introduced, Multi Edged,
Avoiding Long Links)
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Journey of WSNs in Routing Layer…
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EEPB (Distance and Energy Based Leader Selection)
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Related Work/ History…
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IEEPB (Weighting Factor Based Leader Selection)
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Motivation
• Similar Approaches for different application doesn’t work
• A technique has to be proposed which can perform better in
real time scenario as well.
• Drawbacks of certain classical approaches like
– LEACH (Clustering scenario, un-balance energy utilization)
– SEP (Limited energy levels)
– DEEC (Direct communication of Clusterheads)
– All above technique are not applicable if shape of networks changes.
– PEGASIS (Data Packet has to transverse from too many Hops )
– EEPB (Long Link Problem)
– Base Station Position dependent Scenarios.
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Radio Model
Energy consumed by a sensor is directly
proportional to
Transmission distance (d)
Packet size (L)
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Radio Model
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Energy dissipated by Transmitter and Receiver circuitry
Energy for Tx amplifier to achieve an acceptable Eb/N0
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Proposed Schemes
(Hybrid DEEC) H-DEEC
(Multi-edged chained Hybrid DEEC) MH-
DEEC
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H-DEEC
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H-DEEC
• Random Deployment
• Heterogeneous Network ([E0, E0(1+amax)])
• Network is divided into two parts
– Normal Nodes
– Beta Nodes
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Hybrid = Clustering + Chain forming
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H-DEEC
• Our proposed scheme divided into different
phases
– Initializing the Network
• Distance from BS will be broadcasted by BS.
– Chain forming
– Clustering
– Data Transmission Phases
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H-DEEC (Clustering) • For Balancing the energy consumption DEEC is used for clustering.
• Cluster Heads will be elected on the base of residual energy (Nodes with higher energy will be more probable to elect as a Cluster Head of respective cluster)
𝑝𝑖 =𝑝𝑜𝑝𝑡𝑁(1 + 𝑎)𝐸𝑖(𝑟)
(𝑁 + 𝑎𝑖𝑁𝑖=1 )𝐸 (𝑟)
where
– pi is the probability of a node to be clusterhead
– popt is the optimum probability of selection of cluster heads
– Ei(r) is residual energy of the node.
– N is the total number of nodes
– r is the current round
– ai is the additional energy factor
– G is the set of nodes eligible for becoming a Cluster Head
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H-DEEC(Chain Forming)
• Beta Nodes will do multi-hopping and the sequence
of Hops is elected on the basis of Greedy approach
(PEGASIS).
• Leader is selected on the basis of distance of beta
node to the base stations.
• Long Link Problem
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MH-DEEC
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MH-DEEC(Chain Forming)
• Chain forming Scenario is modified
• Nodes position will be broadcasted by the BS when
network will be initiated.
• Leader is selected on the base of weight of every beta
node
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MH-DEEC(Chain Forming)
Leader Selection Phase
– 𝐸𝑝 =𝐸𝑖𝑛𝑖𝑡_𝑏
𝐸𝑖_𝑏(𝑟)
where Einit_b is the initial energy of beta nodes and Ei_b(r) is the residual energy of beta node.
– 𝐷𝑡𝑜𝐵𝑆 = d4
toBSd4
avg
where dtoBS is the distance of beta node from BS and davg is the average distance of beta nodes from BS.
Weighting factor is calculated as :
– 𝑊𝑖 = 𝑤1𝐸𝑝 + 𝑤2𝐷𝑡𝑜𝐵𝑆 Where
– 𝑤1 + 𝑤2 = 1
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MH-DEEC(Clustering)
Same as done in DEEC
On the basis of initial and residual energy
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Simulation Results
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Simulation Parameter
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Parameter Value
Network size 100m × 100m
Number of nodes 100
BS position (30m,150m)
Packet size 4000 bits
Popt 0.1
E0 0.5 J
Eelec 5 nJ/bit
Distance threshold (d0) 70m
ϵamp 10pJ/bit/m2
ϵfs 0.0013pJ/bit/m4
Simulation Tool Matlab
Communication Standard ZigBee (assumption)
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Stability Graph
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0 500 1000 1500 2000 2500 3000 3500 40000
10
20
30
40
50
60
70
80
90
100
Number of Rounds
Nu
mb
er o
f A
liv
e n
od
es
MH-DEEC
H-DEEC
DEEC
SEP
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Stability Graph
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• Stability time is greater than all other classical
approaches which will avoid coverage holes
• Shows the efficient and balanced utilization of
energy.
• Network lifetime is greater than DEEC and
SEP
• Stability Graph Comparison
(approx.)
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Throughput Graph
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0 500 1000 1500 2000 2500 3000 3500 40000
0.5
1
1.5
2
2.5
3x 10
5
Number of Rounds
Num
ber
of
Pac
ket
s S
ent
to B
S
MH-DEEC
H-DEEC
DEEC
SEP
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Throughput Graph Comparison
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Energy Graph
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0 500 1000 1500 2000 2500 3000 3500 4000-10
0
10
20
30
40
50
60
70
80
Number of Rounds
Res
idual
Ener
gy o
f th
e N
etw
ork
MH-DEEC
H-DEEC
DEEC
SEP
(joule
s)
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Applications
Battle Fields Monitoring
Borders Monitoring
Crops Monitoring
Forest Fire Monitoring
Underground Networks for soil monitoring
Linear Networks
Underground Mine Monitoring
Linear Network Application
Body Area Network
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Future Work
Working on Practical Sensor Nodes
Application for the underground mine sensor
Network
Publication to be submitted in ICC 2014
Wizzi motes
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Conclusion
• Efficient energy utilization is a serious issue in
WSNs and H-DEEC and MH-DEEC are
energy efficient.
• Both protocol achieving greater stability time
and throughput.
• Balanced and Efficient energy utilization
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Tools
Matlab® For simulations
Latex For writing the manuscript and paper
Inkscape For figure formatting
Microsoft Visio For drawing the diagrams
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Questions???
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