Towards Resilient and Practical Geometric Routing for WSNs

Ph.D. Proposal

By Ke Liu

09/07/2007

Outline Background and

Motivation Wireless Sensor

Networks (WSN) Geographic Routing

Protocols Virtual Coordinates

System (VCS)

Contributions: Anomalies in VCS HGR: Hybrid

Geographic Routing AVCS: Aligned VCS Security Issues Other Contributions

Remaining Work Future Research

Wireless Sensor Networks (WSNs) Sensor nodes:

Small, cheap and resource constrained sensing, processing, storage and radio

Wireless Sensor Networks: Multiple sensors collaborate as a network Large-Scale, fine-grain sensing Many applications: military, industrial, civilian,

medical, scientific, etc.

WSNs properties Application driven Data-centric Limited Computing Capacity Limited Resources Communication Pattern: many-to-one Large Scale Real-time

Mica2 Mote

128KB Instruction EEPROM

4KB Data RAM

Atmega 128Lmicroprocessor7.3827MHz

ChipcornCC1000Radio TranscieverMax 38Kbps- Lossy transmission

FlashMemory

128KB – 512KB

UART

51 pin expansionconnector

UART, ADC

Typical Sensor Processor: MicaZ

Typical Sensor Transceiver: MicaZ

Typical Sensor: MicaZ

System Organization of WSNs

Routing is Important for WSNs Support the special communication pattern Large-scale and data-centric: traditional ID-

based (IP-based) protocol not a good fit Data-centric: care about collecting data, not

communication between ends Limited Resources Nodes often location aware

Location is needed context for the data

Traditional Wireless Routing Routing table is commonly used: requiring

relatively large storage ID-centric Routing (not data-centric): does not

support the many-to-one communication patterns Before data traffic, the path between ends has to

be set up The network Dynamics may affect the

performance of routing. For Example, Moving node may cause failure of

forwarding paths going through it

Routing Protocols for WSNs Flat Routing:

SPIN Directed Diffusion (actually, Shortest Path routing)

Hierarchical Routing LEACH (Cluster-based routing) Virtual Grid Architecture Routing

Geometric Routing GPSR GOAFR, GOAFR+

Geographic Routing (GPSR)

Proposed by Karp et al (MobiCom 2000), know as Greedy and Perimeter Stateless Routing (GPSR)

Similar protocol proposed by Frey et al know as Greedy and Face routing (GFG)

Stateless: no path information, no (traditional) routing table. Only locations of neighbors are used.

GR is independent of the traffic pattern and topology Highly distributed and resilient: Only need to track

neighbor information-- resilient to network Dynamics

GPSR Introduction 2 phases:

Greedy Forwarding (GF) Perimeter Routing (Face Routing in GFG)

When GF fails, used as a complementary algorithm

Based only on location Planar Graph Theory is used (discovered in

early 90’s) Note: It only works for 2-dimensional space

Greedy Forwarding X is source’s closest

neighbor to sink Source node (or any

forwarding node) selects its closest neighbor to sink as the next hop

Neighborhood Physical Location

Euclidean Distance

Void Problem X is a local minimum X does not have

neighbors closer to sink than itself

The best next hop of source to sink should be a, other than X

X is a void

Void avoidance: Perimeter Routing

Note: borrow from GFG paper

Why Planar Graph?

Why Planar Graph? (Cont’) 3 Faces Along the faces’

perimeter, determinable

How Many Faces? 7 Faces non-determinable face

Geographic Routing Limitations

Location Errors cause routing failures GPS is expensive for Sensors and does not work

indoors—use localization algorithms Localization algorithms inaccurate: 40% of range error

is common Location inaccuracy cause problems in both greedy and

complementary phases

Perimeter Routing is inefficient Paths can be orders of magnitude longer than best

available path

Greedy Forwarding vs Perimeter Routing

GF PR on GG planar

Physical Void Avoidance Physical Void is due to the lack of relay nodes on

the straight line between source and destination nodes

In the physical coordinates system (PCS), some part of the coordinate space is empty

If another coordinates system can set up a continuous space, the void can be avoided

Virtual Coordinates System (VCS) based only on nodes’ connectivity was proposed

Virtual Coordinates System (VCS)

Idea: overlay virtual coordinates on nodes Forward to neighbor closer to destination (per

some geometric measure of distance) Typically coordinates are hop counts from

selected reference nodes (beacons) Based on communication connectivity:

Naturally bridges physical voids Immune to localization errors

Physical Voids Avoided in VCS

Note: borrowed from LCR paper

Voids happen in VCS All related works, such as VCap, LCR, BVR,

include backtracking algorithm to deal with the failure of greedy forwarding on VCS

But why Void happens in VCS was NOT analyzed Perimeter Routing can not be used in VCS

Recall that Planar graph theory works only for 2D VCS is typically 3+ Dimensional

Intuition: some part of the VCS is missing

VCS Variants Most well-known VCS

Scoped FloodingManhattanN (>10, typically 80)

BVR (NSDI’05)

Universal RecordEuclidean4LCR (RTS 2004)

Random WalkEuclidean3Vcap (InfoCom 2005)

BacktrackingDistanceDimensionsVariant

PCS vs VCS: path stretch

PCS vs VCS (cont’)

PCS vs VCS: Anomalies Ratio

VCS Anomaly: Expanded VC Zone

VC Zone: The VC’s

of nodes are the same

VCS Anomaly: Disconnected VC Zone

VCS Anomaly: Forwarding Void It is possible

Dis(A, B) == Dis(A, C)

Packet arrives at A can not be forwarded to C, since B is as far as A to C

Even there is a path from A to C through B, forwarding would fail

VCS Forwarding Void (Cont’)

Why VCS Anomalies happen? In VCap, authors prove that if the network density is infinite, the VC Zone is

bounded What’s the difference between the proof and reality? – Density Quantization Error: Mapping loses the distance differences Quantization Error

Only number of hops is used for VC Nodes at different location receive the same VC Higher effects with higher density

Quantization Error can be bounded as below, where x = No. of Hops

Quantization Error Distance Map

Important Observations Physical Void and Virtual Void arise at different

places in network topology Side Observation: greedy forwarding is more efficient

than complementary routing (perimeter routing) Accordingly, I propose HGR

Quantization Error is the major reason of the Virtual Void Accordingly, I propose AVCS

Second Contribution -- HGR

Addressing Anomalies in Virtual Coordinates for Geometric Routing in WSNs, IEEE Upstate New York Workshop 2006

Virtual Coordinate Backtracking for Void Traversal in Geographic Routing, Ad hoc Now 2006

HGR: hybrid geometric routing Greedy Forwarding is efficient Impact of Localization Error on Perimeter

routing is tremendous—failure can occur Use VCS as complementary aglorithm: we

replace inefficient perimeter routing with greedy forwarding on VCS

HGR is more tolerant to localization errors since the complementary algorithm is VCS

HGR Backtracking If VCS fails, backtracking is used Axis by Axis basis-- in current axis:

Packet is forwarded to node closer to sink (physical distance) among nodes with the same VC

When void reached, reverse the backtracking direction or skip to next axis

When all axes are tried, HGR fails (possibly) HGR may also fail (since it is still a greedy

forwarding) Can use other backtracking algorithms as well

such as those in LCR and BVR

A Sample Path of HGR

HGR Path Quality

HGR: Impact of Localization Error

Third Contribution--AVCS Aligned Virtual Coordinates for Greedy Routing

in WSNs, in Proc. Of IEEE MASS 2006 Aligned Virtual Coordinates for Greedy

Geometric Routing in Wireless Sensor Networks, (extension to IEEE MASS 2006 paper),International Journal on Sensor Networks (IJSNET)

Aligned VCS (AVCS): Intuition Quantization Error: higher effect with higher

density VCS is set up based only on communication

connectivity, but not all connectivity information was used for VCS

Greedy Forwarding is used less with VCS than with PCS, leading to much more use of inefficient complementary routing (backtracking)

AVCS is immune to localization error, inheriting from VCS

AVCS: Intuition (Cont’)

AVCS: Alignment For Node A and all its Neighbors (N) in VCS, we have

The alignment function is used in AVCS as

The alignment is the average of virtual coordinates of the given node’s neighborhood.

Note: Different alignment functions have been studied, differences are trivial

Related Work

Serve as Localization Algorithm: 2D Multiple Perimeter Nodes, knowing their physical location Central location initializes all other nodes Nodes average the location with neighbors Long convergence time, low accuracy

AVCS avoids virtual voids

AVCS: reduced quantization error

AVCS Evaluation Scenario

A single hole is created in the center of the area, where all nodes are deployed into grids

Evaluation of AVCS: greedy ratio

Evaluation of AVCS: path stretch

Fourth Contribution—Securing Geometric Routing Towards Resilient Geographic Forwarding in WSNs, Q2SWinet'05

(Workshop) Securing Geographic Routing in Wireless Sensor Networks, in Proc. of

Symposium on Information Assurance (SIA) 2006 Location verification and trust management for resilient geographic

routing Source, Journal of Parallel and Distributed Computing (JPDC), February 2007

An Application-Driven Perspective on Wireless Sensor Network Security, Q2SWinet'06 (Workshop)

Application-Driven Approach to Designing Secure Wireless Sensor Networks, Wireless Communications and Mobile Computing, to appear

TARMAC, under preparation

Security of WSNs: introduction Unique characteristics of WSNs invite new modes

of attacks Sensor nodes are resource-limited and often

unattended easier to eavesdrop, capture, tamper with, and

carry on DoS Data sinks are more important than common nodes Vulnerability and Incentive Application dependent

Security of GR GR critically dependent on location Malicious nodes may claim a fake location

Sybil attack: malicious node creates multiple locations (ID’s)

Black-hole attack: the fake location causes all its neighbours to forward packets to it, but it does not forward them

Selective attack: some of those packets are selected to be forwarded, avoiding detection

Traffic-analysis attack: through eavesdropping, the attacker can discover the location of data users (sink)

Location verification: multi-equipment Sastry et al proposed: wireless signal and

ultrasonic are both used Verifier sends challenge to some node Upon receiving challenge, sensor node

reply through ultrasonic channel, with a nonce from the challenge

Location is verified by comparing the delay between wireless signal and the ultrasonic

Problems Specific hardware: ultrasonic device Location of Verifiers should be accurate Single verification at a given time Immediate response may not always be

available: honest node may be hurt

Localization Authentication Reverse the localization procedure: a non-

trusted sensor node is not allowed to generate its own location estimate

Can be used for triangulation-based localization methods

Authentication Procedure Sensor node sends an authentication (localization)

request to multiple anchors Upon receiving request, anchors would exchange

this request, estimating the location of the sensor Anchors would send a location certificate back to

the querying sensor The certified location information is exchanged

among sensors securely

How it works

Key observation: node will appear closer to, or further, from all anchors concurrently

Detectable when anchors exchange ranges Leads to Non-feasible location in all non-trivial

anchor placements

d2

d3

d1d2-dx

d3-dx

d1-dx

d2+dx

d3+dx

d1+dx

Multiple Unicast Attack Attacker can still attack this authentication

by send multiple unicast requests to different anchors: Sequentially sending: can be prevented by

synchronizing anchors with a tolerance of a beacon packet length

Concurrently sending: the attacker needs to be equipped with multiple (directional) transceivers, which is hard

Black-hole attack Attacker can still attack this system by

using the correct and certified location, but not to forward any incoming packets

Attacker can forward the incoming packet to a non-existing node

Meanwhile, packet may be dropped due to system reason: congestion, collision, etc.

A forwarding verification is needed

Trust-management Monitoring the packet forwarding:

To favor well behaving honest nodes by giving them the credit for each successful packet forwarding

To penalize suspicious nodes that supposedly lie about or exaggerate their contribution to routing

Once a node lies its location, it is excluded immediately

It can also be used as a link-quality aware geographic routing protocol: node with bad link-quality may lose credit as a forwarding candidate

Grading Function A sensor node initializes each neighbor with a trust level For each successfully forwarding, a neighbor’s trust level

is increased by

For each failed forwarding, trust level is decreased by

Basic Study Scenarios

Basic Study Evaluation

Impact of t: delivery ratio

Impact of t: Path Quality

Impact of t: Energy

Other Contributions Real-time Scheduling algorithm for WSNs:

Just-in-Time Scheduling (JiTS) New MAC Protocol possible for WSNs Link-quality insensitive GR

JiTS My Master Thesis Work Most Existing Scheduling algorithms for WSNs

try to forward incoming packets as early as possible

JiTS tries to forward packets as LATE as possible – Just before missing the deadline

By scheduling the traffic with such delay, JiTS is capable to deal with more potential data flow

JiTS related Publications Master Thesis JiTS: Just-in-Time-Scheduling for Real-

Time Sensor Data Dissemination, PerCom'06

JiTS: Queueing Delay Sensitive Scheduling for Real-Time Data Dissemination in WSNs, submitted to Real Time Systems Journal

New MAC technology MicaZ adapts the IEEE 802.15.4 (actually,

the ZigBee) MAC protocol ZigBee is Low-Rate Wireless Personal Area

Network (LR-WPAN) protocol, 256kbps IEEE 802.15.3 (actually the UWB) MAC

protocol is also WPAN protocol, which is High Rate 54Mbps – 480 Mbps

WPAN MAC protocols Low energy consumption: fit into WSNs Low cost: fit into WSNs Either low rate or high rate is available Drawback: transmission range is limited

Working with WiMedia UWB MAC protocol

An industrial replacement of the IEEE 802.15.3 protocols

TDMA and Contention Based communication protocol

Fit for limited resources Fit for the Stateless routing protocols

High Rate UWB performance Ex

Note: copyright reserved by Olympus

DRP Throughput with pkt size 1K

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50

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150

200

250

53.3 80 106.7 160 200 320

Data Rate (Mbps)

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Remaining Work Expanded Evaluation More Systematic Analysis GR with pure VCS Practical Hybrid GR

Detailed Study with more scenarios

To discover more anomalies of VCS: other possible failures of Greedy forwarding on VCS

To design more detailed study of HGR: discover the failure of the HGR

Combination of AVCS and HGR

The pure VCS is not Enough? Although the VCS was proposed to replace the

PCS, it may be not enough for pure greedy forwarding

The design goal of our geometric routing is to avoid the complementary routing as much as possible

PCS may be a necessary help for VCS To prove that: there is no VCS, which can provide

a consistent monotonic increasing (or decreasing) gradient between any given pair of nodes

Practical Hybrid Geometric Routing Note: I would like to do so, but not promise The practical geometric routing demands

the hybrid coordinates: PCS with VCS Some proposed the practical GPSR, which

adapts broadcast to discover the planarizing failure under localization error, losing the stateless nature of GPSR

Planarizing under localization error can be corrected with VCS help.

Demo: Visual GR Simulator Alpha Version Model Analysis tool, not Experiment Tool Showing:

Topology Planar graph GPSR: GF and Perimeter Routing GR on VCS and AVCS Anomalies on VCS

Thank you

Questions ?