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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
0
50
100
150
200
250
53.3 80 106.7 160 200 320
Data Rate (Mbps)
Th
rou
gh
pu
t (M
bp
s)
No Acc
Imm Ack
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 ?