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Practical Belief Propagation in Wireless Sensor Networks. Bracha Hod Based on a joint work with: Danny Dolev, Tal Anker and Danny Bickson The Hebrew University of Jerusalem. Outline. Introduction to Wireless Sensor Networks Belief Propagation overview

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practical belief propagation in wireless sensor networks

Practical Belief Propagation in Wireless Sensor Networks

Bracha Hod

Based on a joint work with:

Danny Dolev, Tal Anker and Danny Bickson

The Hebrew University of Jerusalem

outline
Outline
  • Introduction to Wireless Sensor Networks
  • Belief Propagation overview
  • Efficient Belief Propagation framework for Wireless Sensor Networks
  • Experimental evaluation
  • Summary

Israeli Networking Seminar May 29, 2008

wireless sensor networks
Wireless Sensor Networks
  • Technology is pushed by breakthroughs in MEMS, wireless communication, battery power, etc.
  • Wireless Sensor Networks (WSNs)
    • Wireless network consisting of spatially distributed autonomous devices using sensors
    • The sensors cooperatively monitor physical or environmental conditions

Israeli Networking Seminar May 29, 2008

wsn characteristics
WSN Characteristics
  • Limited power sources and restricted computational capacities
  • Wireless medium which imposes constraints, such as collisions and errors
  • Topology changes due to interference, poor link quality, sleep states, death, etc.
  • Special network dynamic resulting from the self-organization property
  • Scaling problems because the network has a large number of nodes

Israeli Networking Seminar May 29, 2008

history
History
  • 1994 - DARPA funded research on ‘Low Power Wireless Integrated Microsensor’
  • 1998 - WSN technology has been nurtured in its early stages at UC-Berkeley and UCLA
    • It is estimated that in the US over $100 million in government funding has been invested in university WSN research projects since then
  • 2003 - Technology Review from MIT, listed WSN on the top, among 10 emerging technologies, that would impact our future
  • 2008 – About ten years of academic work has been done in this area but still a long way to go

Israeli Networking Seminar May 29, 2008

current status
Current Status
  • Research
    • Many protocols for routing, synchronization, fault tolerant, localization, collaborative information processing, data aggregation, etc.
  • Development
    • Dedicated Operating System and Database system, programming languages and test deployments
  • Standardization
    • IEEE 802.15.4, Zigbee, 6lowpan
  • Still a lot to do
    • Deployment, integration with other networks, security and scalability

Israeli Networking Seminar May 29, 2008

inference in wsns
Inference in WSNs
  • Data fusion and processing are the core information gathering activities performed in the sensor nodes
  • Consequently, inference methods become an increasing research interest in the field of WSNs
graphical model

A

B

C

D

Graphical Model
  • In this model, an undirected graph G = (V,E) is a set of nodes V and arcs E, which represent dependencies among random variables
  • A complex system is viewed as a combination of many simpler pieces connected by probability theory
  • The idea: instead of calculating

8-sums

we can calculate

4-sums

and 2-sums

Israeli Networking Seminar May 29, 2008

belief propagation bp
Belief Propagation (BP)
  • BP is an iterative algorithm for computing maximum or marginal posterior probabilities by a local message passing
  • BP is associated with rapid convergence, accurate results and good performance in asynchronous environment
  • When performed on trees, BP converges to the correct values in a finite number of iterations

Israeli Networking Seminar May 29, 2008

the min sum variation
The Min-Sum Variation
  • The goal is to minimize the overall cost in the network, based on the local cost functions and the constraints between the nodes
  • Each node transmits to its neighbors a message with its local and joint costs. Each neighbor updates its own belief accordingly and transmits the new belief
  • Gradually the information is propagated through the network until the nodes converge to a common belief

Israeli Networking Seminar May 29, 2008

practical considerations
Practical Considerations
  • The unique constraints and requirements in WSN demand changes in traditional algorithms
  • Several issues to address
    • Mapping WSN to graphical model
    • Robustness against failures
    • Scalability

Israeli Networking Seminar May 29, 2008

mapping wsn to graphical model

X1

m12

m21

X2

m32

m24

m42

m23

X4

X3

m45

m54

X5

Mapping WSN to Graphical Model
  • Loopy BP
    • Operates on a cyclic network
    • Usually works well because the cycles are large
  • Junction Tree
    • Creates a tree based on the cliques in the graph
    • Scales exponentially with the number of nodes
    • Involves high overhead

Israeli Networking Seminar May 29, 2008

robustness against failures
Robustness against Failures
  • Broadcast communication
    • The message update rule is not an atomic operation which may result in erroneous calculation
  • Synchronization problems
    • Asynchronous messages may harm the accuracy
  • Topology changes
    • Alink break in the middle of the message-passing may badly affect the convergence

Israeli Networking Seminar May 29, 2008

scalability
Scalability
  • The original BP algorithm is based on a local message passing, but it is not scalable
    • The process is performed in the entire network
    • The convergence depends on the size of the network, and as a result, time and message complexity are not constant

Israeli Networking Seminar May 29, 2008

our solution
Our Solution
  • Adoption of two WSNs’ approaches
    • Localized Algorithms
    • Data-centric
  • Resulting in

Approximation by a set of local optimums instead of a single global optimum

 Energy-efficient, fully distributed, asynchronous, robust and scale scheme

Israeli Networking Seminar May 29, 2008

efficient bp framework
Efficient BP Framework
  • Construction of multiple trees according to the routing tree properties and the information that the nodes hold
  • Every tree is created on-the-fly using a special message, without any maintenance
  • A “round” field in each message helps in dealing with the asynchronous process
  • Part of the errors may be detected and overcome
  • Scalability is achieved by operating in a restricted region, with limited number of rounds

Israeli Networking Seminar May 29, 2008

empirical evaluation
Empirical Evaluation
  • Case study: clustering
  • The challenge is to efficiently form a connected disjointed group of nodes in a local and distributed manner. Each group contains a single leader and several ordinary nodes

Israeli Networking Seminar May 29, 2008

simulation framework
Simulation Framework
  • Simulation in TOSSIM, TinyOS simulator
  • 5 different time slots were used to validate the behavior on different network topologies
  • The localized algorithm vicinity was set to 2 with constant number of rounds equal to 8
  • In the simulation, the average density is 14 which means that the optimal number of clusters for 50 nodes is about 4

Israeli Networking Seminar May 29, 2008

simulation results
Simulation Results
  • Network topology
  • Message-passing trees
  • Clustered network

Israeli Networking Seminar May 29, 2008

simulation results1
Simulation Results
  • Number of clusters per 50 nodes
  • Percent of nodes who have a cluster head

Israeli Networking Seminar May 29, 2008

simulation results2
Simulation Results
  • Percent of nodes who reach a full convergence
  • Average loss messages in a message-passing tree

Israeli Networking Seminar May 29, 2008

summary
Summary
  • WSNs are envisioned to become an integral part of our lives, in applications such as environmental monitoring, smart spaces, medical monitoring, etc.
  • Two leading approaches: localized algorithms and data-centric, are essential for the design of practical and robust algorithms in WSNs
  • BP is a promising approach to solve inference tasks in WSNs, when combined with these two approaches.

Israeli Networking Seminar May 29, 2008

thank you

Thank You!

Israeli Networking Seminar May 29, 2008