ECE 555Real-Time Embedded Systems

Multi-Channel Communication in Wireless Sensor Networks(WSN)

Presented by Rukun Mao

Nov. 13th 2008

Reference

• Yafeng W., Stankovic J.A., Tian H, Shan L, “Realistic and Efficient Multi-Channel Communications in Wireless Sensor Networks”

• Hieu Khac Le, Dan Henriksson, and Tarek Abdelzaher, “A Practical Multi-Channel Media Access Control Protocol for Wireless Sensor Networks”

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Outline

• Introduction• Experiments on Multi-Channel Reality• Tree Based Multi-Channel Protocol (TMCP)• Minimum Interference Channel Assignment

Problem• Performance Evaluation• Conclusion

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Introduction

• Current WSN hardware such as Micaz and Telos provide multiple channels– Improve network throughput– Provide reliable and timely communication services

• Recently MAC layer multi-channel protocols are proposed– To assign different channels to two-hop neighbors

and coordinate channel switching– Also called node-based schemes

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Introduction

• Practical issues for node-based scheme– A large number of orthogonal channels are

needed in dense networks.– Require precise time synchronization at nodes.– Channel switching delay and scheduling overhead.– Complex.

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Non-orthogonal Channel Interferences

• Place three Micaz motes in a line– One transmitter, one receiver, and one jammer– The jammer’s transmission is synchronized with

the transmitter.

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Transmitter : channel 11Receiver : channel 11

Jammer : channel 12 (adjacent) channel 13 (2 channel

away)

Interferences with 802.11 networks• Put 8 pairs of Micaz motes closely in a department

office with 802.11 networks– Each pair uses unique channel and all 8 channels are

orthogonal.– Multi-channel protocols must have capabilities to work

well with a small number of available channels.

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Impact of Time Synchronization Errors

•Each node with unique channel and all are synchronized.•A time period is divided into 2 time slots

1st time slot Nodes in odd positions send packets Nodes in even positions receive packets

2nd time slot is vice versa

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TMCP

• To overcome two problems in practical networks– The small number of available orthogonal

channels.– Unavoidable time errors.

• Data collection traffic – Multiple information flows generated at sensor

nodes converge to the base station.

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TMCP• Main idea

– Partition the whole network into multiple vertex-disjoint sub-trees all rooted at base station

– Allocate different channels to each sub-tree.– Forward each flow only along its corresponding sub-

tree.• 3 components

– Channel detection (CD)– Channel assignment (CA)– Data communication (DC)

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TMCP

• CD finds available orthogonal channels – Two motes are used to sample the link quality, and

we selected good link qualities with non-adjacent channel.

– Assume we have k channels at this point.• CA partitions the whole network into k sub-trees

and assigns one unique channel to each sub-tree– Inter-tree interference is eliminated (non-adjacent)– Intra-tree interference is minimized ( same channel)

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TMCP

• DC manages the data collection through each sub-tree– Assume the base station is equipped with multiple

radio transceivers.– Without time synchronization

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Model and Problem Definition

• The goal is to minimize intra-tree interferences.• Assume that a sensor network is a static.• The interference set of a node u is defined as

– INT(u) = {v|v є D(v, Iv), where D(v, Iv) is the interference disk

with node v in its center and radius Iv} (*)– Interference value: int(u) = |INT(u)|

• The intra-tree interference value of a tree T is defined as– int(T) = max{int(u): u is a non-leaf of T}

13* M. Burkhart, P. V. Rickenbach, R. Wattenhofer, and A. Zollinger, “Does topology control reduce interference,” in ACM MobiCom, 2004.

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PMIT Algorithm• Apply Breadth-First search algorithm from the base

station to construct a fat tree.– Nodes keep height and have multiple parents on the fat

tree.– The tree is a shortest path tree.

• Execute the channel allocation one-by-one level from top to bottom on the fat tree– For each node, choose an optimal tree and add this node

to bring the least interference to this tree.– Selects a parent which has the least interference value.– Nodes with fewer parents first, because they are less free

to choose channels.

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Evaluation of the PMIT Algorithm

• Simulations parameters– 200m x 200m field– 250 nodes are uniformly distributed– Communication range is 10~35m – Interference range is 1.5 times as the

communication range

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Evaluation of the PMIT Algorithm

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Performance with different node density

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Performance comparison of TMCP and MMSN

Evaluation in a Real Testbed

• Experiment setup– A real testbed with 20 Micaz motes.– Four motes are laid closely together to act as a

base station with four transceivers.

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• TMCP effectively reduces interferences and mitigates congestion at nodes.• TMCP works well in a real sensor network.

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Conclusion• Multiple channels to improve network performance

in WSNs.• Realities in WSNs

– Small number of available channels– Synchronization errors

• TMCP – Work with a small number of channels.– Work without the need of time synchronization.– Decrease potential radio interferences.– Three components: Channel Detection, Channel

Assignment(CA), Data Communication(DC)

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Critique

Critique1: Communication between nodes in different sub-trees is blocked.

Critique2: Adjacent channels are not used, and limit bandwidth is not fully utilized.

Critique3: The assumption that interference sets of all nodes are already know is not applicable under certain circumstance.

Critique 4: interference range/communication range ratio is set at 1.5 without justification.

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A Practical Multi-channelMedia Access Control Protocolfor Wireless Sensor Networks

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Outline

• Introduction• Related Work• Protocol Analysis• Implementation• Experimental Results• Conclusion

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Introduction

• A typical sensor network• There is lots of collisions and interference

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Introduction• The solution is

multi-channel• Utilizing multi-

channel at MAC layer give any application benefit from multi-channel for free.

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Related Work• Many multi-channel MACs were developed for WSN

and ad-hoc networks.• All of them have at least one of below drawbacks

– Assume channel switching time is negligible– Require time synchronization– Require multi-radio or special radio interface

• As a result– Most of them were only illustrated in simulation– The rest need special sensor node with multi-radio

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Contribution

– Uses only one half-duplex radio interface– Considers real channel switching overhead– Is lightweight with small memory and code

footprint– Does not require any input from the upper

layers

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Protocol Analysis

• Each node has a home channel• A node stays at its home channel while listening

to incoming messages• If node A want to send a message to node B, A

need to switch to B’s home channel• It is desirable to minimize cross-channel

communication and maximize same channel traffic. This is directly related to the objective of the K-Way cut problem.

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The K-Way Cut Problem

A K-Way Graph Partitioning:– Given a graph G(V, E)– Given a number K– Divide the graph in to K sub-graphs such that the

total weight of edges across the sub-graphs is minimum.

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“K-Way Cut Problem” Algorithm

Some intuitions– More channels are only allocated when needed– Nodes with better view of network traffic will

initiate the cut– Nodes with less information should act locally to

minimize cross-channel communication

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Three Rules• Rule 1: Nodes start at channel F0

• Rule 2: Channel Advancement• Each node j periodically broadcasts <#successful channel access = sj,

#failed channel access fj> to its neighborhood.• Node j estimates the probability of successful access the channel α

If α is below a threshold, node considers advancing channel with the probability β

• Rule 3: Channel FollowIf a node A figures out its neighbor B switches channel, A consider going to the channel in which it has highest data flow.

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OutInOutInrsink_facto

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The switch fluctuation problem

Use a simple control scheme– Consider a node at channel i having successful

access probability αi(k) at time k- Probability to switch from channel i to channel i+1 is

βi,i+1(k) at time k

If αi(k) < αref

βi,i+1(k) βi,i+1(k-1) + Kc(αref – αi(k))If αi(k) ≥ αref

βi,i+1(k) βi,i+1(k-1) – Kc1(αi(k)- αref )

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Implementation

• Implemented on MicaZ mote• Same code works for both TOSSIM and MicaZ• Channel switching time is ~50ms• Code footprint is around 9KB and RAM

footprint is less than 1KB

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Experimental Results

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Experimental Results

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Experimental Results

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Conclusion

Presented MAC has the following advantages– Using only one half-duplex radio interface– Having channel switching time conforming to

reality– Lightweight enough to run on MicaZ mote with

small memory and code footprint– Not requiring any input from the upper layers

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Critique

• There is no discussion about interference among K available channels.

• Threshold γ is determined based on worst-case delay d, which will change during various network status.

• Only compare with single-channel MAC. Should also compare with other multi-channel MAC

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comparisonPaper 1 Paper 2

MAC Multi-channel Multi-channel

Solution Specific( data collection) General Purpose

Networks Status Static Dynamic

Control Method Heuristic Heuristic and Feedback Control

Implementation Simulation and Hardware Simulation and Hardware

Node behavior Stay in sub-tree switching

Group based Yes Yes

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Acknowledgement

• I would like to thank Yu-Chun Chang(paper 1) and Hieu Khac Le (paper 2) for sharing PPT slices with me, which make this presentation possible.

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Thank You

• Questions?

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