A LowLatency and EnergyEfficient Algorithm for Convergecast in Wireless Sensor Networks

1
A Low-Latency and Energy-Efficient Algorithm for
Convergecast in Wireless Sensor Networks

• Authors
• Sarma Upadhyayula, Valliappan Annamalai,
  Sandeep Gupta
• Presented by
• Bin Wang
• Arizona State University

2
Presentation Flow

• Introduction
• Problem Description
• System Model
• Algorithm
• Results
• Conclusions and Future Work
• References

3
Introduction

• Wireless Sensor Networks (WSN) long life
  expectancy
• Power Anemic
• Communication consumes maximum energy
• Data aggregation (convergecast) is a frequent
  operation in WSN important to minimize its
  energy consumption
• Prior Work PEGASIS Step02, LEACHWendi00,
  CCTCCAValli03
• Typically, convergecast follows broadcast
  broadcast tree for convergecast. Bhas02

4
Introduction Contd...

• Prior work concentrate on energy efficiency
  alone.
• We have dual objective Energy-Efficiency and
  Low-Latency
• Conventional approach not necessarily the best
  approach

5
Problem Description

• n nodes in the network
• Data from all the nodes to be collected at a
  central node
• Single Hop or Multi-Hop communication
• Energy consumed for communication is proportional
  to distance ( , between 2 and 4)Wendi00
• Objective 1 Find a route connecting all nodes
  to central node consuming minimum energy.
• Objective 2 Minimum latency

6
System Model

• Assumptions
• Nodes are static and clocks are synchronized
• Every node has only one transceiver
• A node can transmit or receive at a time but not
  both
• Intermediate nodes concatenate the data they
  receive during upstream transmission
• Intermediate nodes wait until it receives data
  from all the nodes in whose path it lies.

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System Model

• Energy Model Wendi00

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System Model

• Latency Model Valli03
• Let be time taken to transmit longest data
  packet
• Latency is the total time required to transmit
  data from all the nodes to the central node

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System Model

• Latency Model
• Balanced trees increases possibility of multiple
  simultaneous transmissions
• number of children per node where is
  a positive integer
• If, due to the rule, a node will be left out of
  the tree overlook the rule.

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Algorithm (CCA)

• Rationale for Tree Construction
• Broadcast trees may not be suitable for
  convergecast

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Tree Construction Algorithm

• Constructs tree following greedy approach
• A set of nodes chooses closest neighbors as its
  children subject to
• This process is followed iteratively until all
  the nodes in the network join the tree

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Tree Construction Algorithm

Network
Tree
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Channel Allocation Algorithm

• A fixed number of CDMA codes are given
• Each node is assigned a triplet (Transmission
  Code, Reception Code, Transmission Time Slot)
• Reception code of a node and Transmission code of
  all its children are same
• A node uses a time slot and a code for
  transmission if
• Its parent is receiving using same code
• Choosing the code and time slot will avoid any
  collisions with all of its neighbors

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Channel Allocation Algorithm

Network
(Transmission Code, Reception Code, Transmission
Time Slot)
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Results

• Energy for Convergecast ( 3)
• Valli03 and CCA consumes almost same amount
  of energy for convergecast
• CCA gains upto 8 over Imrich87 for network
  of size gt150 nodes

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Results

• Latency for Convergecast ( 3)
• CCA is almost 4 times faster than Valli03 and
  2 times faster than Imrich87

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Conclusions and Future Work

• Proposed a tree construction and channel
  allocation algorithm for convergecast satisfying
  two objectives
• Showed that broadcast trees are not efficient for
  convergecast
• The proposed work should be studied for
  distributed manner
• Cluster based convergecast can be studied in
  future work

18
References

• Valli03 V. Annamalai., S.K.S. Gupta and L.
  Schwiebert On Tree-Based Convergecasting in
  Wireless Sensor Networks. IEEE Wireless
  Communications and Networking Conference 2003,
  New Orleans 2003.
• Imrich87 I. Chalmatac. and S. Kutten
  Tree-Based Broadcasting in Multihop Radio
  Networks. IEEE Transactions on Computers Vol.
  C-36, No. 10, Oct 1987.
• Wendi00 W. R. Heinzelman, A. Chandrakasan and
  H. Balakrishnan Energy-Efficient Communication
  Protocol for Wireless Micro Sensor Networks.
  Proceedingsof the Hawaii International Conference
  on System Science, Jan 2000.

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Reference

• Step02 S. Lindsey, C. Raghavendra, K. M.
  Sivalingam Data Gathering Algorithms in Sensor
  Networks Using Energy Metrics. IEEE Transactions
  on Parallel and Distributed Systems, Vol. 13, No.
  9, Sept 2002.
• Bhas02 B. Krishnamachari, D. Estrin and S.
  Wicker Impact of Data Aggregation in Wireless
  Sensor Networks. International Workshop on
  Distributed Event-Based Systems (DEBS, 02)
  Vienna, Austria, July 2002.