Energy Optimization in Mobile Wireless Sensor Networks

1
Energy Optimization in Mobile Wireless Sensor
Networks
Department of Computer Science
EngineeringCollege of Engineering
Fatme El-Moukaddem and Eric Torng

• Centralized Approach
• Traffic Patterns
• Single source single destination
• Multiple sources single destination
• Main Idea
• One node acts as a controller.
• It computes optimal positions for other nodes.
• It transmits new positions to relative nodes
• The nodes then move to new positions and begin
  transmission
• Computation Method
• Nodes are labeled as either odd or even depending
  on their order in the transmission path
• Iterative approach each iteration split into 2
  rounds Even and Odd
• In even (odd) rounds, the controller computes
  the locally optimal position for even (odd)
  servers based on the position of their odd (even)
  neighbors.
• The controller iterates until convergence
• Experiments show that convergence to globally
  optimal positions occurs after only 2 iterations
  (4 rounds)

We consider the problem of energy optimization in
mobile wireless sensor networks. Nodes are
battery powered and consume energy when they
transmit data, perform computations and move to a
new location. The amount of energy consumed
depends on the distance traveled or transmitted
and the size of the message. Our goal is to find
the optimal positions of nodes along one or more
transmission paths in order to minimize the total
energy spent.
The previous graph shows the energy consumption
costs under 3 different approaches. Savings
through the optimal approach can be up to 25
from either of the other 2 approaches for
messages between 20 and 40 MB
Motivation
2c
Distributed Approach The centralized algorithm is
not feasible for many application. We propose a
distributed algorithm that produces results very
close to optimal. The key observation is that
computing the locally optimal position of a
server depends only on the current position of
its neighbors. Thus, the server itself can
perform this computation instead of the
controller. In the first transmission round,
servers get notified of their order and get an
even/odd label. In subsequent rounds,
participating servers (odd or even) compute their
new positions and exchange with their neighbors.
1c
In the graph above, the nodes are initially
positioned at 1a and 2a. If we ignore moving
costs, the optimal positions would be 1b and 2b.
But in practice moving consumes energy, so the
optimal solution is to move to positions 1c and
2c. In general, with short messages, the optimal
positions are closer to the original positions
and with longer messages, they are closer to the
evenly spaced positions.
April 18, 2008