Power management is an active area of research in wireless sensor networks (WSNs). Efficient power management is necessary because WSNs are battery-operated devices that can be deployed in mission-critical applications. From the communications perspective, one main approach to reduce energy is to maximize throughput so the data can be transmitted in a short amount of time. Frame fragmentation techniques aim to achieve higher throughput by reducing retransmissions. Using experiments on a WSN testbed, we show that frame fragmentation helps to reduce energy consumption. We then study and compare recent frame fragmentation schemes to find the most energy-efficient scheme.
Our main contribution is to propose a new frame fragmentation scheme that is optimized to be energy efficient, which is originated from the chosen frame fragmentation scheme. This new energy-efficient frame fragmentation protocol is called (Green-Frag). Green-Frag uses an algorithm that gives sensor nodes the ability to transmit data with optimal transmit power and optimal frame structure based on environmental conditions. Green-Frag takes into consideration the channel conditions, interference patterns and level, as well as the distance between sender and receiver.
The thesis discusses various design and implementation considerations for Green-Frag. Also, it shows empirical results of comparing Green-Frag with other frame
fragmentation protocols in terms of energy efficiency. Green-Frag performance results shows that it is capable of choosing the best transmit according to the channel conditions. Subsequently, Green-Frag achieves the least energy consumption in all environmental conditions.
|Date of Award||May 15 2013|
- Computer, Electrical and Mathematical Science and Engineering
|Supervisor||Basem Shihada (Supervisor)|
- frame fragmentation
- wireless sensor network
- power adaptive