Data Collection in Tree-Based Wireless Sensor Networks

Ozlem Durmaz Incel, Amitabha Ghosh, Bhaskar Krishnamachari, and krishna kant chintalapudi

Abstract

We investigate the following fundamental question - how fast can information be collected from a wireless sensor network

organized as tree? To address this, we explore and evaluate a number of different techniques using realistic simulation models under

the many-to-one communication paradigm known as convergecast. We first consider time scheduling on a single frequency channel

with the aim of minimizing the number of time slots required (schedule length) to complete a convergecast. Next, we combine scheduling

with transmission power control to mitigate the effects of interference, and show that while power control helps in reducing the schedule

length under a single frequency, scheduling transmissions using multiple frequencies is more efficient. We give lower bounds on the

schedule length when interference is completely eliminated, and propose algorithms that achieve these bounds. We also evaluate the

performance of various channel assignment methods and find empirically that for moderate size networks of about 100 nodes, the use

of multi-frequency scheduling can suffice to eliminate most of the interference. Then, the data collection rate no longer remains limited

by interference but by the topology of the routing tree. To this end, we construct degree-constrained spanning trees and capacitated

minimal spanning trees, and show significant improvement in scheduling performance over different deployment densities. Lastly, we

evaluate the impact of different interference and channel models on the schedule length.

Details

Publication typeArticle
Published inIEEE Transactions on Mobile Computing
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