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Tuesday 30 October 2012

Fast Data Collection in Tree Based Wireless Sensor Networks


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 

converge cast. 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 converge cast. 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.


Algorithm used:

1. BFS TIME SLOT ASSIGNMENT
2. LOCAL-TIME SLOT ASSIGNMENT

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