Cataloged from PDF version of article.Wireless sensor networks, which consist of many sensor devices communicating
with each other in order to sense the environment, is an emerging field in the
area of wireless networking. The primary objective in these wireless networks
is the efficiency of energy consumption. Since these networks consist of a large
number of sensors, allowing some of the nodes to sleep intermittently can greatly
increase the network lifetime. Furthermore, some applications do not require
100% coverage of the network field and allowing the coverage to drop below
100%, i.e., partial coverage, can further increase the network lifetime.
A sleep scheduling algorithm must be distributed, simple, scalable and energy
efficient. In this thesis, the problem of designing such an algorithm which
extends network lifetime while maintaining a target level of partial coverage is
investigated. An algorithm called Distributed Adaptive Sleep Scheduling Algorithm
(DASSA) which does not require location information is proposed. The
performance of DASSA is compared with an integer linear programming (ILP)
based optimum sleep scheduling algorithm, an oblivious algorithm and with an
existing algorithm in the literature. DASSA attains network lifetimes up to 89%
of the optimum solution, and it achieves significantly longer lifetimes compared
with the other two algorithms.
Furthermore, the minimum number of sensors that should be deployed in
order to satisfy a given partial coverage target with a certain probability while
maintaining connectivity is computed and an ILP formulation is presented for
finding the minimum number of sensors that should be activated within the set
of deployed sensors.Yardibi, TarıkM.S
