Immune clonal selection algorithm for target coverage of wireless sensor networks

In wireless sensor networks, the coverage problems have received increased attention recently. The coverage concept is subject to wide ranging interpretations due to a variety of sensors and applications. Different coverage formulations have been proposed. Among those coverage concepts, the target coverage is a measure of the quality of service (QoS) of the sensing function, which is proved to be an NP-hard problem. In the target problem, the number of targets is monitored by some sensors, which have adjustable sensing range. Inspired by the immune system, the target coverage based on the immune clonal selection algorithm is proposed. The immune clonal selection algorithm is a relatively novel evolution optimisation computation method inspired by clonal selection principle of the human immune system. The method is used to extend the sensor network operational time by organising the sensors into a maximal number of adjustable range set covers that are activated successively. Only the sensors from the current active set are responsible for monitoring all targets and for transmitting the collected data, while nodes from all other sets are in a low-energy sleep mode. The maximum set coverage problem is computed by our approach. Theoretical analysis and performance evaluation results are presented to verify our approach.

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