Target Coverage Based On Immune Algorithm In Directional Sensor Networks

With the development of the sensor technology,computer technology,signal processing technology,wireless sensor networks(WSN) becomes a major concern in research field.For the limitation of the sensor hardwares,WSN consists of a large number of sensors with limited power which are randomly deployed in a certain area.The sensor nodes are capable of monitoring,data gathering,wireless communications.Former sensing model of sensor nodes in WSN is omni-directional,whose sensing area is a round.But in realistic condition we have another kind of sensor nodes which have different sensing capabilities in different sensing directions,and its sensing range is a sector whose direction can be turned. So former resolvents in omni-directional wireless sensor networks don't adapt to the directional wireless sensor networks,for which we need to present new resolvents.Coverage issue which consists of area coverage,targets coverage and so on is fundamental and crucial in the research of WSN.Now people pay attention mostly to the area coverage,and the researchs in targets coverage are scarce.The thesis focuses on the targets coverage in directional sensor networks. With the vast sensors and targets which are randomly deployed in an area,we create mathematic modeling of directional sensors and choose sensors as few as possible that can monitor all the targets.So we can economize the cost of hardwares and also prolong the life of directional sensor networks.We introduce the conception and the essential theories of directional sensor networks first in the thesis, and also discuss the 0-1 sensing model and the probability sensing model.Based on the 0-1 sensing model,we have simulation experiments at the same parameters of directional sensor networks with immune algorithm(IA) which consists of immune programming algorithm(IP) and clone selection algorithm(CSA),and the simulation results are compared with genetic algorithm.In the probability sensing model and considering the searching time and stability of algorithms,we adopt immune programming algorithm,and then analyse the simulation results.Simulation experiments show that IP and CSA are valid for targets coverage in directional sensor networks and better than genetic algorithm.Also IP is valid for targets coverage in probability sensing model.