Abstract
Directional sensors are a special class of sensors that have special characteristics, such as the angle of sensing. Hence the techniques or methods that are used to solve problems in traditional disk-based sensing models may not be applicable to directional sensor networks. Random deployment of directional sensor nodes usually fails where the number of sensors are limited or have less sensing capability. This paper addresses coverage enhancement of applications that use directional sensor nodes. We assume that the number of directional sensor nodes are less than the number of objects to be covered in the region. The main aim is to identify the optimal/near optimal deployment locations of the directional sensor nodes such that the coverage is maximized. We use Particle Swarm Optimization (PSO) algorithm to compute the deployment locations of the nodes. The experimental results reveal that PSO is a promising method to solve this problem.
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Singh, P., Mini, S., Sabale, K. (2016). Particle Swarm Optimization for the Deployment of Directional Sensors. In: Panigrahi, B., Suganthan, P., Das, S., Satapathy, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2015. Lecture Notes in Computer Science(), vol 9873. Springer, Cham. https://doi.org/10.1007/978-3-319-48959-9_15
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DOI: https://doi.org/10.1007/978-3-319-48959-9_15
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