Target Coverage Heuristics in Wireless Sensor Networks
In order to cover a fixed set of targets within a wireless sensor networks, sensor nodes are closely deployed. Since, sensors are heavily deployed, instead of all sensors, few sensors are sufficient to monitor full target set. Therefore, to maximize the t
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Abstract In order to cover a fixed set of targets within a wireless sensor networks, sensor nodes are closely deployed. Since, sensors are heavily deployed, instead of all sensors, few sensors are sufficient to monitor full target set. Therefore, to maximize the total network lifetime for covering all the targets (target coverage problem), sensor nodes are partitioned into cover sets. Each cover set is sufficiently enough to monitor the complete target set. Then the cover sets are activated sequentially for a fixed duration. The summation of all the covers duration is called network lifetime. More number of such cover set results in longer global network lifetime. To do this, in this work, we propose an energy optimal heuristic which generates maximum possible cover sets to reach the upper bound calculated for network lifetime. Keywords Target coverage
Network lifetime Upper bound Cover set
1 Introduction Wireless sensor network mainly consists of tiny, low-powered sensors incorporated with a small microprocessor, transceiver, and memory resource to make it functional. Mainly, sensor networks are used in area like wild life monitoring, fire detection, land Manju (&) D. Singh B. Kumar Netaji Subhash Institute of Technology, Sector-3, Dwarka, New Delhi 110078, India e-mail: [email protected] D. Singh e-mail: [email protected] B. Kumar e-mail: [email protected] S. Chand School of Computer and System Sciences, Jawaharlal Nehru University, New Delhi 110067, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 R.K. Choudhary et al. (eds.), Advanced Computing and Communication Technologies, Advances in Intelligent Systems and Computing 562, https://doi.org/10.1007/978-981-10-4603-2_25
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sliding detection, and military application [1–3] where human accessibility is not possible. To facilitate these applications, sensors are densely deployed to provide continuous surveillance. Sensor nodes are equipped with small battery device, which is not rechargeable. Thus, we need to optimize this limited source. In this paper, our main focus is on sensor scheduling for target coverage problem. Here, we assume that sensor network is densely deployed. One way to increase the total network lifetime is to put redundant sensors to Sleep mode. In order to follow this strategy, activate only a subset of sensor (say cover set) to monitor the complete set of targets. Then activate these cover set consecutively in the given environment which in turn maximizes the network lifetime. Many works addressed this coverage problem (target coverage) as maximum network lifetime problem (MLP) [4, 5]. The main objective of the MLP is to maximize the functional duration of a deployed network by guaranteeing the coverage of fix number of targets. Recent works shows bit more interest to use the exact approaches while solving optimization problems in wireless sensor networks [6–10]. The column generation approach has been proved to be better for solving the maximum network lifetime problem. The col
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