Sensor Coverage Problem in Sparse MANET Environments
In this paper, we define the problem of sensor coverage in sparse mobile ad hoc networks. Previously, the nodes are assumed static or the number of nodes is large enough to cover the area for the coverage problem in wireless sensor networks. However, in s
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IT Convergence Education Center, Dongguk University, Seoul, Korea [email protected] Department of Computer Science and Engineering, Korea University, Seoul, Korea [email protected] 3 School of Information Technology, Catholic University of Daegu, Gyeongsan, Korea [email protected]
Abstract. In this paper, we define the problem of sensor coverage in sparse mobile ad hoc networks. Previously, the nodes are assumed static or the number of nodes is large enough to cover the area for the coverage problem in wireless sensor networks. However, in sparse mobile ad hoc network environments, the semantics of the coverage problem differ in that the nodes are free to move in the area and the distance between the nodes should be long enough in order not to overlap the nodes’ coverage to maximize the total coverage area in the network. We formulate the sensor coverage problem in sparse mobile ad hoc network environments. Keywords: Sensor coverage Mobile ad hoc network network Machine to machine
Wireless sensor
1 Introduction Wireless sensor networks (WSNs), sometimes called wireless sensor and actuator networks (WSANs), are spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to forward their data via the network [1]. Meanwhile, mobile ad hoc networks (MANETs) have been one of the most innovative and challenging wireless networking paradigms in the field [2, 3]. Hence, MANET immediately gained momentum and produced tremendous research efforts in the mobile network community [4–6]. By taking advantage of WSN and MANET, there are many applications that projected to have a significant impact into our daily lives such as battlefield surveillance, environmental monitoring, industrial diagnostics, and precision agriculture [7, 8].
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2014R1A1A2055463 and NRF-2015R1D1A1A01061373). © Springer Nature Singapore Pte Ltd. 2017 J.J. (Jong Hyuk) Park et al. (eds.), Advances in Computer Science and Ubiquitous Computing, Lecture Notes in Electrical Engineering 421, DOI 10.1007/978-981-10-3023-9_44
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J. Lim et al.
Among various performance metrics for sensor networks, coverage is one of the most important ones that reflect how well a sensor field is monitored [9, 10]. The coverage problem is a well-known problem in wireless sensor networks. To maximize the coverage area, the nodes in the network should cooperate with each other. Because the sensor nodes have limited capabilities including battery, computing power, and coverage, each node proactively schedules itself to be in a state either sleep or wake-up with the assumption of the dense network. Covering the area of the sensor networks with minimum nodes is considered as an NP-hard problem and various solutions have been proposed [11–13]. On the other hand, when few nodes exist in the sensor network, it is necessary to reconsider the sensor covera
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