A coverage problem is one of the important issues to prolong the lifetime of a wireless sensor network while guaranteeing that the target region is monitored by a sufficient number of active nodes. Most of existing protocols use geometric algorithm for each node to estimate the degree of coverage and determine whether to monitor around or sleep. These algorithms require accurate information about the location, sensing area, and sensing state of neighbor nodes. Therefore, they suffer from localization error leading to degradation of coverage and redundancy of active nodes. In addition, they introduce communication overhead leading to energy depletion. In this paper, we propose a novel coverage control mechanism, where each node relies on neither accurate location information nor communication with neighbor nodes. To enable autonomous decision on nodes, we adopt the nonlinear mathematical model of adaptive behavior of biological systems to dynamically changing environment. Through simulation, we show that the proposal outperforms the existing protocol in terms of the degree of coverage per node and the overhead under the influence of localization error.
Abstract-A coverage problem is one of major issues of a wireless sensor network to prolong the lifetime while guaranteeing that the target region and objects are monitored by sufficient number of active nodes. There have been many proposals on the coverage problem, but most of them use geometric algorithms in order to determine whether to monitor around or sleep. As such, these algorithms require information about the location, sensing area, and sensing state of neighbor nodes. In addition, they suffer from localization error leading to degradation of coverage and redundancy of active nodes. In this paper, we propose a coverage control mechanism where each sensor node relies only on the information about the degree of coverage of the target region. To enable autonomous decision of sensor nodes, we adopt a nonlinear mathematical model called the attractor selection model of adaptive behavior of biological systems to dynamically changing environment. Through simulation experiments, it is shown that the proposal outperforms the existing protocol regarding the pernode coverage and the overhead under influece of localization error.
Bio-inspired network controls are driven by the competition between their ordering force and disordering force. Both forces simultaneously affect their performance and robustness. Therefore, we must carefully determine their balance. In this paper, we focus on thermodynamic phenomena where a substance achieves the balance between both forces depending on its temperature. We translate bio-inspired network controls from the perspective of thermodynamics, and we analytically show that the appropriate balance between both forces can be achieved by selecting appropriate temperature.
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