Abstract
In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.
Highlights
In Emerging Sensor Networks (ESNs), sensor nodes are equipped with several abilities, including information acquisition, wireless communication, data processing and self-organization
By making a global and comprehensive judgment of the nodes based on the degree of coverage redundancy in the network, the redundant nodes may be closed according to certain rules so as to achieve a balanced energy consumption and prolong the network lifetime [10]
Aiming at resolving the coverage problem for randomly deployed mobile sensor networks, Meng et al [31] presented two strategies named coverage-priority and connectivity-priority for node deployment based on a ring model of energy consumption
Summary
In Emerging Sensor Networks (ESNs), sensor nodes are equipped with several abilities, including information acquisition, wireless communication, data processing and self-organization. By making a global and comprehensive judgment of the nodes based on the degree of coverage redundancy in the network, the redundant nodes may be closed according to certain rules so as to achieve a balanced energy consumption and prolong the network lifetime [10] This type of scheduling approach demands that the nodes cooperate with each other to complete the tasks, and massive factors should be taken into account comprehensively to determine which nodes are redundant, for example, the coverage ratio, nodes’ location information, the number of neighbor nodes, the distance between nodes, etc. The sharing of state information between nodes will increase communication overhead, but the advantage is that the distribution of active nodes in the target area is more balanced This can effectively avoid the problem of “routing holes” in some areas of the network which occurs more frequently with stochastic scheduling methods.
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