A Novel Coverage Optimization Strategy for Heterogeneous Wireless Sensor Networks Based on Connectivity and Reliability

Abstract

To overcome the problems of coverage blind areas and coverage redundancy when sensor nodes are deployed randomly in heterogeneous wireless sensor networks (HWSNs). An optimal coverage method for HWSNs based on an improved social spider optimization (SSO) algorithm is proposed, which can reduce the energy consumption and improve the network coverage. First, a mathematical model of HWSN coverage is established, which is a complex combinatorial optimization problem. To improve the global convergence speed of the proposed algorithm, a chaotic initialization method is used to generate the initial population. In addition, the SSO algorithm has a poor convergence speed and search ability, which is enhanced by improving the neighborhood search, global search, and matching radius. In the iterative optimization process, the optimal solution is ultimately obtained by simulating the movement law of the spider colony, i.e., according to the cooperation, mutual attraction, and mating process of female and male spiders. An improved SSO algorithm based on chaos, namely the CSSO algorithm, is proposed to apply to the optimal deployment of sensory nodes in HWSNs. On this basis, the optimization goals are to improve the network coverage and reduce network costs. The optimal deployment plan of nodes is searched via the proposed CSSO algorithm, which effectively prevents coverage blind spots and coverage redundancy in the network.

A Novel Privacy‐Preserving Mobile‐Coverage Scheme Based on Trustworthiness in HWSNs

“…Naveen and Kumar [24] studied the problem of minimizing the cost of network deployment under the constraint of average vacancy, which calculated the density function of the relay nodes to preset the initial position of the nodes and verified the effectiveness of the scheme. In dynamic HWSNs, Cao et al [25] proposed an improved social spider optimization strategy to reduce the network coverage blind spots and redundancy, which simulated the movement law of spiders and cooperation mechanism to achieve the optimal solution of network coverage.…”

A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization

“…However, due to its own software and hardware conditions, the storage, computing, and communication capabilities are weak; especially, the energy is limited and cannot be recharged in real time. Therefore, traditional routing protocols are not suitable for heterogeneous wireless sensor networks [ 2 , 3 ]. How to balance energy consumption and prolong the lifetime of the network has become the focus and difficulty of designing routing protocols for heterogeneous wireless sensor networks [ 4 – 6 ].…”

“…In a cluster, the closer the geographic location of the cluster head is to the center of the cluster, the smaller the average energy consumption of each node in the cluster is and the less energy consumption of the cluster head is [ 3 ]. Therefore, when selecting the cluster head, the remaining energy of the node and its average energy consumption per round are considered at the same time so that the greater the remaining energy and the smaller the average energy consumption per round, more chances the nodes have to become cluster heads.…”

“…erefore, traditional routing protocols are not suitable for heterogeneous wireless sensor networks [2,3]. How to balance energy consumption and prolong the lifetime of the network has become the focus and difficulty of designing routing protocols for heterogeneous wireless sensor networks [4][5][6].…”

“…In a cluster, the closer the geographic location of the cluster head is to the center of the cluster, the smaller the average energy consumption of each node in the cluster is and the less energy consumption of the cluster head is [3].…”