Wireless Sensor Network Coverage Optimization Based on Fruit Fly Algorithm

Abstract

Abstract-To solve the defect of traditional node deployment strategy, the improved fruit fly algorithm was combined with wireless sensor network. The optimization of network coverage was implemented. Based on a new type of intelligent algorithm, the change step of fruit fly optimization algorithm (CSFOA) was proposed. At the same time, the mathematical modeling of two network models was carried out respectively. The grid coverage model was used. The network coverage and redundancy were transformed into corresponding mathematical variables by means of grid partition. Among them, the maximum effective radius of sensor nodes was fixed in mobile node wireless sensor network. The location of nodes was randomly cast. The location of sensor nodes was placed in fixed position nodes. The effective radius of nodes can be changed dynamically. Finally, combined with the corresponding network model, the improved algorithm was applied to wireless sensor network. The combination of the optimal solution of the node position and the perceptual radius was found through the algorithm. The maximum network coverage was achieved. The two models were simulated and verified. The results showed that the improved algorithm was effective and superior to the coverage optimization of wireless sensor networks. Keywords-wireless sensor networks; coverage optimization; sensor nodes IntroductionIn recent years, the Internet of Things, cloud computing and big data have developed rapidly. The Internet of things is the key technology of the information interaction between the future reality and the virtual. It is also the key research direction to realize the "information society". The Internet of Things mainly has three communication sensing technologies, namely, intelligent sensing, identification technology and pervasive computing. Internet of Things technology is widely used in information processing, in order to achieve a complete integration of the physical world and the information world. As a core technology of Internet of Things, Wireless Sensor Network (WSN) is attracting much attention. The wireless sensor has three functions, such as information collection, processing and transmission. They correspond to the three modern basic information technologies, namely, sensor technology, computer 58

An Improved Grey Wolf Optimizer with Multi-Strategies Coverage in Wireless Sensor Networks

“…It can be found in the literature [5][6][7] that they all study swarm intelligence algorithms improve the performance of WSNs, from aspects such as node redundancy and coverage of homogeneous WSNs. Similar research includes the improved sticky algorithm proposed by Wei et al, simplified slime mold algorithm (SSMA) [8], the improved fruit fly optimization algorithm (change step of fruit fly optimization algorithm (CSFOA)) proposed by Song et al [9]. Some researchers aim to optimize the coverage of heterogeneous WSNs and study swarm intelligence algorithms that reduce node redundancy and improve coverage.…”

Environmental Health Oriented Optimal Temperature Control for Refrigeration Systems Based on a Fruit Fly Intelligent Algorithm

“…The fruit fly optimization algorithm (FOA), proposed by Pan in 2011 [16], is a kind of stochastic optimization algorithm that selects a result with certain rules. With the merits of fast convergence and easy programmability, it is widely used to solve optimization problems [17,18,19]. To this end, a fruit fly optimization algorithm is applied to tune and optimize the parameters of a refrigeration controller in this paper.…”