Abstract
Wireless sensor network topology optimization is a highly important issue, and topology control through node selection can improve the efficiency of data forwarding, while saving energy and prolonging lifetime of the network. To address the problem of connecting a wireless sensor network to the Internet in cyber-physical systems, here we propose a geometric gateway deployment based on a competitive swarm optimizer algorithm. The particle swarm optimization (PSO) algorithm has a continuous search feature in the solution space, which makes it suitable for finding the geometric center of gateway deployment; however, its search mechanism is limited to the individual optimum (pbest) and the population optimum (gbest); thus, it easily falls into local optima. In order to improve the particle search mechanism and enhance the search efficiency of the algorithm, we introduce a new competitive swarm optimizer (CSO) algorithm. The CSO search algorithm is based on an inter-particle competition mechanism and can effectively avoid trapping of the population falling into a local optimum. With the improvement of an adaptive opposition-based search and its ability to dynamically parameter adjustments, this algorithm can maintain the diversity of the entire swarm to solve geometric K-center gateway deployment problems. The simulation results show that this CSO algorithm has a good global explorative ability as well as convergence speed and can improve the network quality of service (QoS) level of cyber-physical systems by obtaining a minimum network coverage radius. We also find that the CSO algorithm is more stable, robust and effective in solving the problem of geometric gateway deployment as compared to the PSO or Kmedoids algorithms.
Highlights
Cyber-Physical Systems (CPSs) have great influence on the way we observe and change the world
In a CPS, information regarding the monitoring area within a local area is acquired using a large number of micro-sensor nodes and a multi-hop, self-organizing wireless sensor network is created through wireless communication, and transport delay, data security are important topics [3,4,5]
In the study described in reference [23], the individual optimum pbest and population optimum gbest in the particle swarm optimization (PSO) algorithm were eliminated, and a competition mechanism was introduced into the particle swarm, which essentially changed the particle search mechanism: in short, a competition-based competitive swarm optimizer (CSO) algorithm was proposed in an effort to effectively avoid precocious particles and local optimum trapping, as well as to lower the computation cost
Summary
Cyber-Physical Systems (CPSs) have great influence on the way we observe and change the world. There are two types of WMN gateway deployments [6]: one is to select K network nodes from the existing network nodes as the gateways, referred to as the vertex K-center problem, and the method is searching for local optimal in a discrete space. The other is to choose K positions from the plane in which the node is located to deploy gateway nodes, referred to as the geometric K-center problem This method is searching for a global optimal in a continuous space. In the study described in reference [23], the individual optimum pbest and population optimum gbest in the PSO algorithm were eliminated, and a competition mechanism was introduced into the particle swarm, which essentially changed the particle search mechanism: in short, a competition-based CSO (competitive swarm optimizer) algorithm was proposed in an effort to effectively avoid precocious particles and local optimum trapping, as well as to lower the computation cost. This paper adopts a novel CSO algorithm in order to solve the problem of WMN gateway deployment
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