Abstract
Routing requests in industrial wireless sensor networks (IWSNs) are always restricted by QoS. Therefore, finding a high-quality routing path is a key problem. In this paper, a clone adaptive whale optimization algorithm (CAWOA) is designed for reducing the routing energy consumption of IWSNs with QoS constraints, and a novel clone operator is proposed. More importantly, CAWOA innovatively adopts a discrete binary-based routing coding method, which provides strong support for optimal routing schemes. In addition, a novel routing model of IWSNs combined with QoS constraints has been designed, which involves comprehensive consideration of bandwidth, delay, delay jitter, and packet loss rate. Subsequently, in a series of simulations, the proposed algorithm is compared with other heuristic-based routing algorithms, namely, whale optimization algorithm (WOA), simulated annealing (SA), particle swarm optimization (PSO), and genetic algorithm (GA). The simulation results suggest that the CAWOA-based routing algorithm outperforms other methods in terms of routing energy consumption, convergence speed, and optimization ability. Compared with GA, SA, PSO, and WOA under the conditions that the number of nodes is 120, the maximum delay is 120 ms, the maximum delay jitter is 25 ms, the maximum bandwidth is 9 Mbps, and the packet loss rate is 0.02; the energy consumption of CAWOA-based routing is reduced by 12%, 17%, 19%, and 7%, respectively.
Highlights
With the improvement in productivity and the popularization of industrial automation, industrial wireless sensor networks (IWSNs) have become an important tool for monitoring the production environment [1, 2]
(5) clone adaptive whale optimization algorithm (CAWOA) is compared with the genetic algorithm, particle swarm optimization, simulated annealing, and whale optimization algorithm in routing energy consumption, convergence speed, and optimization ability
The purpose of this paper is to reduce the routing energy consumption of IWSNs under the quality of service (QoS) constraints; a novel clone adaptive whale optimization algorithm (CAWOA) is designed
Summary
With the improvement in productivity and the popularization of industrial automation, industrial wireless sensor networks (IWSNs) have become an important tool for monitoring the production environment [1, 2]. There is a large number of wireless sensor nodes in IWSNs, and these nodes are connected to the gateway through the Network Manager (NM), thereby transmitting information to the plant automation network. In IWSNs, there are requirements for low latency, high reliability, and real time. To meet these requirements, reasonable planning and careful design of IWSNs are necessary, and the characteristics of sensor devices and the properties of IWSNs make these tasks more complex and challenging. To reduce the transmission distance of data and improve the quality of service (QoS) of IWSN applications, routing optimization is a commonly used method. There are many literatures on the reasonable planning of IWSN routing, and the effect of routing schemes obtained by different methods and different evaluation criteria is not the same [6]
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