A Novel QoS Routing Energy Consumption Optimization Method Based on Clone Adaptive Whale Optimization Algorithm in IWSNs

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.

Sensors, Signal, and Artificial Intelligent Processing

“…Through simulation experiments, this improved node energy usage efficiency. J. Xiao et al [7] have designed an optimization algorithm with adaptive whale strategy which decreases the energy consumption with QoS. The simulation results suggest that the CAWOA-based routing algorithm got better performance in terms of routing energy consumption, convergence speed, and optimization ability.…”

Intrusion Detection System and Fuzzy Ant Colony Optimization based Secured Routing in Wireless Sensor Networks

“…The proposed secured Fuzzy ACO based routing algorithm provides better performance than the existing QoS routing protocols, which also try to boost QoS via improving packet delivery ratio, decreasing delay, and lowering energy consumption [22], [23]. In this proposed scheme, the quality metrics are targeted while retaining security and latency issues in the routing process by cluster head rotation, not only based on distance, energy and mobility metrics but also using the security mechanisms.…”