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

Routing requests in industrial wireless sensor networks (IWSNs) are always restricted by QoS. Therefore, finding a high-quality routing path is key problem. In this paper, clone adaptive whale optimization algorithm (CAWOA) designed for reducing the energy consumption of IWSNs with QoS constraints, and novel operator proposed. More importantly, CAWOA innovatively adopts discrete binary-based coding method, which provides strong support optimal schemes. addition, model combined constraints has been designed, involves comprehensive consideration bandwidth, delay, delay jitter, packet loss rate. Subsequently, series simulations, proposed compared other heuristic-based algorithms, namely, (WOA), simulated annealing (SA), particle swarm (PSO), genetic (GA). The simulation results suggest that CAWOA-based outperforms methods terms consumption, convergence speed, ability. Compared GA, SA, PSO, WOA under conditions number nodes 120, maximum 120 ms, jitter 25 bandwidth 9 Mbps, rate 0.02; reduced 12%, 17%, 19%, 7%, respectively.