【摘要】 为了解决物联网感知层无线传感器网络(WSNs)的节点调度问题,使网络能量总消耗最小化、网络生存周期最大化和网络性能最优化,该文将问题转化为一个约束条件下的组合优化问题,利用元启发式蝙蝠算法在求解复杂组合优化问题中参数设置少、快速收敛等优点,提出一种非均匀条件下的基于蝙蝠算法的WSNs节点调度算法。仿真对比和结果分析表明,在无线传感器网络节点调度过程中,蝙蝠算法效率最高,能耗最低,时延最短,可靠性好。与人工免疫算法和粒子群算法相比,该方法的网络节点平均能耗分别降低10.8%和3.5%。更多还原

【Abstract】 For making the better node scheduling strategy of wireless sensor networks( WSNs) of the perception layer internet of things to minimize the energy consumption,maximize the network lifetime and optimize the network performance,the problem is transformed into a combinatorial optimization problem with constraints. A new WSNs node scheduling algorithm under the non-uniform conditions is proposed here based on the meta-heuristic bat algorithm which has the low parameter setting and the fast convergence when solving complex combinatorial optimization problems. The comparative analysis of simulation experiment shows that,the proposed algorithm is the most efficient,and it has the lowest energy consumption,the shortest time delay and the best reliability in the wireless sensor network node scheduling. Compared with the artificial immune algorithm and the particle swarm algorithm,the average energy consumption of the network nodes is reduced by 10. 8% and 3. 5%,respectively.更多还原