Mobile Sink-Based Path Optimization Strategy in Wireless Sensor Networks Using Artificial Bee Colony Algorithm

In traditional static wireless sensor networks (WSNs), the unbalanced communication overhead in different regions will result in premature death of some monitoring nodes. The introduction of mobile sink in WSNs can not only balance the node traffic load, but also obtain even energy consumption of nodes, thus effectively avoiding the “hot spot” problem and prolonging the network lifetime. However, the mobility of the sink will lead to frequent changes in the aspect of network topology, which can aggravate the overhead of the node’s reorganization in hierarchical WSNs. Therefore, it is essential to obtain the optimal trajectory design of the mobile sink so as to improve the ability of data gathering. In this paper, a mobile sink-based path optimization strategy in WSNs using artificial bee colony algorithm is proposed. First, the problem of overall energy consumption in the network can be transformed into the minimization of the total hops between all subnodes and the rendezvous points of the mobile sink. The objective function and the constraint criterion should be established. Second, an improved artificial bee colony algorithm is proposed to solve the problem. On the one hand, the cumulative factor is introduced to the position update of the employed bee stage to speed up the convergence of the algorithm. On the other hand, the Cauchy mutation operator is presented to increase the diversity of the feasible solution and enhance the global search ability of the algorithm. The simulation results show that the proposed algorithm is better than the traditional methods in the aspects of energy efficiency and the real-time performance of data collection.