Abstract

In mobile wireless sensor networks (MWSNs), methods of traditional data collection only consider increasing the amount of data acquisition or reducing the energy consumption of the whole network. In the process of data collection, how to maximize the data, the shortest mobile path and the reliability of the network is an optimization problem. In order to solve the above problems, this paper proposes an algorithm of reliable data collection for mobile Sink based on improved artificial bee colony optimization. It combines the selection of cluster node, the transmission path from sensor node to cluster node, and the path optimization of mobile Sink. It provides a typical model system of data collection in MWSNs, including the method of network energy consumption in the process of data collection. An improved artificial bee colony algorithm is proposed by using the initialization method of reverse learning, and introducing the search equation inspired by differential evolution algorithm. It overcomes the shortcomings of artificial bee colony algorithm with premature convergence and poor ability to search in late evolution, which satisfying the conditions of the shortest time consumption and the shortest path length of the mobile Sink. On the one hand, it aims to improve data collection and find the shortest traversal path of the mobile Sink. On the other hand, it is necessary to improve the network efficiency and reliability by considering network energy consumption and network delay. By the improved artificial bee colony algorithm, it gets the shortest path planning of mobile Sink for searching each cluster node. The sensor node transmits data to the nearest cluster node by multi hop routing with temporarily saving, and then it is sent to the mobile Sink. The proposed algorithm can effectively reduce the amount of sensor nodes transmitted to mobile sink with improving the efficiency of data collection. Compared with other methods, it can reduce network energy consumption and increase energy consumption balance and network reliability, so as to prolong network lifetime.

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