Due to the continuous development and progress of wireless communication technology and sensor network technology, wireless sensor networks (WSNs) have gradually become an attractive technology that facilitates people’s lives. Due to the extensive use of WSNs, maximizing the lifetime of WSNs to obtain real-time and effective information has become a critical concern. This paper studies the life of mobile wireless sensor networks (MWSNs). MWSNs are a special type of WSN in that the sensor nodes are movable within a certain area. A system model is developed to prolong the network lifetime of MWSNs. This paper uses five evolutionary computing (EC) algorithms to develop the MWSN lifetime optimization model. Numerical simulations are performed to study the advantages and disadvantages of the five algorithms for solving the model. The comparison and discussion can provide advice for using EC algorithms to solve MWSN lifetime maximization problems.

Introduction

Due to the continuous development and progress of wireless communication technology, network technology, microprocessor technology and sensor network technology, WSNs have gradually become an attractive technology that facilitates people’s lives [1]-[5]. Moreover, WSNs are a new way to acquire information through real-time monitoring of the environment. Because of their unique way of obtaining information, WSNs are widely used in various fields, such as military defense, biological medicine, smart home technology, industry and agriculture [2], [3]. As the capacity of battery of nodes is limited, the operational longevity of nodes is critical. The longevity of a WSN directly affects the overall performance of the network [4]. MWSNs are a special distributed network of many deployed sensor nodes that are movable within a monitoring area. MWSNs form a selforganizing network through wireless communication technology [5]. Unlike in static WSNs, the mobility of sensors or sink nodes in MWSNs causes network topology to change dynamically. Thus, compared to when designing static WSNs, more issues have to be addressed when designing mobile networks [4]. Recently, there have been studies on the lifetime of MWSNs. [6] studied maximizing the lifetime of MWSNs that contained mobile sink nodes. In [7], the exploration and exploitation trade-off was studied, and different methods were compared.