Wireless Sensor Network Design Methodologies: A Survey Wireless sensor networks (WSNs) have grown considerably in recent years and have a significant potential in different applications including health, environment, and military. Despite their powerful capabilities, the successful development of WSN is still a challenging task. In current realworld WSN deployments, several programming approaches have been proposed, which focus on lowlevel system issues. In order to simplify the design of the WSN and abstract from technical lowlevel details, highlevel approaches have been recognized and several solutions have been proposed. In particular, the modeldriven engineering (MDE) approach is becoming a promising solution. In this paper, we present a survey of existing programming methodologies and modelbased approaches for the development of sensor networks. We recall and classify existing related WSN development approaches. The main objective of our research is to investigate the feasibility and the application of highlevelbased approaches to ease WSN design. We concentrate on a set of criteria to highlight the shortcomings of the relevant approaches. Finally, we present our future directions to cope with the limits of existing solutions.

Mobile wireless sensor network lifetime maximization by using evolutionary computing methods Abstract   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 peopleu0027s lives. Due to the extensive use of WSNs, maximizing the lifetime of WSNs to obtain realtime 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.