Journal of Network Intelligence c 2017 ISSN 2414-8105(Online) Taiwan Ubiquitous Information Volume 2, Number 3, August 2017 An Optimal Deployment Wireless Sensor Network Based on Compact Differential Evolution Trong-The Nguyen, Thi-Kien Dao, Trinh-Dong Nguyen, Truong-Giang Ngo Department of Information Technology, Haiphong Private University, No. 35 Danlap Rd.,Hai-Phong, Vietnam vnthe@hpu.edu.vn, jvnkien@gmail.com, dongnt@hpu.edu.vn, giangnt@hpu.edu.vn Shu-Chuan Chu School of Computer Science, Engineering and Mathematics Flinders University, Australia jan.chu@flinders.edu.au Received March 2017; revised September 2017 Abstract. This paper proposes a compact Differential Evolution (namely cED) for op- timizing the deployment Wireless Sensor Network (WSN). The optimal scheme for de- ploying WSN should be a light and efficient algorithm because WSN limitations of size, memory, battery power, and computation. The proposed cDE uses a probabilistic model to generate candidate solutions for locating the promising area in search space. The solution of the population-based algorithm is expressed its distributed probability and is responding the order-one behavior for DE. So that cDE is a light and efficient tool that is suitable for deploying WSN. Simulation results are compared with the original and the other methods in the literature e.g. LEACH, LEACH-C, and HEED shows that the proposed method is the better performance regarding residual energy, nodes alive, and received items to save the energy of nodes. Keywords: Compact differential evolution, Deployment Wireless sensor network, Op- timization. 1. Introduction. Wireless sensor networks (WSN) is an emerging, promising technol- ogy, and it is an essential infrastructure of Internet of Things (IoT) to collect relevant information in the target environment [1][2]. The applications of WSN have widely ap- plied in a variety of fields of industry, traffic control, healthcare, and home automation [3][4]. However, the sensor nodes are limited on computation capability and storage ca- pacity of computing unit, in communication range and radio quality of communication unit, in sensing coverage and accuracy of sensing unit, and in the available energy of power units [5]. Because the limited memory and the power constraints, WSNs fully functional network must be maintained and stable by the good design system employment. The problems arise from the insufficient memory of computational devices to store various candidate solutions for optimization applications. The required solutions to a complex optimization problem even though in limited hardware conditions have arisen from some applications [6]. The compact algorithm is a promising answer to these challenges [7]. An efficient com- promise is used to present solutions of search space for the advantages of population-based 263