Research on Cloudlet Placement in Wireless Metropolitan Area Network

With the development of 5G technology, the Internet of Everything is becoming possible, and the communication traffic of mobile terminals will explode. Meanwhile, the requirements of mobile terminals in terms of fluency and the computing power of applications are also becoming more stringent. However, the computing power of mobile devices is always limited due to their portability. Edge computing can offer a timely manner by offloading tasks of the mobile device to nearby cloudlet. Therefore, the computing tasks can be processed quickly nearby network edge, which can effectively reduce the system delay. Although there are many researches on cloudlet placement technology, how to optimize the cloudlet placement in a given network to improve the performance of mobile applications is still an open issue. This paper mainly proposes a particle swarm optimization algorithm based on genetic algorithm (PSO-GA) to optimize the cloudlet placement in a wireless metropolitan area network, aiming at reducing the average response time for users to process tasks. The simulation results show that the PSO-GA approach performs better in user service quality and reduces system average response time compared with other cloudlet placement schemes.