Low-latency AP handover protocol and heterogeneous resource scheduling in SDN-enabled edge computing

As mobile devices are widely used and various applications emerge, users have higher demands on data rates and computing power. Software Defined Network (SDN) can configure and manage various devices in the network through a centralized control controller, making the network more flexible. In an SDN-enabled edge computing environment, dense multiple access devices make mobile devices handover frequently, and mobile devices handover between different access points becomes an inevitable problem. To address this problem, we propose an Access Point (AP) handover strategy based on the signal strength and traffic load. The scheme uses the global view and centralized control capability of the SDN controller to obtain, manage, and analyze information, then calculate the weights and compare them, and finally develop the handover policy. On the other hand, to improve system resource utilization and meet the performance demands of different applications, MEC systems need to allocate computing and communication resources appropriately to keep users' Quality-of-Service (QoS) experience. We propose a joint optimization strategy for computing and communication resources based on the Lagrange multiplier method. The policy calculates and analyzes the task execution latency and energy consumption of edge servers and local terminals, and develops an optimization scheme for sub-channel allocation and resource allocation. It aims to reduce latency and energy consumption as much as possible. The results of the experiments in this paper illustrate that the proposed AP handover scheme which is on the basis of received signal strength indicator (RSSI) and traffic load can effectively improve the task completion time and energy consumption performance. The proposed joint optimization strategy of computing and communication resources based on the Lagrange multiplier method can effectively improve energy consumption and delay performance.