OPECE: Optimal Placement of Edge Servers in Cloud Environment

Cloud computing offloads user tasks to remote cloud servers, which can effectively enhance the user’s network experience, but in recent years, as the number of offloaded tasks increases and users’ real-time requirements improve, cloud services are becoming increasingly challenging to meet users’ needs. Edge computing deploys multiple edge servers around the users. The shorter distance from users can significantly reduce the transmission time of task data and avoid unpredictable network latency, which is especially suitable for normal users whose tasks are mainly data-intensive tasks. However, the large variability in the density of users in different areas and the type of computing tasks (i.e., compute-intensive and data-intensive) in the same area leads to the challenge of optimally deploying multiple edge servers. To address this challenge, we design a method named optimal placement of edge servers in the cloud environment (OPECE). First, this optimal placement problem is modeled as a constrained multi-objective optimization model with task time and server utilization as the two optimization objectives. Then, this multi-objective optimization model is optimized using the Non-dominated Sorting Differential Evolution (NSDE) algorithm. Finally, the effectiveness and superiority of OPECE are demonstrated by comparing it with the currently used methods.