Joint Coverage and Latency for Data-intensive Application Deployment in Mobile Edge Computing Environment (S)

Mobile edge computing (MEC) is an emerging computing paradigm where application vendors deploy applications at the edge of the network by configuring computing and storage resources, to achieve low latency, high bandwidth, and exceptional user experience.However, end-users are extremely sensitive to the response latency of data-intensive applications, which is one of the main challenges in MEC.Therefore, application vendors must ensure that data-intensive applications deployed on edge servers have the lowest possible response latency, thereby maximizing the total Quality of Experience (QoE) for end-users.To address this challenge, this paper jointly considers user coverage and response latency as QoE, aiming to obtain application deployment strategy within the constraints of deployment budget , while maximizing the total QoE.We propose the Data-Intensive Application Deployment (DIAD) problem and model it as a constrained optimization problem.By taking QoE into account, a greedy heuristic strategy (DIAD-G) is proposed to effectively tackle the DIAD problem.Extensive experimental evaluations are conducted on real-world datasets, comparing DIAD-G with five representative methods.The experimental results demonstrate the effectiveness of this method, with total QoE for end-users significantly surpassing other methods and achieving the best performance.