Joint Shareability and Interference for Multiple Edge Application Deployment in Mobile Edge Computing Environment

Mobile edge computing (MEC), as an emerging computing paradigm, allows app vendors to deploy their mobile and/or IoT applications on edge servers to deliver low-latency services to their app users. However, when an edge server needs to serve excessive app users concurrently, severe interference is incurred, which immediately reduces app users’ achievable data rates and consequently impacts their perceived service quality. This is a major challenge to the app vendor’s attempt to minimize the edge resources required for serving its app users with satisfactory service quality. To tackle this challenge, in this paper, we present and formulate this multiple edge application deployment (MEAD) problem in the MEC environment, aiming to maximize app users’ overall service quality at minimum deployment cost, considering application shareability and communication interference. We prove that the MEAD problem is NP-hard. Then, we propose a heuristic approach, namely deployment-priority greedy via divide-and-conquer strategy (DPG-D&C), to solve the MEAD problem effectively and efficiently. We evaluate our approach extensively by using a widely-used real-world dataset. The experimental results show that DPG-D&C significantly outperforms state-of-the-art approaches.