Performance and Stability of Application Placement in Mobile Edge Computing System

We investigate the design of a Mobile Edge Computing (MEC) system in which self-interested users minimize their own costs and a MEC service provider attempts to maximize its revenue. We introduce a third-party platform that works as an intermediary to facilitate the service transaction between the users and the provider. The platform collects MEC server information and discloses that to users; users rely on their user agent apps to place their application jobs on edge computing servers during their stay in the system. We propose a dynamic programming algorithm for a user to minimize his/her own cost and an efficient heuristic algorithm for the platform to minimize the cost of all users by optimally scheduling the admission of users' jobs and still allowing users to make independent optimal decisions. We have demonstrated the effectiveness of these algorithms via extensive simulations based on an empirical Google cloud dataset and a Web file dataset. Furthermore we model the interaction between users and a provider as a game, referred to as User-Provider Game. We find that when the provider always attempts to maximize its own revenue by adjusting the prices of edge servers, the interaction will lead to an unstable system with severe oscillation and degraded performance. To address the issue, we propose a better response algorithm for the provider which stabilizes the system and results in high performance. This paper sheds light on this important area of MEC, and points a promising direction to further investigate and design an effective MEC system of independent self-optimizing mobile users.