Joint Service Placement and Request Scheduling for Multi-SP Mobile Edge Computing Network

Abstract

Mobile edge computing(MEC), as an emerging computing paradigm, pushes services away from centralized remote cloud to distributed edge servers deployed by multiple service providers(SPs), improving user experience and reducing the communication burden on core network. However, this distributed computing architecture also brings some new challenges to the network. In multi-SP MEC system, a SP prefers to use edge servers deployed by itself instead of others, which not only improves service quality but also reduces processing cost. The service placement and request scheduling strategies directly affect the revenue of SPs. Since the service popularity changes over time and the resources of edge servers are limited, the network system needs to make decisions about service placement and request scheduling dynamically to provide better service for users. Owing to the lack of long-term prior knowledge and involving binary decision variables, how to place services and schedule requests to boost the profit of SPs is a challenging problem. We formally formalize this joint optimization problem and propose an efficient online algorithm. First, we invoke Lyapunov optimization technology to convert the long-term optimization problem into a series of subproblems, then a dual-decomposition algorithm is utilized to solve the subproblem. Experimental results show that the algorithm proposed in this paper achieves nearly optimal performance, and it raises 25% and 70% profit compared to greedy and Top-K algorithms, respectively.