Collaborative Service Placement for Maximizing the Profit in Mobile Edge Computing

Mobile edge computing (MEC) is a promising cloud computing convergence paradigm that improves the quality of services and reduces the traffic load on the core network. By deploying base stations (BSs) endowed with computing resources on the edge of network, MEC system can response to the user requests more efficiently and faster than the traditional cloud center which is far away from the end users. However, limited by the capacity of the computing resource and radio resource on a BS, only a few services can be placed on each BS, and the number of users that each BS can serve in each time slot is also limited. Moreover, in a densely deployed network, service placement decisions of adjacent BSs are influenced by each other, because their communication ranges are overlapped. Thus, service provider (SP) who deploys the BSs on the MEC system has to coordinate service placement among BSs so as to maximize its profit. Moreover, there are different kinds of users on the MEC system, some of them would like to pay more for higher priority to acquire computing resource. Therefore, SPs need to design a pricing method to distinguish users' priorities to get higher profit. In this paper, we will design a novel method to coordinate service placement among BSs and propose a pricing method that considering the difference of users. Our service placement method can theoretically achieve optimal result in single BS. And the simulation results also indicate that our service placement method achieve better performance in the cluster than the existing methods.