Multi-server Collaborative Resource Allocation Approach Based on Game Theory
The storage and computing capabilities of a single mobile edge computing(MEC)server are limited,often unable to meet the demands of heavy computation tasks.Therefore,choosing a collabora-tive approach among multiple MEC nodes to handle migrated tasks becomes an effective measure.To opti-mize resource allocation in multi-server collaboration,the game theory is employed,and a resource alloca-tion problem based on the game theory for multi-server collaboration is further proposed.In response to this problem,servers are categorized as either migrators or collaborators based on their status.With the game theory,the profit models for buyers/migrators and sellers/collaborators are proposed respectively.By seeking flexible allocation of computing resources,an equilibrium between buyer server profits and sell-er server profits is achieved.A dynamic payment bidding mechanism for multi-server computing resources is studied,and an on-demand resource allocation algorithm oriented towards server collaboration is pro-posed.Simulation results show that the proposed algorithm not only meets the computational needs be-tween different servers but also maximizes system performance.
mobile edge computing(MEC)task migrationresource allocationgame theory
NETL
NSTL
万方数据
维普
