Distributed Online Resource Scheduling for Mobile Edge Servers

Due to the flexibility and scalability, the increasing number of mobile edge computing applications involves Mobile Edge Servers (MES). MES introduces the new challenge of online resource scheduling to serve different requests under limited energy to offer similar functionalities of the immobile edge servers. The previous studies consider the case of the identical server, which has poor scalability and is hard to apply to real-world applications. This work proposes a novel model named the distributed k-server problem that formulates the MES resource scheduling to address the heterogeneity issues in both servers and requests. We design an algorithm named DWFA based on the efficient network flow-based Work Function Algorithm (WFA) to the classic k-server problem as an immediate solution to the proposed problem. DWFA inher-its the competitiveness of WFA but has high computational complexity. To further increase scalability via the computing power of MES, we parallelise DWFA to design a distributed algorithm named FD-WFA as a distributed execution of DWFA, which significantly reduces the computational complexity and increases the practicality. Extensive simulations have been con-ducted to verify the theoretical results and show the advantages of FD-WFA over the benchmarks.