Economical revenue maximization in cache enhanced mobile edge computing
Mobile edge computing (MEC) has emerged as a potential paradigm to enhance the processing capabilities of mobile user equipments (MUEs), while edge caching has become a promising means of alleviating traffic in the backhual. In this paper, we formulate a stochastic optimization problem to maximize the average economical profit of MEC server by jointly optimizing offloading decision and caching decision making, and the allocation of radio, computing, and caching resources in a cellular network, with network stability taken into account. To tackle this problem, we develop an online algorithm referred to as dynamic joint computation offloading, resource allocation, and content caching algorithm (DJORC) based on Lyapunov optimization theory. Specifically, the proposed DJORC only needs the current states of the system, and without requiring any prior-knowledge. By further using 0-1 integer programming and linear programming, the closed-form solution of the formulated problem is obtained. Simulation results are presented to verify the performance of DJORC under different parameter settings, as well as the performance gains obtained by DJORC over other existing schemes.
|Content caching, Economical revenue, Mobile edge computing, Resource allocation, Stochastic optimization|
|2018 IEEE International Conference on Communications, ICC 2018|
|Organisation||School of Information Technology|
Du, J. (Jianbo), Zhao, L. (Liqiang), Feng, J. (Jie), Chu, X. (Xiaoli), & Yu, F.R. (2018). Economical revenue maximization in cache enhanced mobile edge computing. In IEEE International Conference on Communications. doi:10.1109/ICC.2018.8422232