Low-Latency Oriented Resource Allocation for MEC-Assisted Adaptive Bitrate Video Streaming

Abstract

This paper focuses on low-latency transmissions for mobile edge computing (MEC)-assisted adaptive bitrate (ABR) video streaming. With the aim to realize minimum video service latency, an optimization problem is formulated by jointly designing caching, computing and power allocation, subject to diverse video version downloading rate requirements and the limited resources of MEC servers. The formulated optimization problem turns out to be a mixed integer nonlinear programming (MINLP) problem. To solve the problem and satisfy the low-latency service requirement of ABR video streaming, a low-complexity two-step iterative algorithm is proposed by decomposing the MINLP problem into two subproblems, a joint caching and computing subproblem and a power allocation subproblem. Due to the highly coupled nature of the caching and computing, the first subproblem is an integer nonlinear programming (INLP) problem. To solve it efficiently, the INLP problem is equivalently transformed into an integer linear programming (ILP) problem, which is thereafter solved by MATLAB intlinprog function. The second subproblem is a convex problem and is solved by low-complexity power allocation (LCPA) algorithm. Intensive simulation results show that the proposed algorithm converges in a very short time, and can significantly reduce the average latency compared to the state-of-the-art baselines.