Robust Task Offloading and Resource Allocation in Mobile Edge Computing With Uncertain Distribution of Computation Burden

Abstract

In mobile edge computing (MEC) supporting multiple mobile users (MUs), it is essential to optimize the offloading policy and communication and computation resource allocation. A main challenge is that the computation burden of a computation task may be random and even with uncertain probabilistic distribution. To address this challenge, we investigate a multiple-MU MEC system with random computation burden. For the random computation burden of an MU, only the mean and variance are known, but its distribution is unknown. Robustness is provided such that computation outage probabilities (due to uncertain distribution of computation burden) are bounded by a predefined threshold. We minimize the weighted sum of the MUs’ energy consumption. The formulated optimization problem is non-deterministic and non-convex, and thus, is hard to solve. To deal with the challenge, we transform the formulated problem into a deterministic and convex problem by applying the Chebyshev-Cantelli inequality and some mathematical manipulations. We further decompose the convex problem to a lower-level and an upper-level problem. Low-complexity algorithms are developed for the lower-level and upper-level problems. The overall complexity of our proposed method is linear with the number of MUs.