Decentralized Computation Offloading in Mobile Edge Computing Systems

Existing works on mobile edge computing (MEC) which operate under multi-user and multi-server scenarios often assume centralized computation offloading. This paper proposes a decentralized computation offloading scheme where a user does not require information about other users and about the MEC network (e.g., number of servers, network topology). Under the proposed computation offloading scheme, a user infers the transmission delay from the link rate assigned by its associated base station (BS). Further, each user privately deploys a moving average model to estimate the network delay after transmission. Using such information and its own information (i.e., local computing resource and energy availability), the user decides whether to offload its task to the MEC network via the BS. In case, a user decides to offload its task then the task deadline is not revealed to the MEC network to maintain fairness. Thereafter, the central controller of the MEC network performs optimal task allocation and notification of the computation results to the users. The impact of various user-parameters such as task generation probability, deadline, task size and processing density on the users and the MEC network are analyzed using extensive simulations.