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Mobile edge computing (MEC), as a novel computing paradigm, promises dramatic reduction in latency and energy consumption by offloading computation-intensive tasks to edge clouds in close proximity to mobile users. However, compared with conventional mobile cloud computing (MCC), it has finite computation capacity, especially under the scenario of multi-user offloading. Thus, how to optimize mobile energy consumption and utilize computational resources effectively have being challenged MEC design. In this paper, we consider a multi-user MEC system design, where the multiple mobile devices ask for computation offloading to a MEC server according to the system state. We formulate the computation offloading as a stochastic dynamic programming (SDP) problem, aiming at minimizing the long-term cumulative system cost. To achieve this goal, we propose an approximate dynamic programming (ADP …