Delay-aware Energy Efficient Computation Offloading for Energy Harvesting Enabled Fog Radio Access Networks

Fog computing, also referred to mobile edge computing (MEC), has been recognized as an effective technology to cope with the computation-intensive applications of mobile users. In energy harvesting (EH) enabled fog-computing-based radio access networks (F-RANs), green power can be utilized by fog-computing enabled access points (F-APs) to support the computation offloaded from the mobile users. The utilization of EH will minimize the average grid power consumption. However, intermittency and uneven distribution of the harvested energy may bring in dynamics of the offloading design and affect the delay processing. In this paper, we propose a delay-aware energy efficient computation offloading scheme for F-RANs with hybrid energy supplies. The optimization problem is formulated to minimize the consumption of the non-renewable grid energy under delay and networks constraints. Simulation results show that the proposed offloading scheme can reduce grid power consumption. Besides, the number of computation tasks can be completed within the delay provision.