Relay transmission under mobile edge computing in energy-limited networks with real-time constraints

For energy-limited networks with real-time constraints, long-distance transmission, complex calculations, and limited delay are problems to be faced in service applications. The cloud-based mobile edge computing framework is proposed in energy-limited networks to solve these problems. Under certain power and delay conditions, source node and destination node in adjacent cells, respectively, can select the appropriate relay node to complete the communication process. The mobile edge computing brings a novel idea for the application of auto-regressive and moving average model and further improves transmission efficiency and reduces transmission delay. Historical energy information of potential relay nodes can be predicted through auto-regressive and moving average model in edge computing server. Then, source node selects appropriate relay node by the proposed relay selection algorithm. Power objective function with signal-to-noise ratio that satisfies the limited delay is formulated to optimize the power allocation of nodes in terms of reducing energy consumption. The results show that our proposed relay selection algorithm under mobile edge computing architecture in energy-limited networks with real-time constraints could effectively improve the performance of networks on energy consumption and delay.