Joint Power Control and Computing Association for Delay Minimization in Edge Computing-Enabled Smart Grid Networks

Edge computing (EC) has a promising advantage by leveraging the computation resource closing to the sensors and devices to reduce the delay of the smart grids (SGs). However, it is challengeable to balance the communication and computation for the relatively limited resource of edge nodes. Firstly, a general delay model for the multiple edge computing units is built to characterize the influence of the computing association. Secondly, a joint power control and computing association optimization problem is formulated to minimize the system delay in the uplink EC-enabled SG network. Although the problem is non-convex due to the coupling of the transmit power and the computing association, we slack the integer constraints and propose a suboptimal scheme based on the fractional programming to decouple the transmit power and the computing association. Finally, some simulation results show that the EC-enabled SG system is always in the communication-limited region when the packet size is small and becomes computation-limited with the increasing of the packet size. In addition, the proposed scheme can achieve performance gain up to 21% compared to the benchmark scheme.