Joint Optimization of Sensing-Communication-Computing Resource Allocation for Transparent and Secure Control in Distribution Networks

Transparent and secure control of distribution network realizes the comprehensive and real-time supervision of its operation status by information intelligence. Delay and privacy security are important indicators of transparent and secure control performance. The joint guarantee of them is achieved through the joint optimization of communication (channel), sensing (sensing data encryption level), and computing (computing resource) resources, which suffers from the contradiction between delay and security, high optimization complexity, and resource competition. Therefore, we propose a joint optimization algorithm of sensing-communication-computing resource allocation for transparent and secure control of distribution networks. We first formulate the joint optimization problem of privacy entropy and end-to-end queuing delay under the long-term transparent control constraint. Second, the long-term constraint is decoupled from the short-term decision based on Lyapunov optimization. Then, a joint optimization algorithm for channel and data encryption level selection based on two-layer collaborative combinatorial matching is proposed. It constructs the preference lists of devices for the combination options through device-device collaboration, and develops service priority and privacy entropy-sensitive price-rising strategy through edge-device collaboration to avoid resource competition. Finally, the computing resource allocation is optimized through Lagrange optimization. Simulation results show that the proposed algorithm has excellent end-to-end queuing delay and privacy entropy performances.