Reliable Collaboration Mechanism of Side End Resources for Discrete Services of Virtual Power Plants

Abstract

AbstractWith the substantial increase in the number of participants in virtual power plants and the in-depth popularization of power Internet of Things, a large number of IoT terminals will be deployed on the internal and external networks of the system. Service terminals are connected to the network in different ways, and transmitted to the service system and cloud platform via the backbone network. In the process of data transmission and processing, the communication, computing, and storage resources required by the service terminal are highly heterogeneous and different. The bearing relationship between services and resources, and the connection relationship between resources in different network segments are complex, and it is impossible to Realize the integrated management of end-to-end resources. In response to the above problems, this paper proposes a MEC server collaborative computing model, which combines the computing capabilities of the service terminal itself and edge nodes to coordinate the offload rate between different devices to minimize the system's delay and energy consumption, and proposes A load balancing model that transfers tasks between overloaded and lightly loaded edge nodes to maximize system operating efficiency. Through simulation experiments, the method proposed in this paper effectively reduces the service delay and system energy consumption, and improves the reliability of the system.KeywordsMobile edge computingComputation offloadingMachine learningArtificial intelligenceVirtual power plant