Research On Offloading And Security Protection Based On Edge Node Collaboration In Power Internet Of Things

With the continuous development of the power Internet of Things(PIoT),the degree of intelligence and modernization of power system equipment has been continuously improved,realizing the interconnection of devices,information sharing,and intelligent control in the PIoT.However,as terminal services continue to expand,the data in the PIoT is increasing day by day,making it difficult for traditional cloud computing models to process data in the network in a timely manner.Multi-access edge computing(MEC)technology can greatly reduce communication latency and bandwidth consumption in the network by deploying computing and storage resources to the edge of the network.The introduction of MEC in the PIoT has made network data transmission more efficient and business response more rapid.However,the process of combining MEC with the PIoT also faces some challenges.First,edge nodes consume a lot of energy in the process of computing,caching,and forwarding data,and how to reduce node energy consumption while ensuring system performance has become a critical issue.Secondly,the introduction of MEC makes resource allocation in the PIoT more flexible,so designing reasonable offloading schemes to meet terminal requirements is also a key issue.Finally,the introduction of MEC has made the PIoT involve more information transmission and data processing,so strengthening measures to prevent data security and privacy protection is also a key challenge.In summary,this thesis studies how to integrate cloud computing and edge computing resources to improve the speed of data processing,reduce node energy consumption,and ensure network security in the PIoT.The main work is as follows:Firstly,to address the current problem of uneven energy consumption in the PloT and the difficulty of a single edge node in processing a large number of concurrent businesses,a green energy-saving offloading strategy based on multi-edge node cooperation is proposed.Firstly,a model is established for the time delay and energy consumption required for edge nodes to compute terminal tasks under a cooperative mode.Secondly,a clustering algorithm and an edge node cooperative offloading algorithm are designed with the optimization objectives of reducing node energy consumption and task offloading delay.The clustering algorithm maintains energy balance among nodes in the network,and the edge node cooperative offloading algorithm is combined to reduce task offloading delay.Simulation results show that the proposed green energy-saving offloading strategy based on multi-edge node cooperation successfully reduces edge node energy consumption while also reducing the offloading delay of terminal tasks.Secondly,to address the problem that edge nodes in the PIoT are vulnerable to attacks,which can affect the normal operation of the network,an abnormal node detection strategy based on multi-edge node cooperation is proposed.Firstly,an abnormal node detection algorithm is proposed based on edge node cooperation.The algorithm updates the trust values of each node in real-time through communication interactions between nodes,and quickly detects abnormal nodes in the network based on trust values.Secondly,the abnormal node detection smart contract proposed in this thesis is implemented based on the Hyperledger Fabric blockchain platform.Experimental results show that the designed abnormal node detection smart contract accurately detects abnormal nodes in the network and successfully synchronizes the results to all nodes,effectively ensuring the operation security of the PIoT.