When the smart grid phasor measurement equipment competes for limited network communication resources, the data packets will be delayed or lost due to uneven resource allocation, which will affect the accuracy of power system state estimation. To solve this problem, a Sampling Awareness Weighted Round Robin (SAWRR) scheduling algorithm was proposed. Firstly, according to the characteristics of Phasor Measurement Unit (PMU) sampling frequency and packet size, a weight definition method based on mean square deviation of PMU traffic flow was proposed. Secondly, the corresponding iterative loop scheduling algorithm was designed for PMU sampling awareness. Finally, the algorithm was applied to the PMU sampling transmission model. The proposed algorithm was able to adaptively sense the sampling changes of PMU and adjust the transmission of data packets in time. The simulation results show that compared with original weighted round robin scheduling algorithm, SAWRR algorithm reduces the scheduling delay of PMU sampling data packet by 95%, halves the packet loss rate and increases the throughput by two times. Applying SAWRR algorithm to PMU data transmission is beneficial to ensure the stability of smart grid.

In multicast routing comunication of smart grid, concerning the long communication delay of multicast tree when transmitting control messages to high-power load device, which caused by only considering delay constraint without considering the demand of smart grid, a new multicast tree construction method that considered load and comunication delay at the same time was proposed, namely multicast routing algorithm based on Demand Response (DR) capability constraint. Firstly, a complete graph satisfying the constraint was generated according to the grid network topology. Then, a lower-cost multicast tree was constructed by using the Prim algorithm. Finally, the multicast tree was restored to the original network. The simulation results show that the proposed algorithm can effectively reduce the demand response delay of high-power load devices, and can significantly reduce the power frequency deviation compared with the multicast routing algorithm only considering delay constraint. This algorithm can actually improve the real-time demand response in the smart grid and stabilize the grid frequency.

With the rapid growth of bioinformatics (protein structure analysis, genome identification), social networks (links between entities), Web analysis (interlinkage structure analysis, content mining and Web log retrieval), as well as the complex structure of text information retrievals, mining graph data has become a hot research field in recent years. Some traditional data mining algorithms have been gradually extended to graph data, such as clustering, classification, and frequent pattern mining. In this paper, the authors presented several state-of-art mainstream techniques for mining graph data, and gave a comprehensive summary of their characteristics, practical significance, as well as real-life applications on mining graph data. Finally, several research directions on graph data, and particularly, uncertain graph data were pointed out.