Aiming at the security threats and single point of failure of the agent in mimic cloud systems， a high-available mimic cloud agent with active-standby monitoring was proposed. Firstly， an active-standby monitoring mechanism based on distributed agents in the cloud environment was proposed to construct heterogeneous active-standby agents. The traffic to the active agent was analyzed by the standby agent through mirroring the traffic， and the output results of the active agent were cross-validated by the standby agent. Secondly， based on the Data Plane Development Kit （DPDK） platform， a synchronous adjudication mechanism for standby agents and a seamless active-standby switching mechanism were designed to achieve security reinforcement and performance optimization of cloud agents. Finally， an active-standby switching decision algorithm was proposed to avoid the waste of resources caused by frequent active/standby switching. Experimental results showed that compared with the traffic processing delay of Nginx based cloud agents， the loss of this mimic cloud agent was milliseconds under high concurrency. It can be seen that the designed method can greatly improve the security and stability of the cloud proxy， and reduce the impact of the single point of failure on the stability of the proxy.

With the development of cloud computing and big data, traditional single storage medium based data storage cannot meet the demands of large data processing, thus distributed data storage has been widely used recently. However, some existing distributed ways of storage cannot perfectly meet the needs of the distribution system. In order to achieve the distributed data storage and redundancy more effectively, a new distributed method and backup strategy based on Consistent Tree Distribution (CTD) was proposed to achieve the location mapping of data indexing and storage. The new method featured load balancing, no single point of failure, high scalability and easy programming. In addition, a method based on Consistent Binary Tree Distribution (CBTD) was also put forward. Analysis of the application system verifies that the method can satisfy the data balance, load balance and high scalability requirements of the distributed system.

Concerning the problem that the weighted undirected graphs output is needed to demonstrate weights with edge lengths, a new algorithm for weighted undirected graphs based on genetic algorithm was proposed. The algorithm obtained the ideal vertex coordinates by the crossover and mutation on the vertex coordinate coding. The mutation operator combined the inconsistent mutation with single neighbourhood mutation. In the fitness function, four evaluation criteria were employed: the average distance of the vertex, the edge crossing number, the uniformity of the angles around the multi-degree vertex, and the uniformity of the ratios of edge weight and edge length. The experimental results show that the drawn graph by the proposed algorithm is featured with edge-crossing-free, clear showing of branches and weight-length consistency. The visual output results of the algorithm are clear, visually optimized and especially faithful to weights. The algorithm is suitable to draw most kinds of weighted undirected graphs and can be used in undirected graph drawing methods and/or prototypes.