With the rapid development of information technologies and the popularization of Internet applications, more and more companies and developers pay great attention to the cloud computing. As one of the most significant problems in cloud computing, virtual machine allocation has attracted significant attention. However, early studies usually ignore the load balance issue of the resources. In this article, we aim at multidimensional resource load balancing of all the physical machines in the cloud computing platform to maximize the utilization of resources. To achieve this goal, we leverage the ant colony optimization to design an efficient virtual machine allocation algorithm based on the NP-hard feature of this problem. Specifically, we customize the ant colony optimization in the context of virtual machine allocation and introduce an improved physical machine selection strategy to the basic ant colony optimization in order to prevent the premature convergence or falling into the local optima. Through extensive simulations, we demonstrate that our proposed algorithm can effectively achieve load balancing in virtual machine allocation and improve resource utilization for the cloud computing platform.

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Microblog plays a very important role in the process of public opinion dissemination after the occurrence of public emergencies. As a Micro blogging platform based on user information sharing, dissemination and access, it is suitable for using social network analysis method to analyze because of forming a network structure between the microblogging users. In this paper, we use the social network analysis method to explore the network structure, node position and key nodes feature such as the missed Malaysia Flight Mh370. The research shows that the network structure of the microblogging public opinion about public emergencies is loose, and the key nodes are more important that makes the public opinion spread quickly. Users participating in the dissemination of public opinion have obvious domain features. The relevant regulatory authorities need to focus on the key nodes (opinion leaders) of public opinion-prone areas.

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