Cloud storage has become an important part of a cloud system nowadays. Most current cloud storage systems perform well for large files but they cannot manage small file storage appropriately. With the development of cloud services, more and more small files are emerging. Therefore, we propose an optimized data replication approach for small files in cloud storage systems. A small file merging algorithm and a block replica placement algorithm are involved in this approach. Small files are classified into four types according to their access frequencies. A number of small files will be merged into the same block based on which type they belong to. And the replica placement algorithm helps to improve the access efficiencies of small files in a cloud system. Related experiment results demonstrate that our proposed approach can effectively shorten the time spent reading and writing small files, and it performs better than the other two already known data replication algorithms: HAR and SequenceFile.

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The virtualization of cloud computing improves the utilization of resources and energy. And a cloud user can deploy his/her own applications and related data on a pay-as-you-go basis. The communications between an application and a data storage node, as well as within the application, have a great impact on the execution efficiency of the application. The locations of subtasks of an application and the data that transferred between the subtasks are the main reason why communication delay exists. The communication delay can affect the completion time of the application. In this paper, we take into account the data transmission time and communications between subtasks and propose a heuristic optimal virtual machine (VM) placement algorithm. Related simulations demonstrate that this algorithm can reduce the completion time of user tasks and ensure the feasibility and effectiveness of the overall network performance of applications when running in a cloud computing environment.