GCplace: geo-cloud based correlation aware data replica placement
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Cloud computing attracts considerable attention from both industry and academic these years. Nowadays, a number of research investigations have been conducted on cloud-based services (e.g., IaaS, PaaS, SaaS, etc.). Deployment of cloud-based services is one of the most important research problems. In cloud computing, multiple services tend to cooperate with each other to accomplish complicated tasks. Deploying these services independently may not lead to good overall performance, since there are a lot of interactions among different services. Making an optimal co-deployment of multiple services is critical for reducing latency of user requests. When deploying highly related services, taking only distribution of users into consideration is not enough, since the deployment of one service would affect others. To attack this challenge, we employ cross service information as well as user locations to build a new model in integer programming formulation. To reduce the computation time of the model, we purpose a sequential model running iteratively to obtain approximate solution. Extensive experiments have been conducted over a large real-world dataset, involving 307 distributed computers in about 40 countries, and 1881 real-world Internet-based services in about 60 countries. The experimental results show the effectiveness of our proposed model. Our real-world dataset is publicly released to promote future research, which also makes our experiments reproducible.