Research And Application Of Service Deployment Optimization Technology In Cloud Computing Environment

In a Cloud Computing environment, a great amount of services require to be deployed into the cloud, which may lead to the redundancy and complexity of cloud-services, and a ever-increasing resource consumption. Current researches try to optimize the ever-growing services with support of buffer pool and deployment optimization algorithms by the compatibility between different atomic services. Buffer pool here performs the crucial task of storing the deployment requirements awaiting to be optimized. However, issues like when to enforce flush and which stored objects should be flushed out still lack thorough consideration. To address these problems, we propose a improved cooperative dynamic double buffer pool in this paper. Through classifying different deployment requirements and flush fashions, we select a threshold to determine when to enforce the flush. According to this flush time, combining with necessary interaction with service owner, we can select the to-be-optimized objects dynamically. Meanwhile we present part of our algorithms of the buffer pool flush mechanism, and the improved service deployment optimization approach. We illustrate the effectiveness and feasibility of our approach through a demonstration, to guarantee a relatively high optimization efficiency. In the end, we use a real project to demonstrate its design effective and reliable.