On-Demand Self-Adaptivity of Service Availability for Cloud Multi-tier Applications
Jin Yang, Jianmin Pang, Ning Qi, Tao Qi · 2015
Cloud data centers are increasingly becoming the first choice for many Internet enterprises (especially medium-sized and small ones) to deploy their online application. However, scaling service availability autonomously is a critical issue for Internet applications. Surplus service supply may take a lot of unnecessary money and insufficient resources reserve will result in denial of service when meeting sudden massive requests. A general idea to address the issue is increasing the resource utilization through workload balancing and dynamic resources management. In this paper, we propose a self-adaptive approach that is suitable for the multi-tier cloud applications. The approach tries to scale the applications' service availability on demand and reduce infrastructure costs by improving utilization of the resources that are already billed. Moreover, in order to cope with the unexpected requests, an evaluation method is adopted to estimate the trend of requests' development and then decide to add or remove working servers. Finally, we compare the proposed algorithms with the workload consolidation method by a quantitative analysis, showing the superiorities of costs and performance in some situations.