Towards an SLA-driven cache adjustment approach for applications on PaaS

Cloud computing encourages application to migrate into it for economic of scale, where they rent shared resources to deliver services. Service Level Agreements(SLA) plays an important role in assisting various applications providing high-quality services to end users in cloud's complex and uncertain environments. Most of the existing work tries to support application claimed quality by help cloud make decisions of computing resources allocation during runtime. In this paper, we propose an approach for applications to maintain quality requirements by runtime cache adjustment in consideration of service level objectives (SLOs) and unpredictable workload in cloud, which can be taken as a complement to the existing work. Our approach includes application SLO modeling and mapping to monitor metrics during runtime, and an algorithm to adapting caches according to runtime status and SLOs. The approach has been applied to a real-world SNS application which proves effectiveness of our approach. Categories and Subject Descriptors D 2.8 [Metrics]: Performance measures; D.4.2 [Storage Managements]: Distributed memories. General Terms Performance, Algorithms, Experiment.EI