-
Views
-
Cite
Cite
Mosong Zhou, Xiaoshe Dong, Heng Chen, Xingjun Zhang, A Runtime Available Resource Capacity Evaluation Model Based on the Concept of Similar Tasks, The Computer Journal, Volume 61, Issue 5, May 2018, Pages 722–744, https://doi.org/10.1093/comjnl/bxx091
- Share Icon Share
Abstract
A mismatch between resource supply and demand in cloud computing leads to inefficient utilization of resources or performance degradation. Therefore, this paper establishes a runtime model to evaluate the available capacity of computing resources on the basis of similar tasks. This model takes advantage of a characteristic of cloud workload; that is, similar tasks in cloud computing have a similar execution logic. The model evaluates the available resource capacity according to task similarity, thus avoiding any impact on the resource consumption of existing benchmarks. We apply the model to propose a resource capacity evaluation method called Caipan, which considers numerous factors according to resource type. This method obtains accurate results in a timely manner at little cost. We use the results of Caipan to develop some algorithms that aim to match resource supply and demand, and improve cloud platform performance. We test the Caipan method and the Caipan-based algorithms in both dedicated and real-world cloud environments. The test results show that the Caipan method obtains the available resource capacity both accurately and in a timely manner, and effectively supports the optimization of both algorithms and platforms. Moreover, algorithms based on Caipan reduce the mismatch between resource supply and demand, and significantly improve cloud platform performance.