Survey of Adaptive Elastic Scaling Studies on Distributed Service Resources

Abstract

In distributed service resource environments, a large number of service resources are underutilized or even idle for a long time due to the narrow percentage of peak load. Adaptive elastic scaling of resources can significantly improve system energy efficiency and reduce operation overhead: on the one hand, service resources can be expanded to cope with high demand during high load; and on the other hand, they can be scaled down to reduce the overhead during low load. However, the actual load is usually highly volatile, and the service resources required to satisfy the quality of service are constantly varying, which poses a great challenge to the adaptive elastic scaling of service resources. Although existing commercial distributed platforms generally have some resource elastic scaling capability, they suffer from limited adaptive ability and poor precision, and there exists a considerable improvement space. In order to promote the research and application development in this field, this paper analyzes the studies on adaptive elastic scaling of service resources in this environment. Firstly, the corresponding research background and main challenges in demand evaluation and resource adjustment are analyzed. Secondly, a categorized survey of domestic and international studies in this field is conducted, by dividing these studies into three categories based on the resource objects they adjust. The similarities and differences of these studies are compared, and their respective characteristics and usefulness are summarized. Finally, these study efforts are summarily analyzed, then a comprehensive realization is outlined based on the analysis, and besides, the current application status, research challenges and future research trends are discussed.

Keywords

• parallel and distributed computing; distributed service resources; resource management and allocation; adaptive elastic scaling