A Survey and Taxonomy of Self-Aware and Self-Adaptive Cloud Autoscaling Systems

Research output: Contribution to journalArticle

Colleges, School and Institutes

External organisations

  • Department of Computing and Technology, Nottingham Trent University, UK, and CERCIA, School of Computer Science, University of Birmingham, UK
  • CERCIA, School of Computer Science, The University of Birmingham
  • Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China, and CERCIA, School of Computer Science, University of Birmingham, UK

Abstract

Autoscaling system can reconfigure cloud-based services and applications, through various configurations of cloud software and provisions of hardware resources, to adapt to the changing environment at runtime. Such a behavior offers the foundation for achieving elasticity in a modern cloud computing paradigm. Given the dynamic and uncertain nature of the shared cloud infrastructure, the cloud autoscaling system has been engineered as one of the most complex, sophisticated, and intelligent artifacts created by humans, aiming to achieve self-aware, self-adaptive, and dependable runtime scaling. Yet the existing Self-aware and Self-adaptive Cloud Autoscaling System (SSCAS) is not at a state where it can be reliably exploited in the cloud. In this article, we survey the state-of-the-art research studies on SSCAS and provide a comprehensive taxonomy for this field. We present detailed analysis of the results and provide insights on open challenges, as well as the promising directions that are worth investigated in the future work of this area of research. Our survey and taxonomy contribute to the fundamentals of engineering more intelligent autoscaling systems in the cloud.

Details

Original languageEnglish
Article number61
JournalACM Computing Surveys
Volume51
Issue number3
Publication statusPublished - 12 Jun 2018

Keywords

  • Cloud computing, auto-scaling, resources provisioning, distributed systems, self-aware systems, self-adaptive systems