Survey and Taxonomy of Self-Aware and Self-Adaptive Autoscaling Systems in the Cloud.
Year: 2016
Type: preprint
Abstract: Autoscaling system can reconfigure cloud-based applications and services, through various cloud software configurations and hardware provisioning, to adapt to the changing environment at runtime. Such a behaviour offers the foundation to achieve elasticity in modern cloud computing paradigm. Given the importance of autoscaling in cloud, computational intelligence has been widely applied for engineering autoscaling system, leading to self-aware, self-adaptive and more dependable runtime scaling. In this paper, we present the brief background and history for autoscaling in the cloud, as well as their associations with self-awareness and self-adaptivity of a system. Subsequently, we conduct detailed survey and taxonomy of the key related work and identify the gaps in this area of research. Keywords-performance modeling, self-aware systems; selfadaptive systems; auto-scaling; cloud computing
Source: arXiv (Cornell University)
Authors: Tao Chen, Rami Bahsoon
Institution: University of Birmingham
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2518787508