Bridging Ecology and Cloud: Transposing Ecological Prespective to Enable Better Cloud Autoscaling
Tao Chen, Rami Bahsoon

TL;DR
This paper explores how ecological principles can be applied to cloud autoscaling to improve the stability and sustainability of cloud services amidst complex, dynamic workloads.
Contribution
It introduces a novel ecological perspective to understand and enhance cloud autoscaling mechanisms, bridging ecology and cloud computing.
Findings
Ecological view helps explain cloud service evolution.
Ecological principles can improve autoscaling stability.
Potential for more sustainable cloud ecosystems.
Abstract
Elastic autoscaling is the fundamental mechanism that enables the cloud-based services to continually evolve themselves - through changing the related software configurations and hardware resource provisions - under time-varying workloads. However, given the increasingly complex dynamic, uncertainty and trade-offs related to the runtime QoS and cost/energy of services, cloud autoscaling system is becoming one of the most complex artifacts constructed by human and thus its effectiveness is difficult to be preserved. In this article, we present novel ideas for facilitating cloud autoscaling. Our hypothesis that cloud ecosystem, represented by a collection of cloud-based services, bears many similarities with the natural ecosystem. As such, we in- tend to investigate how ecological view can be adopted to better explain how the cloud-based services evolve, and to explore what are the key…
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Taxonomy
TopicsCloud Computing and Resource Management · Big Data and Business Intelligence · Scientific Computing and Data Management
