ATOM : Efficient Tracking, Monitoring, and Orchestration of Cloud Resources

Abstract

The emergence of Infrastructure as a Service framework brings new opportunities, that conjointly accompanies with new challenges in auto-scaling, resource allocation, and security. A elementary challenge underpinning these issues is that the continuous tracking and monitoring of resource usage within the system. during this paper, we tend to present ATOM, AN efficient and effective framework to automatically track, monitor, ANd orchestrate resource usage in an Infrastructure as a Service (IaaS) system that's wide employed in cloud infrastructure. we tend to use novel trailing methodology to ceaselessly track vital system usage metrics with low overhead, and develop a Principal part Analysis (PCA) primarily based approach to ceaselessly monitor and automatically notice anomalies supported the approximated trailing results. we tend to show a way to dynamically set the trailing threshold supported the detection results, and more, a way to regulate trailing rule to confirm its optimality beneath dynamic workloads. Lastly, once potential anomalies square measure known, we tend to use introspection tools to perform memory forensics on VMs guided by analyzed results from trailing and monitoring to spot malicious behavior within a VM. we tend to demonstrate the extensibility of ATOM through virtual machine (VM) bunch. The performance of our framework is evaluated in AN open supply IaaS system.