A Lightweight Approach Multiplexing Resource Allocation Scheme by Virtualization based on Time Series in SOC

By leveraging virtual machine (VM) technology which provides performance and fault isolation, Cloud resources can be provisioned on demand in a fine-grained, multiplexed manner rather than in monolithic pieces. By integrating volunteer computing into Cloud architectures, we envision a gigantic Self-Organizing Cloud (SOC) being formed to reap the huge potential of untapped commodity computing power over the Internet. Towards this new architecture where each participant may autonomously act as both resource consumer and provider, we propose a fully distributed, VM-multiplexing resource allocation scheme to manage decentralized resources. Our approach not only achieves maximized resource utilization using the proportional share model (PSM), but also delivers provably and adaptively optimal execution efficiency. We also design a novel multi-attribute range query protocol for locating qualified nodes. Contrary to existing solutions which often generate bulky messages per request, our protocol produces only one lightweight query message per task on the Content Addressable Network (CAN). It works effectively to find for each task its qualified resources under a randomized policy that mitigates the contention among requesters. This paper extends our previous work and proposes a lightweight mathematical model to estimate the energy cost of live migration of an idle virtual machine quantitatively. A series of experiments were conducted on KVM to profile the migration time and the power consumption during live migration. Based on these data we derived an energy cost model that predicts the energy overhead of live migration of virtual machines with an accuracy of higher than 90%.