RESOURCE ALLOCATION IN SELF ORGANIZING CLOUD - A SURVEY
S. Thejeswi · 2013
By gearing virtual machine (VM) technology which provides performance and fault seclusion, cloud resources can be provisioned on demand in a pulverized, multiplexed manner rather than in monumental pieces. By incorporating unpaid assistant computing into cloud architectures, we foresee a colossal self-organizing cloud being twisted to gather the vast perspective of unexploited service computing power over the Internet. Toward this new architecture where each participant may separately act as both resource consumer and provider, we propose a fully distributed, VM-multiplexing resource allocation format to supervise decentralized resources. Our approach not only achieves maximized resource utilization using the proportional share model but also delivers provably and adaptively finest execution efficiency. We also devise a new multi attribute range query protocol for locating best fit nodes. Divergent to existing solutions which often produce immense number of messages per request, our protocol produces only one lightweight query message per task on the Content Addressable Network . It works efficiently to discover for each task its best fit resources under a randomized policy that mitigates the contention among requesters. We show the self organizing cloud with our optimized algorithms can make an enhancement by 15-60 percent in system throughput than a P2P Grid model. Our solution also exhibits fairly high adaptability in a self-motivated node- agitating environment.