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Abstract: The basic idea behind Cloud computing is that resource providers offerelastic resources to end users. In this paper, we intend to answer one keyquestion to the success of Cloud computing: in Cloud, can small or medium-scalescientific computing communities benefit from the economies of scale? Ourresearch contributions are three-fold: first, we propose an enhanced scientificpublic cloud model ESP that encourages small- or medium-scale organizationsto rent elastic resources from a public cloud provider; second, on a basis ofthe ESP model, we design and implement the DawningCloud system that canconsolidate heterogeneous scientific workloads on a Cloud site; third, wepropose an innovative emulation methodology and perform a comprehensiveevaluation. We found that for two typical workloads: high throughput computingHTC and many task computing MTC, DawningCloud saves the resourceconsumption maximally by 44.5% HTC and 72.6% MTC for service providers, andsaves the total resource consumption maximally by 47.3% for a resource providerwith respect to the previous two public Cloud solutions. To this end, weconclude that for typical workloads: HTC and MTC, DawningCloud can enablescientific communities to benefit from the economies of scale of public Clouds.



Autor: Lei Wang, Jianfeng Zhan, Weisong Shi, Yi Liang

Fuente: https://arxiv.org/



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