Using MinMax-Memory Claims to Improve In-Memory Workflow Computations in the Cloud

	Using MinMax-Memory Claims to Improve In-Memory Workflow Computations in the Cloud
	He, Shuibing; Wang, Yang; Sun, Xian-He; Xu, Chengzhong
刊名	IEEE Transactions on Parallel and Distributed Systems
	2017
文献子类	期刊论文
英文摘要	In this paper, we consider to improve scientific workflows in cloud environments where data transfers between tasks are performed via provisioned in-memory caching as a service, instead of relying entirely on slower disk-based file systems. However, this improvement is not free since services in the cloud are usually charged in a "pay-as-you-go" model. As a consequence, the workflow tenants have to estimate the amount of memory that they would like to pay. Given the intrinsic complexity of the workflows, it would be very hard to make an accurate prediction, which would lead to either oversubscription or undersubscription, resulting in unproductive spending or performance degradation. To address this problem, we propose a concept of minmax memory claim (MMC) to achieve cost-effective workflow computations in in-memory cloud computing environments. The minmax-memory claim is defined as the minimum amount of memory required to finish the workflow without compromising its maximum concurrency. With the concept of MMC, the workflow tenants can achieve the best performance via in-memory computing while minimizing the cost. In this paper, we present the procedure of how to find the MMCs for those workflows with arbitrary graphs in general and develop optimal efficient algorithms for some well-structured workflows in particular. To further show the values of this concept, we also implement these algorithms and apply them, through a simulation study, to improve deadlock resolutions in workflow-based workloads when memory resources are constrained.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12523]
专题	深圳先进技术研究院_数字所
作者单位	IEEE Transactions on Parallel and Distributed Systems
推荐引用方式 GB/T 7714	He, Shuibing,Wang, Yang,Sun, Xian-He,et al. Using MinMax-Memory Claims to Improve In-Memory Workflow Computations in the Cloud[J]. IEEE Transactions on Parallel and Distributed Systems,2017.
APA	He, Shuibing,Wang, Yang,Sun, Xian-He,&Xu, Chengzhong.(2017).Using MinMax-Memory Claims to Improve In-Memory Workflow Computations in the Cloud.IEEE Transactions on Parallel and Distributed Systems.
MLA	He, Shuibing,et al."Using MinMax-Memory Claims to Improve In-Memory Workflow Computations in the Cloud".IEEE Transactions on Parallel and Distributed Systems (2017).