Contention-aware scheduling with task duplication

Sinnen, Oliver; To, Andrea; Kaur, Manpreet

doi:10.1016/j.jpdc.2010.10.004

Cited by 56 publications

(11 citation statements)

References 25 publications

(33 reference statements)

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“…Heuristics involves 3 subcategories namely clustering [3], list [5]and duplication algorithms [4]. In Clustering based algorithms such as Clustering for Heterogeneous Processors(CHP) [3], clusters of tasks are assigned to appropriate processors.…”

Section: Types Of Schedulingmentioning

confidence: 99%

“…On the other hand, duplication algorithms try to duplicate tasks to minimize makespan. Algorithms such as Contention aware (CA-D) [4] duplication algorithms eliminates the communication cost by placing tasks on same processor. A large time complexity and more processor usage limit the use of duplication based algorithms in cloud environment.…”

Section: Types Of Schedulingmentioning

confidence: 99%

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A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

Kaur

2017

IJARCSSE

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Abstract-Cloud Computing is a computing environment where different services are provided to users over the Web. Task Scheduling is one of the important aspects of Cloud Computing, improving the performance of the cloud system. Task Scheduling involves assignment of resources to a particular task for the task to be completed within possible minimum time. Task Scheduling helps in achieving efficient utilization of resources. This paper presents a review of various task scheduling algorithms in Cloud Computing.

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Section: Types Of Schedulingmentioning

confidence: 99%

Section: Types Of Schedulingmentioning

confidence: 99%

A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

Kaur

2017

IJARCSSE

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“…The communication link competition in task communication is considered. They proposed an energy-aware list-based scheduling algorithm [18] and duplication-based scheduling algorithm [19]. The communication path is selected based on the routing algorithm.…”

Section: Related Workmentioning

confidence: 99%

A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters

Liang

Pang

2016

MCA

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Abstract:Increasing energy has become an important issue in high performance clusters. To balance the energy and performance, we proposed a novel, energy-aware duplication-based scheduling (NEADS). An existing energy-aware duplication-based algorithm replicates all qualified predecessor tasks in a bottom-up manner. Some tasks without direct relation may be replicated to the same processor, which cannot reduce the communication energy. Instead, the computation overhead may be increased. In contrast, the proposed algorithm only replicates the directly correlated predecessor tasks in the energy threshold range without lengthening the schedule length. The proposed algorithm is compared with the non-duplication algorithm and existing duplicated-based algorithm. Extensive experimental results show that the proposed algorithm can effectively reduce energy consumption in various applications. It has advantages over other algorithms on computation-intensive applications.

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“…As such, we develop a node (representing a dataset or a task) adjustment algorithm to select a better data center for the inappropriately placed datasets and tasks. Another important technique is task duplication . When a task consumes comparatively small volume of datasets but produces large volume of intermediate datasets, it may be better to duplicate the task in another data center instead of transferring the result.…”

Section: Weighted K‐means Clustering Strategymentioning

confidence: 99%

A clustering based coscheduling strategy for efficient scientific workflow execution in cloud computing

Deng

Ren

Song

et al. 2013

Concurrency and Computation

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SUMMARY Due to its advantages of cost‐effectiveness, on‐demand provisioning and easy for sharing, cloud computing has grown in popularity with the research community for deploying scientific applications such as workflows. Although such interests continue growing and scientific workflows are widely deployed in collaborative cloud environments that consist of a number of data centers, there is an urgent need for exploiting strategies which can place application datasets across globally distributed data centers and schedule tasks according to the data layout to reduce both latency and makespan for workflow execution. In this paper, by utilizing dependencies among datasets and tasks, we propose an efficient data and task coscheduling strategy that can place input datasets in a load balance way and meanwhile, group the mostly related datasets and tasks together. Moreover, data staging is used to overlap task execution with data transmission in order to shorten the start time of tasks. We build a simulation environment on Tianhe supercomputer for evaluating the proposed strategy and run simulations by random and realistic workflows. The results demonstrate that the proposed strategy can effectively improve scheduling performance while reducing the total volume of data transfer across data centers. Concurrency and Computation: Practice and Experience, 2013.© 2013 Wiley Periodicals, Inc.

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Contention-aware scheduling with task duplication

Cited by 56 publications

References 25 publications

A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

A Review Paper on Various Task Scheduling Algorithms in Cloud Computing

A Novel, Energy-Aware Task Duplication-Based Scheduling Algorithm of Parallel Tasks on Clusters

A clustering based coscheduling strategy for efficient scientific workflow execution in cloud computing

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