An Improved Algorithm Based on Max-Min for Cloud Task Scheduling

Gao, Ming; Li, Hao

doi:10.1007/978-3-642-25789-6_32

Cited by 36 publications

(6 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For task scheduling in cloud computing, performance of Max-min algorithm is not achieved the better results. To resolve this issue, Ming and Li [ 73 ] offer an enhanced algorithm MMST based on Max-min. It reduces the waiting time and improves the resource utilization of tasks.…”

Section: Rule Based Scheduling Heuristicsmentioning

confidence: 99%

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

et al. 2017

View full text Add to dashboard Cite

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

show abstract

Section: Rule Based Scheduling Heuristicsmentioning

confidence: 99%

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The algorithm MMST also reduced the expenses of cloud services [6]. We are proposing a new leasing policy and implementation of its algorithm in this paper.…”

Section: Ming Et Al Proposed An Improved Algorithm Mmst Based Onmentioning

confidence: 98%

Comma

Shrivastava

Bhilare

2014

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies

View full text Add to dashboard Cite

Virtualization technology has made possible, providing memory, disk and processing power to consumers based on pre-defined conditions to be applied on both cloud consumers and cloud hosts. A consumer can have many Virtual Machines (VMs) at a time and a cloud host may have many such consumers at the same time. Competition in Cloud Service Providers (CSPs) and to maintain service level agreements, it is necessary for a CSP to have market-oriented leasing policy which can provide higher profit to cloud host while maintaining lowest cost, shortest downtime and maximum availability of resources to prioritized consumers at peak times. This paper introduces a new leasing policy and algorithm: COMMA (Cost Oriented, Market and Migration Aware) for maintaining a balance between cost, profit and migrations of VM during peak loads. Experiments and results show that this leasing policy and algorithm are effective and can be used for making profit and maintain QoS in a cloud environment.

show abstract

“…Ming and Li [11] investigated an enhanced algorithm MMST based on the Max-Min algorithm because of Max-Min is not achieved better results. MMST minimizes the waiting time and increases the resource utilization of tasks.…”

Section: International Journal Of Computer Applications (0975 -8887)mentioning

confidence: 99%

Improving Max-Min scheduling Algorithm for Reducing the Makespan of Workflow Execution in the Cloud

Al-Haboobi¹

2017

IJCA

View full text Add to dashboard Cite

Cloud computing has become a new paradigm that provides IT resources as a service based on the basis: pay-per-use over the internet. Scientific workflow applications can gain the advantage by running on cloud resources. However, the optimized of workflow scheduling algorithms is a challenge and still needed further work. This paper presents an improved Max-Min algorithm based on the Max-Min algorithm. It can minimize the makespan of workflow execution and increases the resource utilization. The algorithm tested using WorkflowSim with five workflows from the Pegasus workflow management system. The results show that this algorithm can achieve better than Max-Min in most of the cases. General TermsDistributed Computer Systems, Algorithms.

show abstract

An Improved Algorithm Based on Max-Min for Cloud Task Scheduling

Cited by 36 publications

References 2 publications

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment

Comma

Improving Max-Min scheduling Algorithm for Reducing the Makespan of Workflow Execution in the Cloud

Contact Info

Product

Resources

About