Multi-source task scheduling in grid computing environment using linear programming

Murugesan, G.; Chellappan, C.

doi:10.1504/ijcse.2014.058701

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…In [10], Murugesan et al proposed a multi-source task scheduler to map the tasks to the distributed resources in a cloud. The scheduler has three phases: the task aggregation, the task selection, and the task sequencing.…”

Section: Related Work In the Literaturementioning

confidence: 99%

A Static Assignment Algorithm of Uniform Jobs to Workers in a User-PC Computing System Using Simultaneous Linear Equations

et al. 2022

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Currently, the User-PC computingsystem (UPC) has been studied as a low-cost and high-performance distributed computing platform. It uses idling resources of personal computers (PCs) in a group.The job-worker assignment for minimizing makespan is critical to determine the performance of the UPC system.Some applications need to execute a lot of uniform jobs that use the identical program but with slightly different data, where they take the similar CPU time on a PC. Then, the total CPU time of a worker is almost linear to the number of assigned jobs. In this paper, we propose a static assignment algorithm of uniform jobs to workers in the UPC system, using simultaneous linear equations to find the lower bound on makespan, where every worker requires the same CPU time to complete the assigned jobs. For the evaluations of the proposal, we consider the uniform jobs in three applications. In OpenPose, the CNN-based keypoint estimation program runs with various images of human bodies. In OpenFOAM, the physics simulation program runs with various parameter sets. In code testing, two open-source programs run with various source codes from students for the Android programming learning assistance system (APLAS). Using the proposal, we assigned the jobs to six workers in the testbed UPC system and measured the CPU time. The results show that makespan was reduced by 10% on average, which confirms the effectiveness of the proposal.

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Section: Related Work In the Literaturementioning

confidence: 99%

A Static Assignment Algorithm of Uniform Jobs to Workers in a User-PC Computing System Using Simultaneous Linear Equations

et al. 2022

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“…However, these swift scheduler methods do not focus on the resource utilization and economic factors. To overcome the drawback which is presented in the swift scheduler method, an economic based resource allocation model has been proposed by Murugesan et al (2010). They have proposed a resource allocation model with multiple load originating processors as an economic model.…”

Section: Related Workmentioning

confidence: 99%

Resource Allocation Mechanism with New Models for Grid Environment

Sathish

Reddy

2013

International Journal of Grid and High Performance Computing

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Resource allocation is playing a vital role in grid environment because of the dynamic and heterogeneous nature of grid resources. Literature offers numerous studies and techniques to solve the grid resource allocation problem. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. These problems were occurred because of the inconsiderable level in the code of allocating right resources to right jobs, poor economic model and lack of provision to minimize the waiting time of jobs to get their resources. So, all these drawbacks need to be solved in any upcoming resource allocation technique. Hence in this paper, the efficiency of the resource allocation mechanism is improved by proposing two allocation models. Both the allocation models have used the Genetic Algorithm to overcome all the aforesaid drawbacks. However, one of the allocation models includes penalty function and the other does not consider the economic reliability. Both the models are implemented and experimented with different number of jobs and resources. The proposed models are compared with the conventional resource allocation models in terms of utilization, cost factor, failure rate and make span.

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“…One challenge is that data-intensive applications may be built upon conventional frameworks, such as shared-nothing parallel database management systems, or modern frameworks, such as MapReduce (Cardosa et al, 2011), and so have very different resource requirements. A second challenge is that the parallel nature of large-scale data-intensive applications requires that scheduling (Hu et al, 2010;Achar et al, 2012;Murugesan and Chellappan, 2014) and resource allocation (Kavitha and Sankaranarayanan, 2014;Allenotor and Thulasiram, 2011) be done to avoid data transfer bottlenecks. A third challenge is to support effective scaling of resources when large volumes of data are involved.…”

Section: Introductionmentioning

confidence: 99%

Live migration of virtual machines with their local persistent storage in a data intensive cloud

Modi

Achar

Thilagam

2017

IJHPCN

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Abstract:Processing large volumes of data to drive their core business has been the primary objective of many firms and scientific applications in these days. Cloud computing being a large-scale distributed computing paradigm can be used to cater for the needs of data intensive applications. There are various approaches for managing the workload on a data intensive cloud. Live migration of a virtual machine is the most prominent paradigm. Existing approaches to live migration use network attached storage where just the run time state needs to be transferred. Live migration of virtual machines with local persistent storage has been shown to have performance advantages like security, availability and privacy. This paper presents an optimised approach for migration of a virtual machine along with its local storage by considering the locality of storage access. Count map combined with a restricted block transfer mechanism is used to minimise the downtime and overhead. The solution proposed is tested by various parameters like bandwidth, write access patterns and threshold. Results show the improvement in downtime and reduction in overhead.

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Multi-source task scheduling in grid computing environment using linear programming

Cited by 5 publications

References 13 publications

A Static Assignment Algorithm of Uniform Jobs to Workers in a User-PC Computing System Using Simultaneous Linear Equations

A Static Assignment Algorithm of Uniform Jobs to Workers in a User-PC Computing System Using Simultaneous Linear Equations

Resource Allocation Mechanism with New Models for Grid Environment

Live migration of virtual machines with their local persistent storage in a data intensive cloud

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