Improving Processor Allocation in Heterogeneous Computing Grid through Considering Both Speed Heterogeneity and Resource Fragmentation

It will become increasingly popular that scientists in research institutes will make use of Grid computing resources for running computer simulations and managing data. Although there are some production Grids available, it is often the case that many organizations and research projects need to build their own Grids. However, building Grid infrastructure is not a trivial job as it involves sharing and managing heterogeneous computing and data resources across different organizations, and involves installing many specific software packages and various middleware. This can be quite complicated and time-consuming. Building a Grid infrastructure also requires good knowledge and understanding of distributed computing, parallel computing and Grid technologies. Apart from building physical Grid, how to build a user infrastructure that can facilitate the use of and easy access to these physical infrastructures is also a challenging task. In this chapter, the authors summarize some hands-on experience in building an institutional Grid infrastructure. They describe knowledge and experience obtained in the installations of Condor pools, PBS clusters, Globus Toolkit, and SRB (Storage Resource Broker) for computing Grid and data Grid. The authors also propose to use a User-Centered Design (UCD) approach to develop a Grid user infrastructure which can facilitate the use of the Grid to improve the usability.

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Hands on Experience on Building Institutional Grid Infrastructure

Quantitative Quality of Service for Grid Computing ◽

10.4018/978-1-60566-370-8.ch015 ◽

2011 ◽

pp. 271-298

Author(s):

Xiaoyu Yang ◽

Gen-Tao Chiang

Keyword(s):

Parallel Computing ◽

Heterogeneous Computing ◽

Easy Access ◽

Research Projects ◽

Grid Infrastructure ◽

Research Institutes ◽

Software Packages ◽

Hands On ◽

Storage Resource ◽

Computing Grid

It will become increasingly popular that scientists in research institutes will make use of Grid computing resources for running computer simulations and managing data. Although there are some production Grids available, it is often the case that many organizations and research projects need to build their own Grids. However, building Grid infrastructure is not a trivial job as it involves sharing and managing heterogeneous computing and data resources across different organizations, and involves installing many specific software packages and various middleware. This can be quite complicated and time-consuming. Building a Grid infrastructure also requires good knowledge and understanding of distributed computing, parallel computing and Grid technologies. Apart from building physical Grid, how to build a user infrastructure that can facilitate the use of and easy access to these physical infrastructures is also a challenging task. In this chapter, the authors summarize some hands-on experience in building an institutional Grid infrastructure. They describe knowledge and experience obtained in the installations of Condor pools, PBS clusters, Globus Toolkit, and SRB (Storage Resource Broker) for computing Grid and data Grid. The authors also propose to use a User-Centered Design (UCD) approach to develop a Grid user infrastructure which can facilitate the use of the Grid to improve the usability.

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Heuristic Algorithm for Independent Task Scheduling in Grid Computing

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d9411.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 12861-12866

Keyword(s):

Resource Utilization ◽

Resource Sharing ◽

Heterogeneous Computing ◽

Scheduling Algorithm ◽

Heuristic Scheduling ◽

Heuristic Technique ◽

Geographically Distributed ◽

Computing Grid ◽

Grid Resources ◽

Independent Tasks

Grid enables the integration of large number of geographically distributed heterogeneous resources owned by different organizations for resource sharing and collaboration in solving advanced sciences and engineering applications. In a distributed heterogeneous computing grid environment, scheduling independent tasks on the grid resources is more complicated and is an NP-Complete problem. Scheduling is the process of mapping the tasks to the available resources. In order to utilize the essence of grid efficiently, this paper presents a heuristic technique for scheduling/mapping the tasks to the resources. The efficiency of the proposed algorithm (WSSLVA) in terms of reduced makespan as well as better resource utilization is achieved. The experimental results indicate that the proposed WSSLVA algorithm is a promising algorithm than the Min-min heuristic scheduling algorithm in terms of makespan and resource utilization.

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