Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid

Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid

Kuo-Chan Huang (National Taichung University, Taiwan), Po-Chi Shih (National Taichung University, Taiwan) and Yeh-Ching Chung (National Taichung University, Taiwan)
DOI: 10.4018/978-1-60566-184-1.ch004
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Most current grid environments are established through collaboration among a group of participating sites which volunteer to provide free computing resources. Therefore, feasible load sharing policies that benefit all sites are an important incentive for attracting computing sites to join and stay in a grid environment. Moreover, a grid environment is usually heterogeneous in nature at least for different computing speeds at different participating sites. This chapter explores the feasibility and effectiveness of load sharing activities in a heterogeneous computational grid. Several issues are discussed including site selection policies as well as feasible load sharing mechanisms. Promising policies are evaluated in a series of simulations based on workloads derived from real traces. The results show that grid computing is capable of significantly improving the overall system performance in terms of average turnaround time for user jobs.
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Without grid computing users can only run jobs on their local site. The owners or administrators of different sites are interested in the potential benefit of participating in a computational grid and whether such participation will result in better service for their local users by improving the job turnaround time. Therefore, it is important to ensure that grid computing can bring performance improvement and that the improvement is achieved in the sense that all participating sites benefit from the collaboration. In the other words, no participating sites’ average turnaround time of their local jobs would increase after joining the computational grid.

Heterogeneity is another important issue in a computational grid. Many previous work (Bucur and Epema, 2003; Ernemann et al., 2002; Zhang et al., 2006) have shown significant performance improvement for multi-site homogeneous grid environments. However, in the real world a grid usually consists of heterogeneous sites that differ in configuration and computing speed. Heterogeneity puts a challenge on designing effective load sharing methods. Methods developed for homogeneous grids have to be improved or even redesigned to make them effective in a heterogeneous environment. This article addresses the potential benefit of sharing jobs among different sites in a speed-heterogeneous computational grid environment. Related issues are discussed, including job scheduling for feasible load sharing and site selection for processor allocation.

Job scheduling for parallel computers has been a subject of research for a long time. As for grid computing, previous work discussed several strategies for a grid scheduler. One approach is the modification of traditional list scheduling strategies for usage on a grid (Hamscher et al., 2000; Ernemann et al,. 2002). Some economic based methods are also being discussed (Buyya et al., 2002; 2003; Zhu et al., 2005; Ernemann et al., 2002). In this article we explore non-economic scheduling and allocation policies for a speed-heterogeneous grid environment.

Key Terms in this Chapter

Processor Allocation: It is concerned with the assignment of the required number of processors for a specific job.

Grid Computing: An IT infrastructure that can dynamically integrate various resources together for use based on specific need. Those resources may be located on different places and managed by different organizations or authorities, connected through public or private networks.

Load Sharing: Jobs submitted at a local site and waiting in a queue can be migrated to remote sites for immediate execution or reduced waiting time.

Site Selection: It chooses an appropriate site among a set of candidate sites in a computational grid for allocating a job according to some specified criteria.

Computing Grid: A kind of grid computing platform that focuses on integrating computing resources at different places for solving computing-intensive problems or applications.

Job Scheduling: It determines the sequence of starting execution for the submitted jobs waiting in the queue.

Feasible Sharing: A computational grid is feasible if it can bring performance improvement and the improvement is achieved in the sense that all participating sites benefit from the collaboration. That means no participating sites’ average turnaround time for their jobs get worse after joining the computational grid.

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Editorial Advisory Board
Table of Contents
Ruth E. Shaw
Emmanuel Udoh, Frank Zhigang Wang
Emmanuel Udoh
Chapter 1
Emmanuel Udoh, Frank Zhigang Wang, Vineet R. Khare
This chapter presents a historical record of the advent of Grid with a recourse to some basic definitions commonly accepted by most researchers. It... Sample PDF
Overview of Grid Computing
Chapter 2
Eric Aubanel
The problem of load balancing parallel applications is particularly challenging on computational grids, since the characteristics of both the... Sample PDF
Resource-Aware Load Balancing of Parallel Applications
Chapter 3
Enis Afgan, Purushotham Bangalore
Grid computing has emerged as the next generation computing platform. Because of the resource heterogeneity that exists in the grid environment... Sample PDF
Assisting Efficient Job Planning and Scheduling in the Grid
Chapter 4
Kuo-Chan Huang, Po-Chi Shih, Yeh-Ching Chung
Most current grid environments are established through collaboration among a group of participating sites which volunteer to provide free computing... Sample PDF
Effective Resource Allocation and Job Scheduling Mechanisms for Load Sharing in a Computational Grid
Chapter 5
Tevfik Kosar
As the data requirements of scientific distributed applications increase, the access to remote data becomes the main performance bottleneck for... Sample PDF
Data-Aware Distributed Batch Scheduling
Chapter 6
Gianni Pucciani, Flavia Donno, Andrea Domenici, Heinz Stockinger
Data replication is a well-known technique used in distributed systems in order to improve fault tolerance and make data access faster. Several... Sample PDF
Consistency of Replicated Datasets in Grid Computing
Chapter 7
Ming Wu, Xian-He Sun
Rapid advancement of communication technology has changed the landscape of computing. New models of computing, such as business-on-demand, Web... Sample PDF
Quality of Service of Grid Computing
Chapter 8
QoS in Grid Computing  (pages 75-83)
Zhihui Du, Zhili Cheng, Xiaoying Wang, Chuang Lin
This chapter first summarizes popular terms of QoS related concepts and technologies in grid computing, including SLA, End-to-End QoS Provision and... Sample PDF
QoS in Grid Computing
Chapter 9
Kris Bubendorfer, Ben Palmer, Ian Welch
A Grid resource broker is the arbiter for access to a Grid’s computational resources and therefore its performance and functionality has a... Sample PDF
Trust and Privacy in Grid Resource Auctions
Chapter 10
Sandro Fiore, Alessandro Negro, Salvatore Vadacca, Massimo Cafaro, Giovanni Aloisio, Roberto Barbera
Grid computing is an emerging and enabling technology allowing organizations to easily share, integrate and manage resources in a distributed... Sample PDF
An Architectural Overview of the GRelC Data Access Service
Chapter 11
Man Wang, Zhihui Du, Zhili Cheng
Resource Management System (RMS), which manages the Grid resources and matches the applications’ requests to the proper resources, is one of the... Sample PDF
Adaptive Resource Management in Grid Environment
Chapter 12
Vineet R. Khare, Frank Zhigang Wang
The need for a dynamic and scalable expansion of the grid infrastructure and resources and other scalability issues in terms of execution efficiency... Sample PDF
Bio-Inspired Grid Resource Management
Chapter 13
Yuhui Deng, Frank Zhigang Wang, Na Helian
Storage Grid is a new model for deploying and managing the heterogeneous, dynamic, large-scale, and geographically distributed storage resources.... Sample PDF
Service Oriented Storage System Grid
Chapter 14
Dominic Cherry, Maozhen Li, Man Qi
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A Distributed Storage System for Archiving Broadcast Media Content
Chapter 15
Maozhen Li, Man Qi, Bin Yu
The computational grid is rapidly evolving into a service-oriented computing infrastructure that facilitates resource sharing and large-scale... Sample PDF
Service Discovery with Rough Sets
Chapter 16
Irfan Habib, Ashiq Anjum, Richard McClatchey
Due to some barriers to adoption we have not seen a proliferation of Grid Computing technologies throughout e-Science or other domains. This chapter... Sample PDF
On the Pervasive Adoption of Grid Technologies: A Grid Operating System
Chapter 17
Kurt Vanmechelen, Jan Broeckhove, Wim Depoorter, Khalid Abdelkader
As grid computing technology moves further up the adoption curve, the issues of dealing with conflicting user requirements formulated by different... Sample PDF
Pricing Computational Resources in Grid Economies
Chapter 18
Rosario M. Piro
Large, geographically distributed and heterogeneous computing infrastructures, such as the Grid, often span multiple organizations and... Sample PDF
Resource Usage Accounting in Grid Computing
Chapter 19
Frans Arickx, Jan Broeckhove, Peter Hellinckx, David Dewolfs, Kurt Vanmechelen
Quantum structure or scattering calculations often belong to a class of computational problems involving the aggregation of a set of matrices... Sample PDF
Grid-Based Nuclear Physics Applications
Chapter 20
Gabriel Aparicio, Fernando Blanco, Ignacio Blanquer, César Bonavides, Juan Luis Chaves, Miguel Embid, Álvaro Hernández
In the last years an increasing demand for Grid Infrastructures has resulted in several international collaborations. This is the case of the EELA... Sample PDF
Developing Biomedical Applications in the Framework of EELA
Chapter 21
Gerald Schaefer, Roger Tait
Efficient approaches to computationally intensive image processing tasks are currently highly sought after. In this chapter, the authors show how a... Sample PDF
Distributed Image Processing on a Blackboard System
Chapter 22
Daniele Andreotti, Armando Fella, Eleonora Luppi
The BaBar experiment uses data since 1999 in examining the violation of charge and parity (CP) symmetry in the field of high energy physics. This... Sample PDF
Simulated Events Production on the Grid for the BaBar Experiment
Chapter 23
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A Framework for Semantic Grid in E-Science
Chapter 24
Roberto Barbera, Valeria Ardizzone, Leandro Ciuffo
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Grid INFN Virtual Laboratory for Dissemination Activities (GILDA)
Chapter 25
Dirk Gorissen, Tom Dhaene, Piet Demeester, Jan Broeckhove
The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling... Sample PDF
Grid Enabled Surrogate Modeling
Chapter 26
Patrik Skogster
Grid computing is becoming as essential part of different business analysis. In traditional business computing infrastructures data transfer occurs... Sample PDF
GIS Grids and the Business Use of GIS Data
Chapter 27
Gokop Goteng, Ashutosh Tiwari, Rajkumar Roy
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Grid Computing: Combating Global Terrorism with the World Wide Grid
Chapter 28
Salvatore Scifo
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Accessing Grid Metadata through a Web Interface
Chapter 29
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Chapter 30
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