Costs and Benefits of Load Sharing in the Computational Grid

Towards Feasible and Effective Load Sharing in a Heterogeneous Computational Grid

Advances in Grid and Pervasive Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-540-72360-8_20 ◽

2007 ◽

pp. 229-240 ◽

Cited By ~ 6

Author(s):

Kuo-Chan Huang ◽

Po-Chi Shih ◽

Yeh-Ching Chung

Keyword(s):

Load Sharing ◽

Computational Grid

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QoS-based Job Scheduling and Resource Management Strategies for Grid Computing

Quantitative Quality of Service for Grid Computing ◽

10.4018/978-1-60566-370-8.ch006 ◽

2011 ◽

pp. 110-127

Author(s):

Kuo-Chan Huang ◽

Po-Chi Shih ◽

Yeh-Ching Chung

Keyword(s):

Resource Allocation ◽

Quality Of Service ◽

Job Scheduling ◽

Performance Metrics ◽

Management Strategies ◽

Load Sharing ◽

Computational Grid ◽

Qos Performance ◽

Grid Level

This chapter elaborates the quality of service (QoS) aspect of load sharing activities in a computational grid environment. Load sharing is achieved through appropriate job scheduling and resource allocation mechanisms. A computational grid usually consists of several geographically distant sites each with different amount of computing resources. Different types of grids might have different QoS requirements. In most academic or experimental grids the computing sites volunteer to join the grids and can freely decide to quit the grids at any time when they feel joining the grids bring them no benefits. Therefore, maintaining an appropriate QoS level becomes an important incentive to attract computing sites to join a grid and stay in it. This chapter explores the QoS issues in such type of academic and experimental grids. This chapter first defines QoS based performance metrics for evaluating job scheduling and resource allocation strategies. According to the QoS performance metrics appropriate grid-level load sharing strategies are developed. The developed strategies address both user-level and site-level QoS concerns. A series of simulation experiments were performed to evaluate the proposed strategies based on real and synthetic workloads.

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

Handbook of Research on Grid Technologies and Utility Computing ◽

10.4018/978-1-60566-184-1.ch004 ◽

2009 ◽

pp. 31-40

Author(s):

Kuo-Chan Huang ◽

Po-Chi Shih ◽

Yeh-Ching Chung

Keyword(s):

Site Selection ◽

System Performance ◽

Job Scheduling ◽

Load Sharing ◽

Turnaround Time ◽

Computational Grid ◽

Grid Environment ◽

Grid Environments ◽

Scheduling Mechanisms ◽

Average Turnaround Time

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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QoS-Based Job Scheduling and Resource Management Strategies for Grid Computing

Grid and Cloud Computing ◽

10.4018/978-1-4666-0879-5.ch603 ◽

2012 ◽

pp. 1315-1331

Author(s):

Kuo-Chan Huang ◽

Po-Chi Shih ◽

Yeh-Ching Chung

Keyword(s):

Resource Allocation ◽

Quality Of Service ◽

Job Scheduling ◽

Performance Metrics ◽

Management Strategies ◽

Load Sharing ◽

Computational Grid ◽

Qos Performance ◽

Grid Level

This chapter elaborates the quality of service (QoS) aspect of load sharing activities in a computational grid environment. Load sharing is achieved through appropriate job scheduling and resource allocation mechanisms. A computational grid usually consists of several geographically distant sites each with different amount of computing resources. Different types of grids might have different QoS requirements. In most academic or experimental grids the computing sites volunteer to join the grids and can freely decide to quit the grids at any time when they feel joining the grids bring them no benefits. Therefore, maintaining an appropriate QoS level becomes an important incentive to attract computing sites to join a grid and stay in it. This chapter explores the QoS issues in such type of academic and experimental grids. This chapter first defines QoS based performance metrics for evaluating job scheduling and resource allocation strategies. According to the QoS performance metrics appropriate grid-level load sharing strategies are developed. The developed strategies address both user-level and site-level QoS concerns. A series of simulation experiments were performed to evaluate the proposed strategies based on real and synthetic workloads.

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Using the research on intergroup conflict in nonhuman animals to help inform patterns of human intergroup conflict

Behavioral and Brain Sciences ◽

10.1017/s0140525x19000827 ◽

2019 ◽

Vol 42 ◽

Author(s):

Amanda R. Ridley ◽

Melanie O. Mirville

Keyword(s):

Large Body ◽

Nonhuman Animal ◽

Intergroup Conflict ◽

Costs And Benefits ◽

Animal Groups ◽

Interesting Article ◽

Nonhuman Animals

Abstract There is a large body of research on conflict in nonhuman animal groups that measures the costs and benefits of intergroup conflict, and we suggest that much of this evidence is missing from De Dreu and Gross's interesting article. It is a shame this work has been missed, because it provides evidence for interesting ideas put forward in the article.

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