Evaluating Heuristics for Scheduling Dependent Jobs in Grid Computing Environments

2010 ◽  
Vol 2 (4) ◽  
pp. 65-80 ◽  
Author(s):  
Geoffrey Falzon ◽  
Maozhen Li
Keyword(s):  
Performance Evaluation ◽  
Job Scheduling ◽  
Critical Role ◽  
Difficult Problem ◽  
Grid Environment ◽  
Acyclic Graphs ◽  
Computing Environments ◽  
Np Complete ◽  
Grid Resources ◽  
Direct Acyclic Graphs

Job scheduling plays a critical role in the utilisation of grid resources by mapping a number of jobs to grid resources. However, the heterogeneity of grid resources adds some challenges to the work of job scheduling, especially when jobs have dependencies which can be represented as Direct Acyclic Graphs (DAGs). It is widely recognised that scheduling m jobs to n resources with an objective to achieve a minimum makespan has shown to be NP-complete, requiring the development of heuristics. Although a number of heuristics are available for job scheduling optimisation, selecting the best heuristic to use in a given grid environment remains a difficult problem due to the fact that the performance of each original heuristic is usually evaluated under different assumptions. This paper evaluates 12 representative heuristics for dependent job scheduling under one set of common assumptions. The results are presented and analysed, which provides an even basis in comparison of the performance of those heuristics. To facilitate performance evaluation, a DAG simulator is implemented which provides a set of tools for DAG job configuration, execution, and monitoring. The components of the DAG simulator are also presented in this paper.

Evaluating Heuristics for Scheduling Dependent Jobs in Grid Computing Environments

2012 ◽  
pp. 1099-1113
Author(s):  
Geoffrey Falzon ◽  
Maozhen Li
Keyword(s):  
Performance Evaluation ◽  
Grid Computing ◽  
Job Scheduling ◽  
Critical Role ◽  
Difficult Problem ◽  
Acyclic Graphs ◽  
Computing Environments ◽  
Np Complete ◽  
Grid Resources ◽  
Direct Acyclic Graphs

Job scheduling plays a critical role in the utilisation of grid resources by mapping a number of jobs to grid resources. However, the heterogeneity of grid resources adds some challenges to the work of job scheduling, especially when jobs have dependencies which can be represented as Direct Acyclic Graphs (DAGs). It is widely recognised that scheduling m jobs to n resources with an objective to achieve a minimum makespan has shown to be NP-complete, requiring the development of heuristics. Although a number of heuristics are available for job scheduling optimisation, selecting the best heuristic to use in a given grid environment remains a difficult problem due to the fact that the performance of each original heuristic is usually evaluated under different assumptions. This paper evaluates 12 representative heuristics for dependent job scheduling under one set of common assumptions. The results are presented and analysed, which provides an even basis in comparison of the performance of those heuristics. To facilitate performance evaluation, a DAG simulator is implemented which provides a set of tools for DAG job configuration, execution, and monitoring. The components of the DAG simulator are also presented in this paper.

Evaluating Heuristics for Scheduling Dependent Jobs in Grid Computing Environments

2012 ◽  
pp. 31-46
Author(s):  
Geoffrey Falzon ◽  
Maozhen Li
Keyword(s):  
Performance Evaluation ◽  
Grid Computing ◽  
Job Scheduling ◽  
Critical Role ◽  
Difficult Problem ◽  
Acyclic Graphs ◽  
Computing Environments ◽  
Np Complete ◽  
Grid Resources ◽  
Direct Acyclic Graphs

Job scheduling plays a critical role in the utilisation of grid resources by mapping a number of jobs to grid resources. However, the heterogeneity of grid resources adds some challenges to the work of job scheduling, especially when jobs have dependencies which can be represented as Direct Acyclic Graphs (DAGs). It is widely recognised that scheduling m jobs to n resources with an objective to achieve a minimum makespan has shown to be NP-complete, requiring the development of heuristics. Although a number of heuristics are available for job scheduling optimisation, selecting the best heuristic to use in a given grid environment remains a difficult problem due to the fact that the performance of each original heuristic is usually evaluated under different assumptions. This paper evaluates 12 representative heuristics for dependent job scheduling under one set of common assumptions. The results are presented and analysed, which provides an even basis in comparison of the performance of those heuristics. To facilitate performance evaluation, a DAG simulator is implemented which provides a set of tools for DAG job configuration, execution, and monitoring. The components of the DAG simulator are also presented in this paper.

scholarly journals A Weight-based Query Forwarding Technique for Super-peer-based Grid Resource Discovery

2017 ◽  
Vol 7 (1) ◽  
pp. 1398-1404
Author(s):  
M. Mollamotalebi ◽  
R. Maghami ◽  
A. S. Ismail
Keyword(s):  
Response Time ◽  
Resource Discovery ◽  
Search Process ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Applications ◽  
Computing Environments ◽  
Grid Resources ◽  
Grid Resource Discovery ◽  
Super Peer

Grid computing environments include heterogeneous resources shared by a large number of computers to handle data and process intensive applications. The required resources must be accessible for the grid applications on demand, which makes resource discovery a critical service. In recent years, different techniques are provided to index and discover grid resources. Response time and message load during the search process highly affect the efficiency of resource discovery. This paper proposes a technique to forward the queries based on the resource types accessible through each neighbor in super-peer-based grid resource discovery approaches. The proposed technique is simulated in GridSim and the experimental results indicated that it is able to reduce the response time and message load during the search process especially when the grid environment contains a large number of nodes.

Resource Similarity, Market Commonality, and Spatial Distribution of Hotel Competitive Sets

2021 ◽  
pp. 109634802098857
Author(s):  
Zvi Schwartz ◽  
Timothy Webb
Keyword(s):  
Mathematical Model ◽  
Spatial Distribution ◽  
Performance Evaluation ◽  
Critical Role ◽  
Principal Agent ◽  
Large Dataset ◽  
Principal Agent Theory ◽  
Agent Theory ◽  
Performance And Evaluation

Index scores and competitive sets (compsets) play a critical role in the performance and evaluation of hotels. The reliance on these metrics has drawn skepticism in recent years as competitive sets may be opportunistically chosen, creating bias in performance evaluation. Drawing from the principal–agent theory and the theory of incentives, we explore whether the distance of the competitors chosen for a hotel’s compset influences revenue per available room (RevPAR) index scores. Based on the concepts of resource similarity and market commonality, we develop a novel mathematical model through which we empirically analyze a large dataset of 10,000 compsets. We find evidence that competitor distance influences index performance and that this relationship is bidirectional. Results show that hotels that outperform the competition may use distance to inflate RevPAR indices, while those that underperform may use distance to further reduce scores. These conflicting results may be reflected from the reverse motivations of the stakeholders.

scholarly journals Cooling-Efficient Job Scheduling in a Heterogeneous Grid Environment

2015 ◽  
Vol 69 ◽  
pp. 104-115
Author(s):  
Ahmad Abba Haruna ◽  
Low T. Jung ◽  
Nordin Zakaria ◽  
Jun Okitsu
Keyword(s):  
Job Scheduling ◽  
Grid Environment

Overcoming Complacency Through Quality Intelligence in Greek Higher Education

2020 ◽  
pp. 121-140
Author(s):  
Loukas Anninos
Keyword(s):  
Higher Education ◽  
Performance Evaluation ◽  
Critical Role ◽  
The State ◽  
Academic Leadership ◽  
Evolutionary Perspective ◽  
Institutional Improvement ◽  
University Performance ◽  
Institutional Initiatives

During the last decade, an intensification of evaluation at the Greek universities has been noted, encouraged by the state and institutional initiatives aiming to reform, modernize, and cultivate a culture of excellence. The progress that has been reported was facilitated by global developments that gradually strengthened the cultural and scientific foundations of university performance evaluation and set the foundations for continuous institutional improvement and transformation. However, the role of academic leadership is crucial if universities wish to fully embrace the concept of excellence in their operations and services not from an obligatory, but from an evolutionary perspective that would allow them to learn and improve. As Greek universities are currently in the process of quality accreditation, the chapter briefly presents the framework for quality accreditation in Greek universities and underlines the critical role of academic leadership for achieving accreditation and establishing a culture for sustainable excellence.

Balanced Job Scheduling Based on Ant Algorithm for Grid Network

2010 ◽  
Vol 2 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Nikolaos Preve
Keyword(s):  
Grid Computing ◽  
Ant Colony Optimization ◽  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Scheduling Algorithms ◽  
Experimental Results ◽  
Ant Algorithm ◽  
Entire System ◽  
Grid Environment ◽  
Grid Network

Job scheduling in grid computing is a very important problem. To utilize grids efficiently, we need a good job scheduling algorithm to assign jobs to resources in grids. The main scope of this article is to propose a new Ant Colony Optimization (ACO) algorithm for balanced job scheduling in the Grid environment. To achieve the above goal, we will indicate a way to balance the entire system load while minimizing the makespan of a given set of jobs. Based on the experimental results, the proposed algorithm confidently demonstrates its practicability and competitiveness compared with other job scheduling algorithms.

Resource Allocation Mechanism with New Models for Grid Environment

2013 ◽  
Vol 5 (2) ◽  
pp. 1-26
Author(s):  
Kuppani Sathish ◽  
A. Rama Mohan Reddy
Keyword(s):  
Resource Allocation ◽  
Waiting Time ◽  
Vital Role ◽  
Allocation Mechanism ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Resources ◽  
Utilization Cost ◽  
Resource Allocation Mechanism ◽  
Grid Resource Allocation

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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