Moldable Job Allocation for Handling Resource Fragmentation in Computational Grid

2011 ◽  
pp. 58-71
Author(s):  
Kuo-Chan Huang ◽  
Po-Chi Shih ◽  
Yeh-Ching Chung
Keyword(s):  
System Performance ◽  
Computational Grid ◽  
Grid Environment ◽  
Allocation Policy ◽  
Job Allocation ◽  
Parallel Jobs ◽  
Parallel Job ◽  
Resource Fragmentation ◽  
Job Scheduler ◽  
Grid Resources

In a computational Grid environment, a common practice is to try to allocate an entire parallel job onto a single participating site. Sometimes a parallel job, upon its submission, cannot fit in any single site due to the occupation of some resources by running jobs. How the job scheduler handles such situations is an important issue which has the potential to further improve the utilization of Grid resources, as well as the performance of parallel jobs. This paper adopts moldable job allocation policies to deal with such situations in a heterogeneous computational Grid environment. The proposed policies are evaluated through a series of simulations using real workload traces. The moldable job allocation policies are also compared to the multi-site co-allocation policy, which is another approach usually used to deal with the resource fragmentation issue. The results indicate that the proposed moldable job allocation policies can further improve the system performance of a heterogeneous computational Grid significantly.

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

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.

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.

Reliability Based Scheduling Model (RSM) for Computational Grids

2012 ◽  
pp. 37-54
Author(s):  
Zahid Raza ◽  
Deo P. Vidyarthi
Keyword(s):  
Data Exchange ◽  
Large Scale ◽  
A Priori ◽  
Dynamic Environment ◽  
Computational Grid ◽  
Computational Grids ◽  
Scheduling Model ◽  
Reliability Computation ◽  
Grid Resources ◽  
Maximum Reliability

Computational Grid attributed with distributed load sharing has evolved as a platform to large scale problem solving. Grid is a collection of heterogeneous resources, offering services of varying natures, in which jobs are submitted to any of the participating nodes. Scheduling these jobs in such a complex and dynamic environment has many challenges. Reliability analysis of the grid gains paramount importance because grid involves a large number of resources which may fail anytime, making it unreliable. These failures result in wastage of both computational power and money on the scarce grid resources. It is normally desired that the job should be scheduled in an environment that ensures maximum reliability to the job execution. This work presents a reliability based scheduling model for the jobs on the computational grid. The model considers the failure rate of both the software and hardware grid constituents like application demanding execution, nodes executing the job, and the network links supporting data exchange between the nodes. Job allocation using the proposed scheme becomes trusted as it schedules the job based on a priori reliability computation.

A Security Prioritized Computational Grid Scheduling Model

2011 ◽  
pp. 90-100
Author(s):  
Rekha Kashyap ◽  
Deo P. Vidyarthi
Keyword(s):  
Scheduling Algorithm ◽  
Computational Grid ◽  
Security Requirement ◽  
Computational Power ◽  
Grid Scheduling ◽  
System Utilization ◽  
Scheduling Model ◽  
Grid Resources

Grid supports heterogeneities of resources in terms of security and computational power. Applications with stringent security requirement introduce challenging concerns when executed on the grid resources. Though grid scheduler considers the computational heterogeneity while making scheduling decisions, little is done to address their security heterogeneity. This work proposes a security aware computational grid scheduling model, which schedules the tasks taking into account both kinds of heterogeneities. The approach is known as Security Prioritized MinMin (SPMinMin). Comparing it with one of the widely used grid scheduling algorithm MinMin (secured) shows that SPMinMin performs better and sometimes behaves similar to MinMin under all possible situations in terms of makespan and system utilization.

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.

Efficient Job Scheduling in Computational Grid Systems Using Wind Driven Optimization Technique

2018 ◽  
Vol 9 (1) ◽  
pp. 49-59
Author(s):  
Tarun Kumar Ghosh ◽  
Sanjoy Das
Keyword(s):  
Job Scheduling ◽  
Scheduling Algorithm ◽  
Optimization Technique ◽  
Computational Grid ◽  
Grid System ◽  
Swarm Optimization ◽  
Grid Systems ◽  
Geographically Distributed ◽  
Job Scheduler ◽  
Computational Resources

Computational Grid has been employed for solving complex and large computation-intensive problems with the help of geographically distributed, heterogeneous and dynamic resources. Job scheduling is a vital and challenging function of a computational Grid system. Job scheduler has to deal with many heterogeneous computational resources and to take decisions concerning the dynamic, efficient and effective execution of jobs. Optimization of the Grid performance is directly related with the efficiency of scheduling algorithm. To evaluate the efficiency of a scheduling algorithm, different parameters can be used, the most important of which are makespan and flowtime. In this paper, a very recent evolutionary heuristic algorithm known as Wind Driven Optimization (WDO) is used for efficiently allocating jobs to resources in a computational Grid system so that makespan and flowtime are minimized. In order to measure the efficacy of WDO, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are considered for comparison. This study proves that WDO produces best results.

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