LURR as a Grid Service

2012 ◽  
Vol 155-156 ◽  
pp. 940-944
Author(s):  
Feng Liang ◽  
Hao Ming Guo ◽  
Sheng Wei Yi ◽  
Shi Long Ma
Keyword(s):  
Resource Allocation ◽  
Web Service ◽  
Parallel Applications ◽  
Grid Service ◽  
Response Ratio ◽  
Globus Toolkit ◽  
Execution Engine ◽  
Grid Resources ◽  
Grid Based

Load-Unload Response Ratio (LURR) is one of the parallel applications for seismological analysis and requires large amount of computation resources for simulation. In order to accelerate the LURR calculation and optimize the resource allocation, this paper presents a REST style Web Service LURR-Grid. Based on Globus Toolkit, AIS and MyProxy, LURR-Grid is able to accept LURR job request and conduct LURR calculation tasks on Grid Resources. Using MDS in Globus for resources and GRAM5 for job execution engine, LURR-Grid schedule the task using the SED algorithm. The Experiments proves the LURR-Grid is scalable and efficient in resource allocation.

A Grid Flow Management System for Resource Allocation Problem

2013 ◽  
Vol 706-708 ◽  
pp. 1985-1988
Author(s):  
Li Li Ding ◽  
Xiao Ling Wang ◽  
Zheng Wei Wang
Keyword(s):  
Resource Allocation ◽  
System Performance ◽  
Management System ◽  
Allocation Problem ◽  
Grid Service ◽  
Resource Allocation Problem ◽  
Flow Management ◽  
Rule Based ◽  
Simulated Environment ◽  
Grid Resources

This paper describes a framework for the grid flow management system in resource allocation problem based on the autonomous manager grid service (AMGS). We develop a user agent which is able to estimate the scoring rule based on grid resources attributes without human intervention, since agents are autonomous and intelligent in behavior. The reverse auction protocol involving an iterative algorithm for solving the resource allocation problem is also present. We implement the new protocol in a simulated environment and study its economic efficiency and its effect on the grid system performance.

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

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.

Implementation of Grid Resources and Services Based on WSRF

2011 ◽  
Vol 225-226 ◽  
pp. 642-645
Author(s):  
Luo Zhong ◽  
Gan Zuo ◽  
Hua Zhu Song
Keyword(s):  
Web Service ◽  
Standard Protocol ◽  
Resource Model ◽  
Grid Resource ◽  
Service Resource ◽  
Grid Resources ◽  
Implementation Steps

Traditional web service resource hasn't the concept of state and exists many limitations in application. WS-Resource of WSRF solved this problem. This paper elaborated the principal standard protocol specifications in WSRF, analyzed WS-resources characteristics, gave the implementation steps of grid resource and service, and finally validated the superiority of WSRF resource model with an example.

Benchmarking Grid Applications for Performance and Scalability Predictions

2010 ◽  
pp. 89-121 ◽  
Author(s):  
Radu Prodan ◽  
Farrukh Nadeeem ◽  
Thomas Fahringer
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Real World ◽  
Experimental Results ◽  
Problem Size ◽  
Grid Environment ◽  
Computational Costs ◽  
Grid Applications ◽  
Grid Resources ◽  
Grid Site

Application benchmarks can play a key role in analyzing and predicting the performance and scalability of Grid applications, serve as an evaluation of the fitness of a collection of Grid resources for running a specific application or class of applications (Tsouloupas & Dikaiakos, 2007), and help in implementing performance-aware resource allocation policies of real time job schedulers. However, application benchmarks have been largely ignored due to diversified types of applications, multi-constrained executions, dynamic Grid behavior, and heavy computational costs. To remedy these, the authors present an approach taken by the ASKALON Grid environment that computes application benchmarks considering variations in the problem size of the application and machine size of the Grid site. Their system dynamically controls the number of benchmarking experiments for individual applications and manages the execution of these experiments on different Grid sites. They present experimental results of our method for three real-world applications in the Austrian Grid environment.

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