scholarly journals Porting of Scientific Applications to Grid Computing on GridWay

2005 ◽  
Vol 13 (4) ◽  
pp. 317-331 ◽  
Author(s):  
J. Herrera ◽  
E. Huedo ◽  
R.S. Montero ◽  
I.M. Llorente
Keyword(s):  
Genetic Algorithm ◽  
Resource Management ◽  
Rapid Development ◽  
Management Systems ◽  
Scientific Applications ◽  
Grid Environment ◽  
Distributed Resource Management ◽  
Programming Paradigm ◽  
Bioinformatics Application ◽  
Management Application

The expansion and adoption of Grid technologies is prevented by the lack of a standard programming paradigm to port existing applications among different environments. The Distributed Resource Management Application API has been proposed to aid the rapid development and distribution of these applications across different Distributed Resource Management Systems. In this paper we describe an implementation of the DRMAA standard on a Globus-based testbed, and show its suitability to express typical scientific applications, like High-Throughput and Master-Worker applications. The DRMAA routines are supported by the functionality offered by the GridWay2framework, which provides the runtime mechanisms needed for transparently executing jobs on a dynamic Grid environment based on Globus. As cases of study, we consider the implementation with DRMAA of a bioinformatics application, a genetic algorithm and the NAS Grid Benchmarks.

Enterprise distribution routing optimization with soft time windows based on genetic algorithm

2021 ◽  
pp. 1-11
Author(s):  
Kaixian Gao ◽  
Guohua Yang ◽  
Xiaobo Sun
Keyword(s):  
Genetic Algorithm ◽  
Customer Satisfaction ◽  
Optimization Problems ◽  
Rapid Development ◽  
Time Windows ◽  
Theory And Practice ◽  
Routing Problem ◽  
Logistics Industry ◽  
Routing Optimization ◽  
A Company

With the rapid development of the logistics industry, the demand of customer become higher and higher. The timeliness of distribution becomes one of the important factors that directly affect the profit and customer satisfaction of the enterprise. If the distribution route is planned rationally, the cost can be greatly reduced and the customer satisfaction can be improved. Aiming at the routing problem of A company’s vehicle distribution link, we establish mathematical models based on theory and practice. According to the characteristics of the model, genetic algorithm is selected as the algorithm of path optimization. At the same time, we simulate the actual situation of a company, and use genetic algorithm to plan the calculus. By contrast, the genetic algorithm suitable for solving complex optimization problems, the practicability of genetic algorithm in this design is highlighted. It solves the problem of unreasonable transportation of A company, so as to get faster efficiency and lower cost.

A Heuristic Resource Management Method in Grid Computing Environment

2011 ◽  
Vol 50-51 ◽  
pp. 521-525
Author(s):  
Xian Mei Fang
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Collaborative Research ◽  
Ant Colony Optimization Algorithm ◽  
Computing Environment ◽  
Grid Resource ◽  
Grid Environment ◽  
Load Imbalance ◽  
The World ◽  
Management Method

Grid is an emerging infrastructure which enables effective coordinate access to various distributed computing resources in order to serve the needs of collaborative research and work across the world. Grid resource management is always a key subject in the grid computing. We first analyze the resource management in the grid computing environment, then according to the load imbalance question in the ant colony optimization algorithm, propose an improved algorithm that suits to be used in the grid environment.

Sign in / Sign up

Export Citation Format

Share Document