scholarly journals IRMM: An Integrated Resource Management Model for Grid Computing

2019 ◽  
Vol 8 (3) ◽  
pp. 6691-6696
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Heterogeneous Systems ◽  
Cost Models ◽  
Maximum Throughput ◽  
Grid Resource ◽  
Network Resource ◽  
Heterogeneous Objects ◽  
Resource Broker ◽  
Grid Resource Management

Grid computing is a collection of heterogeneous systems or heterogeneous objects that are geographically distributed over a network. Resource management is a process in which various activities like allocation of resources and scheduling are performed for handling issues like load balancing, reliability, scalability, maximum, throughput, minimum expectation time and security. There are several factors that make resource management difficult as different system may have different requirements, properties, conditions and different access and cost models. Resource management in Grid is the method of identifying requirements, finding corresponding resources to the applications, allocating those matching resources, scheduling and monitoring. In Grid resource management resource broker plays the very important role. Users communicate with a resource broker to access the grid information. Resource broker discover the resource that are available and negotiates with their owners or their agents to get the reservation of resources. Number of approaches exists through which one can develop grid resource management systems. In this paper a new architectural model has been implemented for grid resource management which is based on the characteristics of both the Economical model and Hierarchical model.

Ant colony optimization algorithm for load balancing in grid computing

2012 ◽  
Author(s):  
Ku Ruhana Ku-Mahamud ◽  
Aniza Mohamed Din
Keyword(s):  
Resource Management ◽  
Load Balancing ◽  
Grid Computing ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Computing System ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Grid Resource ◽  
Grid Resource Management

Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources. This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. The proposed algorithm is known as the enhance ant colony optimization (EACO). The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. The resource allocation problem is modelled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element. The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job. EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form. The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job.Resources with high pheromone value are selected to process the submitted jobs. Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization. Experimental results show that EACO produced better grid resource management solution.

New grid resource management framework for mixed types of workloads

2010 ◽  
Vol 30 (8) ◽  
pp. 2197-2201
Author(s):  
Yang LIU ◽  
Kai HAN ◽  
Jian-ping FAN
Keyword(s):  
Resource Management ◽  
Grid Resource ◽  
Management Framework ◽  
Grid Resource Management ◽  
Mixed Types

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.

A Constellation Model for Grid Resource Management

2005 ◽  
pp. 263-272 ◽  
Author(s):  
Yinfeng Wang ◽  
Xiaoshe Dong ◽  
Xiuqiang He ◽  
Hua Guo ◽  
Fang Zheng ◽  
...  
Keyword(s):  
Resource Management ◽  
Grid Resource ◽  
Grid Resource Management

Credit in the Grid Resource Management

2005 ◽  
pp. 725-731
Author(s):  
Manfu Ma ◽  
Jian Wu ◽  
Shuyu Li ◽  
Dingjian Chen ◽  
Zhengguo Hu
Keyword(s):  
Resource Management ◽  
Grid Resource ◽  
Grid Resource Management

scholarly journals VRM: a failure-aware Grid resource management system

2008 ◽  
Vol 5 (4) ◽  
pp. 215 ◽  
Author(s):  
Lars Olof Burchard ◽  
Hans Ulrich Heiss ◽  
Barry Linnert ◽  
Joerg Schneider ◽  
Cesar A.F. De Rose
Keyword(s):  
Resource Management ◽  
Management System ◽  
Grid Resource ◽  
Resource Management System ◽  
Grid Resource Management
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