Reliability and Performance Models for Grid Computing

2010 ◽  
pp. 219-245 ◽  
Author(s):  
Yuan-Shun Dai ◽  
Jack Dongarra
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Optimization Problems ◽  
Data Dependence ◽  
Performance Models ◽  
Task Partitioning ◽  
Modeling And Analysis ◽  
Failure Correlation ◽  
And Performance

Grid computing is a newly developed technology for complex systems with large-scale resource sharing, wide-area communication, and multi-institutional collaboration. It is hard to analyze and model the Grid reliability because of its largeness, complexity and stiffness. Therefore, this chapter introduces the Grid computing technology, presents different types of failures in grid system, models the grid reliability with star structure and tree structure, and finally studies optimization problems for grid task partitioning and allocation. The chapter then presents models for star-topology considering data dependence and treestructure considering failure correlation. Evaluation tools and algorithms are developed, evolved from Universal generating function and Graph Theory. Then, the failure correlation and data dependence are considered in the model. Numerical examples are illustrated to show the modeling and analysis.

Reliability and Performance Models for Grid Computing

2012 ◽  
pp. 119-140
Author(s):  
Yuan-Shun Dai ◽  
Jack Dongarra
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Optimization Problems ◽  
Tree Structure ◽  
Data Dependence ◽  
Task Partitioning ◽  
Modeling And Analysis ◽  
Failure Correlation ◽  
And Performance

Grid computing is a newly developed technology for complex systems with large-scale resource sharing, wide-area communication, and multi-institutional collaboration. It is hard to analyze and model the Grid reliability because of its largeness, complexity and stiffness. Therefore, this chapter introduces the Grid computing technology, presents different types of failures in grid system, models the grid reliability with star structure and tree structure, and finally studies optimization problems for grid task partitioning and allocation. The chapter then presents models for star-topology considering data dependence and tree-structure considering failure correlation. Evaluation tools and algorithms are developed, evolved from Universal generating function and Graph Theory. Then, the failure correlation and data dependence are considered in the model. Numerical examples are illustrated to show the modeling and analysis.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

scholarly journals Exploration based Genetic Algorithm for Job Scheduling on Grid Computing

2016 ◽  
Vol 5 (3) ◽  
pp. 91-100
Author(s):  
Hanaa Abdelrahman ◽  
Mohammed Bakri Bashir ◽  
Adil Yousif
Keyword(s):  
Genetic Algorithm ◽  
Grid Computing ◽  
Large Scale ◽  
Job Scheduling ◽  
Optimization Problems ◽  
Scheduling Algorithm ◽  
Adaptive Method ◽  
Virtual Organizations ◽  
Good Effect ◽  
Exploration Process

Grid computing presents a new trend to distribute and Internet computing to coordinate large scale heterogeneous resources providing sharing and problem solving in dynamic, multi- institutional virtual organizations. Scheduling is one of the most important problems in computational grid to increase the performance. Genetic Algorithm is adaptive method that can be used to solve optimization problems, based on the genetic process of biological organisms. The objective of this research is to develop a job scheduling algorithm using genetic algorithm with high exploration processes. To evaluate the proposed scheduling algorithm this study conducted a simulation using GridSim Simulator and a number of different workload. The research found that genetic algorithm get best results when increasing the mutation and these result directly proportional with the increase in the number of job. The paper concluded that, the mutation and exploration process has a good effect on the final execution time when we have large number of jobs. However, in small number of job mutation has no effects.

scholarly journals Massively multi-user online platform for large-scale applications

2021 ◽  
Author(s):  
Allen Yen-Cheng Yu
Keyword(s):  
Grid Computing ◽  
High Performance ◽  
Large Scale ◽  
Distributed Applications ◽  
Service Architecture ◽  
Online Application ◽  
Online Platform ◽  
Massively Multiplayer Online Game ◽  
And Performance

Many large-scale online applications enable thousands of users to access their services simultaneously. However, the overall service quality of an online application usually degrades when the number of users increases because, traditionally, centralized server architecture does not scale well. In order to provide better Quality of Service (QoS), service architecture such as Grid computing can be used. This type of architecture offers service scalability by utilizing heterogeneous hardware resources. In this thesis, a novel design of Grid computing middleware, Massively Multi-user Online Platform (MMOP), which integrates the Peer-to-Peer (P2P) structured overlays, is proposed. The objectives of this proposed design are to offer scalability and system design flexibility, simplify development processes of distributed applications, and improve QoS by following specified policy rules. A Massively Multiplayer Online Game (MMOG) has been created to validate the functionality and performance of MMOP. The simulation results have demonstrated that MMOP is a high performance and scalable servicing and computing middleware.

An Efficient Resources Management Model and Task Scheduling Algorithm in Grid Computing

2011 ◽  
Vol 50-51 ◽  
pp. 526-530 ◽  
Author(s):  
Xiao Bo Gao
Keyword(s):  
Grid Computing ◽  
Task Scheduling ◽  
Resource Sharing ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Management Model ◽  
Network Computing ◽  
Resources Management ◽  
Task Scheduling Algorithm ◽  
And Task

From the perspective of resource sharing, grid computing is a system ranging from small kind of network system for home using to large-scale network computing systems even to the Internet. The management of resources in the grid environment becomes very complex as these resources are distributed geographically, heterogeneous in nature, and each having their own resource management policies and different access as well as cost models. In this paper, we bring forward an efficient resources management model and task scheduling algorithm in grid computing. The simulation results show that the proposed algorithm achieves resource load balancing, and can be applied to the optimization of task scheduling successfully.

Mobility-Aware Grid Computing

2011 ◽  
pp. 2626-2630
Author(s):  
Konstantinos Katsaros ◽  
George C. Polyzos
Keyword(s):  
Mobile Computing ◽  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Resource Constraints ◽  
Mobile Users ◽  
Mobile Grid ◽  
Computing Environments ◽  
Hoc Networks ◽  
Simulation Signal

Grid computing has emerged as a paradigm for coordinated resource sharing and problem solving in dynamic, multiinstitutional virtual organizations (Foster, 2001). A grid computing system is essentially a large-scale distributed system designed to aggregate resources from multiple sites, giving to users the opportunity to take advantage of enormous computational, storage, or bandwidth resources that would otherwise be impossible to attain. Current applications of grid computing focus on computational-expensive processing of large volumes of scientific data, for example, for earthquake simulation, signal processing, cancer research, and pattern search in DNA sequences. At the same time, the recent advances in mobile and wireless communications have resulted in the availability of an enormous number of mobile computing devices such as laptop PCs and PDAs (personal digital assistants). Thus, it is natural to extend the idea of resource sharing to mobile and wireless computing environments. Resource-sharing collaboration between mobile users appears as a promising research direction toward the alleviation of the inherent resource constraints present in mobile computing environments. Either in the context of mobile ad hoc networks (MANETs) or in wireless networks based on fixed infrastructure (i.e., cellular networks, wireless local area networks (WLANs), small- or large-scale communities of mobile users can form mobile grid systems and collaborate in order to either achieve a common goal (otherwise impossible to achieve) or simply overcome their individual limitations. In the following, we highlight the fundamental issues toward the realization of a computational mobile grid system.

Prototype Design of Decision Supports for GRID Clearinghouse Service Framework

2008 ◽  
Vol 12 (6) ◽  
pp. 523-528
Author(s):  
Johannes K. Chiang ◽  
◽  
Kiekang Chao
Keyword(s):  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Critical Issue ◽  
Trading Behavior ◽  
Distributed Environment ◽  
Service Architecture ◽  
New Business ◽  
Service Data ◽  
Prototype Design

Grid Computing, as an emerging technology, facilitates computer resource sharing, distribution over the Internet. Large-scale collaboration and engineering development for GRID Computing has been engaged world wide. The vigorous momentum of the technology has captured great business attention. The resources management in such large-scale distributed environment becomes a great challenge, and will be the critical issue before GRID deployed into commercial operation while resource allocation and use need to be properly managed in realistic and economic justification. This study aims to elaborate a new business model regarding service trading and billing. The Grid Architecture for Computational Economy (GRACE) framework can be the fundamental framework which reveals resource trading behavior. This paper explored the resource trading models and the way to integrate them into a uniform computing environment. Thereby the concepts and Architecture is to be investigated and extended with Economic Service Architecture (ESA). Last but not least, this paper carries out necessary Service Interfaces and Service Data Entities.

Large Scale Plant Optimization Problems

1988 ◽  
Author(s):  
Paul Cronin ◽  
Harry Woerde ◽  
Rob Vasbinder
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Plant Optimization
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