Architecture of Grid Resource Allocation Management Based on QoS

Wang, Xiaozhi; Luo, Junzhou

doi:10.1007/978-3-540-24680-0_11

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…Plestys et al (2007) emphasized on the relative importance of Grid quality of service (QoS) along with the development of GRID technology because of the concept of GRID service, the multiplicity of users' demands, and the heterogeneity of Grid resources. Sun and Wu (2007) conducted a comprehensive study of QoS (Wang & Luo, 2004) of distributed computing, specifically on grid computing where the necessity of distributed sharing and coordination tends to the extreme. They started at QoS policies, and then concentrated on technical characteristics of the enforcement of the policies and performance optimization under each policy.…”

Section: Introductionmentioning

confidence: 99%

An application of TOPSIS method for task scheduling algorithm in grid computing environment

Kohzadian¹,

Harounabadi²,

Sadeghzadeh³

2014

10.5267/j.dsl

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Today, the world facing with huge flood of data and the recent advances in computer technology have provided the capability to process significant amount of data. On the other hand, analyzing the information requires resources that most institutions do not have, independently. To handle such circumstances, grid computing has emerged as an important research area where the calculation of distributed computing and clustering are different. In this study, we propose a grid computing architecture as a set of protocols that use the cumulative knowledge of computers, networks, databases and scientific instruments based on the implementation of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique. The results of the implementation of the proposed algorithm on grid systems indicate the superiority of the proposed approach in terms of validation criteria scheduling algorithms, such as task completion time and the performance compared with some alternative method.

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Section: Introductionmentioning

confidence: 99%

An application of TOPSIS method for task scheduling algorithm in grid computing environment

Kohzadian¹,

Harounabadi²,

Sadeghzadeh³

2014

10.5267/j.dsl

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“…The scheduling algorithms undertake the subtasks distribution duty among the grid resources. The scheduling is conducted considering the quality of service and it is tried the subtasks are distributed among the resources in the scheduling time as maximum QoS will be achieved [2][3][4]. The reliability is one of the important QoS parameters that causes the efficiency improvement in the grid environment [5].…”

Section: Introductionmentioning

confidence: 99%

Proposing a Formal Model for Performance Improvement in Grid Environment

Amirshekari¹,

Harounabadi²

2013

IJCA

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The cooperation of the geographical distributed resources for solving the great problems is called the computing grid. An efficiency scheduling system is necessary to reach the aim. In the proposed method, RMS divides every task in to several subtasks. Then, the appropriate resources which can create the more reliability and lower execution time for the task were chosen in the system. It means the reliability and execution time parameters were optimized in the proposed model. In the method, the operator can distinguish the Importance of the parameters in the system for choosing the resources until the choosing is conducted considering the significance degree. Multiple attribute decision making (MADM) were used to choose the resources optimumly. In this paper, the task scheduling by RMS and the task execution within grid resources are modeled using coloured Petri nets.In addition, an example of proposed model for a sample grid environment is constructed and analysed using CPN Tools. The results demonstrated reliability improvement compared to the previous model.

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“…In Daniel and Chronopoulos (2003), Park (2003), Rana et al (2002), the authors investigate resource allocation problems in the context of protocol design. The problem from an architectural point of view is studied in Czajkowski et al (1999), Foster et al (2000), Wang and Luo (2004). Security assurance in Grid/Cluster job scheduling is studied in Song et al (2006), Xie and Qin (2008).…”

Section: Introductionmentioning

confidence: 99%

Structural properties of the optimal resource allocation policy for single-queue systems

Yang¹,

Bhulai²,

Mei³

2011

Ann Oper Res

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This paper studies structural properties of the optimal resource allocation policy for single-queue systems. Jobs arrive at a service facility and are sent one by one to a pool of computing resources for parallel processing. The facility poses a constraint on the maximum expected sojourn time of a job. A central decision maker allocates the servers dynamically to the facility. We consider two models: a limited resource allocation model, where the allocation of resources can only be changed at the start of a new service, and a fully flexible allocation model, where the allocation of resources can also change during a service period. In these two models, the objective is to minimize the average utilization costs whilst satisfying the time constraint. To this end, we cast these optimization problems as Markov decision problems and derive structural properties of the relative value function. We show via dynamic programming that (1) the optimal allocation policy has a work-conservation property, and (2) the optimal number of servers follows a step function with as extreme policy the bang-bang control policy. Moreover, (3) we provide conditions under which the bang-bang control policy takes place. These properties give a full characterization of the optimal policy, which are illustrated by numerical experiments.

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Architecture of Grid Resource Allocation Management Based on QoS

Cited by 7 publications

References 8 publications

An application of TOPSIS method for task scheduling algorithm in grid computing environment

An application of TOPSIS method for task scheduling algorithm in grid computing environment

Proposing a Formal Model for Performance Improvement in Grid Environment

Structural properties of the optimal resource allocation policy for single-queue systems

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