Abstract
One of the main challenges in Grid computing is eff icient allocation of resources (CPU-hours, network bandwidth) to the tasks submitted by users. In our previous work a technique to allocate resources in a grid environment using predicted data has been proposed. We propose utilization of the predicted data the resources were classified into three types; they ar e permanent resources, semi-permanent and sporadic resources. These types of resources may become available for a time that is either higher than the dwe lling time or lower than the dwelling time in a grid envi ronment. As the nature features are not known in su ch classification and then allocation mechanism, the p erformance cannot be increased further. In order to avoid such problem, in this study, a prediction model and an allocation factor are introduced. These paramet ers are determined for the sporadic type and semi-perma nent type of resources and they are used in the fuz zybased resource allocation mechanism. The incorporation of these parameters in the resource allocation leads to a remarkable resource utilization rate and makes pan. This can be observed from the simulation and comparative results. From the results, it can be sa id that the proposed resource allocation mechanism has proved the performance in a dynamic environment.
Highlights
Grid Computing is a form of distributed computing that involves coordination and sharing of computing application, data storage or network resources across dynamic and geographically dispersed organizations. (Rafee and Rahimzadeh, 2009; Richard et al, 2008; Vijaya et al, 2009; Abba et al, 2012)
Firstly we describe the dataset and its generation, secondly we analyze the results and the technique is compared with the existing resource allocation techniques using the performance measures utilization rate, failure rate and makespan (Hao et al, 2008; Foster et al, 2006; Poonguzhali and Shanmugavel, 2011)
The mechanism introduced a new classification scheme based on dwelling time of the grid resources in this past time slots
Summary
Grid Computing is a form of distributed computing that involves coordination and sharing of computing application, data storage or network resources across dynamic and geographically dispersed organizations. (Rafee and Rahimzadeh, 2009; Richard et al, 2008; Vijaya et al, 2009; Abba et al, 2012). Grid Computing is a form of distributed computing that involves coordination and sharing of computing application, data storage or network resources across dynamic and geographically dispersed organizations. Grid supports researchers and scientists from diverse organizations to share information, instruments, data and compute and storage resources dynamically in a flexible and secure manner (Vijaya et al, 2009; Puri and Dev, 2012). It is a reliable technology for the process of making scheduling decisions involving allocating jobs to resources over multiple administrative domains. Both the availability and capability of computational resources will exhibit dynamic behavior (Yien et al, 2011; Wankar, 2008)
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