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Resource Selection for Tasks with Time Requirements Using Spectral Clustering
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Resource Selection for Tasks with Time Requirements Using Spectral Clustering

Category : Grid Computing


Sub Category : DOTNET


Project Code : ITDGC03


Project Abstract

RESOURCE SELECTION FOR TASKS WITH TIME REQUIREMENTS USING SPECTRAL CLUSTERING

 

 

ABSTRACT

 

Grid computing is a major part of resources assignments in distributed computing environments, the resource-related performance used to serve the tasks and their utilization efficiency. We focus on the case of tasks with fixed but not strict time requirements, given in the form of a requested start and finish time. We propose an algorithm for assigning tasks to resources that minimizes the violations of the tasks’ time requirements while simultaneously maximizing the resources’ utilization efficiency for a given number of resources. The exact time scheduling of the tasks on the resources is then decided by taking into account the time constraints. The proposed scheme exploits concepts derived from graph partitioning, and group’s together tasks so as to 1) minimize the time overlapping of the tasks assigned to a given resource and 2) maximize the time overlapping among tasks assigned to different resources. The partitioning is performed using a spectral clustering methodology through normalized cuts. Experimental results show that the proposed algorithm outperforms other scheduling algorithms for different values of the granularity and the load of the task requests.

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

In existing, clustering is a emerging as a new paradigm for solving large scale problem.

Time interval allocated to a task may differ, to some degree, from requested one. The tasks compete for resources with each other and a task often takes more execution time than the requested duration.        

PROPOSED CONCEPT:-

In this system using an interval scheduling approach to resolve the resource assignments between start and end times.

The number of resources and the objective is to find minimum cost schedule that not reject any tasks. Fixed number of resources and a predefined profit associated with the successful execution of each task.

EXISTING ALGORITHM:-

Earliest Deadline First (EDF) and Least Laxity First (LLF) .

PROPOSED ALGORITHM:-

Interval scheduling algorithm.

ALGORITHM DEFINITION:-

The LLF (Least Laxity First) scheduling algorithm assigns a priority to a task according to its executing urgency.  least time to go is a dynamic scheduling algorithm used in real-time operating systems to place processes in a priority queue.

ALGORITHM DEFINITION:-

The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be executed.

DRAWBACKS:-

A lack of cost optimization.

In accurate deadline process.

ADVANTAGES:-

Cost optimization between start and end time.

To reduce work load while resource deadline.

 
 
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