Abstract:Grids have emerged as paradigms for the next generation parallel and distributed computing. Computational Grid can be defined as large-scale high-performance distributed computing environments that provide access to high-end computational resources. Grid scheduling is the process of scheduling jobs over grid resources. Improving overall system performance with a lower turn around time is an important objective of Grid scheduling. In this paper a Priority Based Scheduling Algorithm is proposed. In this algorith… Show more
“…In the future, our work can be carried forward in the following three directions. First, other models of grid scheduling (e.g., workflow model [28], priority model [5], etc.) can be studied with the CRO approach.…”
Section: Resultsmentioning
confidence: 99%
“…GGRB is responsible for scheduling. It possesses all necessary information about the tasks and resources and acts like a database of the grid [5]. A grid operates in time intervals.…”
“…In the future, our work can be carried forward in the following three directions. First, other models of grid scheduling (e.g., workflow model [28], priority model [5], etc.) can be studied with the CRO approach.…”
Section: Resultsmentioning
confidence: 99%
“…GGRB is responsible for scheduling. It possesses all necessary information about the tasks and resources and acts like a database of the grid [5]. A grid operates in time intervals.…”
“…This is achieved by using a grid scheduler. A grid scheduler is different from local scheduler in that a local scheduler only manages a single site or cluster and usually owns the resource [2]. There are three generalized stages in the scheduling procedure of the Grid computing.…”
Grid Computing is a collection of computing and storage resources that are collected from multiple administrative domains. Grid resources can be applied to reach a common goal. Since computational grids enable the sharing and aggregation of a wide variety of geographically distributed computational resources, an effective task scheduling is vital for managing the tasks. Efficient scheduling algorithms are the need of the hour to achieve efficient utilization of the unused CPU cycles distributed geographically in various locations. The existing job scheduling algorithms in grid computing are mainly concentrated on the system's performance rather than the user satisfaction. This research work presents a new algorithm that mainly focuses on better meeting the deadlines of the statically available jobs as expected by the users. This algorithm also concentrates on the better utilization of the available heterogeneous resources.
“…GGRB is responsible for scheduling. It possesses all necessary information about the jobs and resources and acts like a database of the grid [5]. Grid operates in an interval-based manner.…”
Section: Introductionmentioning
confidence: 99%
“…A grid usually consists of five parts: clients, the Global and Local Grid Resource Brokers (GGRB and LGRB), Grid Information Server (GIS), and resource nodes [5] (see Fig. 1).…”
Grid computing collects geographically dispersed resources ranging from laptops to supercomputers to compute tasks requested by clients. Grid scheduling, i.e., assigning tasks to resources, is an NPhard problem, and thus, metaheuristic methods are employed to find the optimal solutions. In this paper, we propose a Chemical Reaction Optimization (CRO) algorithm for the grid scheduling problem. CRO is a population-based metaheuristics mimicking the interactions between molecules in a chemical reaction. We compare the CRO approach with four generally acknowledged metaheuristics, and show that CRO performs the best.
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