RPLB: A Replica Placement Algorithm in Data Grid with Load Balancing
Journal: The International Arab Journal of Information Technology (Vol.13, No. 6)Publication Date: 2016-11-01
Authors : Kingsy Rajaretnam; Manimegalai Rajkumar; Ranjith Venkatesan;
Page : 635-634
Keywords : Replica placement; load balancing; ENU; data grid; data replication.;
Abstract
Data grid is an infrastructure built based on internet which facilitates sharing and management of geographically distributed data resources . Data sharing in data grids is enhanced through dynamic data replication methodologies to reduce access latencies and bandwidth consumption. Replica placement is to create and place duplicate copies of the most needed file in beneficial locations in the data grid network. To reduce the make span i.e., total job execution time, storage consumption and Effective Network Usage (ENU) in data grids, a new method for replica placement is introduced. In this proposed method, all the nodes in the same region are grouped together and replica is placed in the highest degree and highest frequency node in the region. The node to place replica should be load balanced in terms of access and storage. The proposed dynamic Replica Placement algorithm with Load Balancing (RPLB) is tested using OptorSim simulator, which is developed by European Data Grid Projects . In this paper, two variants of the proposed algorithm RPLB, namely RPLBfrequency and RPLBdegree are also presented. The comparative analysis of all the three proposed algorithms is also presented in this paper. A Graphical User Interface (GUI) is designed as an interface to OptorSim to get all values for grid configuration file, job configuration file and paramete rs configuration file. Simulation results reveal that the performance of the proposed
methodology is better in terms of makespan, storage consumption and replication count when compared to the existing algorithms in the literature
Other Latest Articles
- An Intelligent Water Drop Algorithm for Optimizing Task Scheduling in Grid Environment
- IHPProxy: Improving the Performance of HPProxy by Adding Extra Hot-Points
- Modified Bee Colony Optimization for the Selection of Different Combination of Food Sources
- An Adaptive Weighted Fuzzy Mean Filter Based on Cloud Model
- Prediction of Part of Speech Tags for Punjabi using Support Vector Machines
Last modified: 2019-11-14 16:35:14