A Light-Weight Dynamic Data Replication in Cloud Using Prioritization Based Optimization Algorithm

M. Amutha and Dr.R. Sugumar


In this work, our research focuses on minimizing the Cloud storage consumption by minimizing data replication while meeting the data reliability requirement. This paper proposed optimized data replication nodes in following steps, the user requests computational time, trust and threshold average values are calculated initially and based on the average of parameter values the requests are prioritized in queue. The prioritized queue consists of both higher and lower priority queue. The higher priority queue is only taken for the optimized data replication. The krill herd optimization algorithm optimizes the high priority queue data. Then the data centers replicated through the replication managers using optimized data. The proposed work performance results shows the reduction in user waiting time, reduction in latency, increasing data availability, reducing the communication cost, integrating data from multiple sites and minimizing bandwidth consumption.

Keywords: Prioritization, Optimization, Data Replication, Data Center, High Priority Queue.

Volume: 5 | Issue: 1

Pages: 469-482

Paper ID : IJPPAS105147

Issue Date: February , 2017

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