A Decentralized Periodic Replication Strategy Based on Knapsack Problem

Abstract

Data grids provide services and infrastructures for data-intensive applications that need to access to huge amount of data stored at distributed locations around the world. The size of these data can reach hundreds of petabytes scale in many applications. Ensuring an efficient and fast access to such massive data is a challenge that must be addressed. Replication is a key technique used in data grids to improve data access efficiency. Replication also provides high availability, decreased bandwidth consumption, improved fault tolerance and enhanced scalability. In this paper, we propose a new decentralized replication strategy for dynamic data grids, called DPRSKP which stands for Decentralized Periodic Replication Strategy based on Knapsack Problem. Our goal is to select the best candidate files for replication and to place them in the best locations assuming limited storage for replicas. The problem isformulated according to the knapsack problem. Our proposed strategy includes LRU and LFU strategies. The obtained experiment results, using OptorSim, show that our strategy outperforms other replication strategies in terms of response time and bandwidth consumption.