Abstract: Distributed file systems are key building blocks for cloud computing applications based on the Map Reduce programming paradigm. In such file systems, nodes simultaneously serve computing and storage functions. Files can also be dynamically created, deleted, and appended. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the nodes. Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balancer is put under considerable workload that is linearly scaled with the system size, and may thus become the performance bottleneck and the single point of failure. In this proposal, a fully distributed load rebalancing algorithm is presented to cope with the load imbalance problem. Additionally, we aim to reduce network traffic or movement cost caused by rebalancing the loads of nodes as much as possible to maximize the network bandwidth available to normal applications. Moreover, as failure is the norm, nodes are newly added to sustain the overall system performance resulting in the heterogeneity of nodes. Exploiting capable nodes to improve the system performance is thus demanded. In the proposed system we also provide security for the data stored on cloud through encryption and decryption concepts.
Keywords: computing, distributed file systems, map reduce, Load imbalance