A Transparent Service Replication Mechanism for Clouds

File replication in distributed environment has been discussed by many researchers, but the issues like transparency and their impact on the overall system performance, are rarely focused, when deployed in the cloud environment. Distributed computing started with the cluster followed by the grid and is now in the era of cloud computing, where most of the services are accessed, by few clicks. In cloud, services are invoked on demand and there is no need of dedicated resources. It demands the availability of resources(i.e. logical resources), in order to fulfill the user requirements. To make this feasible, on-demand availability of logical resources (LR) is preferred. This work proposes an "OndemandLogical Resource Replication Scheme" (OLRRS) for file replication. OLRRS approach provides migration, access and performance transparency to the system, thereby ensuring the migration decisions about the files. It is also responsible for replicating the file, from one peer server to the other peer server, when the total number of request, on a peer server, for transferring a file reaches the threshold value. The scheme is simulated on JAVA platform and tested on a private cloud. A comparative study of the proposed approach with the Request Reply and Request Reply (RR) Acknowledgement (RRA)protocol is presented, showing the significant reduction by 37.5% to 58%, in terms of total number of messages exchanged for replication.

[1]  Luhong Diao,et al.  Lazy update propagation for data replication in cloud computing , 2010, 5th International Conference on Pervasive Computing and Applications.

[2]  Sushil Jajodia,et al.  Secure Dynamic Fragment and Replica Allocation in Large-Scale Distributed File Systems , 2003, IEEE Trans. Parallel Distributed Syst..

[3]  Wei-Tek Tsai,et al.  Service Replication Strategies with MapReduce in Clouds , 2011, 2011 Tenth International Symposium on Autonomous Decentralized Systems.

[4]  Satoshi Matsuoka,et al.  File Clustering Based Replication Algorithm in a Grid Environment , 2009, 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid.

[5]  Franco Zambonelli,et al.  Experience of adaptive replication in distributed file systems , 1996, Proceedings of EUROMICRO 96. 22nd Euromicro Conference. Beyond 2000: Hardware and Software Design Strategies.

[6]  John Paul Walters,et al.  Replication-Based Fault Tolerance for MPI Applications , 2009, IEEE Transactions on Parallel and Distributed Systems.

[7]  Weimin Zheng,et al.  Enabling Cloud Storage to Support Traditional Applications , 2010, 2010 Fifth Annual ChinaGrid Conference.

[8]  Harry G. Perros,et al.  Service Performance and Analysis in Cloud Computing , 2009, 2009 Congress on Services - I.

[9]  Chung-Ta King,et al.  File replication for enhancing the availability of parallel I/O systems on clusters , 1999, ICWC 99. IEEE Computer Society International Workshop on Cluster Computing.

[10]  Ling Zheng,et al.  Design and Research on Private Cloud Computing Architecture to Support Smart Grid , 2011, 2011 Third International Conference on Intelligent Human-Machine Systems and Cybernetics.

[11]  Anna Hác.  A Distributed Algorithm for Performance Improvement Through File Replication, File Migration and Process Migration , 1986, SIGMETRICS Perform. Evaluation Rev..

[12]  Richard T. Hurley,et al.  File Migration and File Replication: A Symbiotic Relationship , 1996, IEEE Trans. Parallel Distributed Syst..

[13]  Alex Delis,et al.  Selective replication for content management environments , 2005, IEEE Internet Computing.

[14]  Alfred Z. Spector,et al.  Performing remote operations efficiently on a local computer network , 1981, SOSP.

[15]  Garret Swart,et al.  Granularity and semantic level of replication in the Echo distributed file system , 1990, [1990] Proceedings. Workshop on the Management of Replicated Data.

[16]  H. Rao,et al.  A transparent service for synchronized replication across loosely-connected file systems , 1995, Second International Workshop on Services in Distributed and Networked Environments.