International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 137 - Number 8 |
Year of Publication: 2016 |
Authors: Sapna R. Kadam, B.M. Patil, V.M. Chandode |
10.5120/ijca2016908687 |
Sapna R. Kadam, B.M. Patil, V.M. Chandode . Improve Speed Efficiency and Maintain Data Integrity of Dynamic Big Data by using Map Reduce. International Journal of Computer Applications. 137, 8 ( March 2016), 5-12. DOI=10.5120/ijca2016908687
Cloud computing has rapid growth globally cause of the facet provided by the service not only scalability but also capacity management that subject to storage huge amount of data. Major issue will going to arrived at the time of storing this much bulky data on a cloud because data integrity may lost at the time of data retrieval.First, Anyone canister to challenge in the intention to verification of data integrity of certain file so that appropriate authentication process will going to miss between cloud service provider and third party auditor(TPA). Second, as the BLS signature obligated for fully dynamic updates of data over data blocks of fixed sized which causes re-computation and updating for an entire block of authenticator which origin not only higher storage but also communication overheads. In order to keep security as a vital issue because malicious party may scarf data at the time of data flows this can be addressed by means of symmetric key encryption. Similarly, in order to increase the speed and efficiency at the time of data retrieval for huge amount of data MapReduce plays vital role and the because of replication over the HDFS maintain data integrity with the full support of dynamic updates.