Cloud storage has become more popular due to their many advantages. To provide access everywhere, a cloud service provider maintains many replicas for each piece of data on geographically distributed servers. Using the replication technique in cloud it has one problem that is it is very costly to maintain strong consistency on a large scale. Here a Consistency as a Service (CaaS) model is presented, which consists of a large data cloud and audit service. CaaS model consists of a data cloud which is maintained by a CSP (Cloud Service Providers) and audit service to verify whether the data cloud provides the level of consistency or not. There is a two-level auditing architecture, which requires a secured synchronized clock in the cloud. Algorithms are designed to express the problems. Finally, a heuristic auditing strategy (HAS) is created to find as many violations as possible.

1. E. Anderson, X. Li, M. Shah, J. Tucek, and J. Wylie, "What consistency does your key-value store actually provide," in Proc. 2010 USENIX HotDep.
2. H. Wada, A. Fekete, L. Zhao, K. Lee, and A. Liu, "Data consistency properties and the trade-offs in commercial cloud storages: the consumers' perspective," in Proc. 2011 CIDR.
3. T. Kraska, M. Hentschel, G. Alonso, and D. Kossmann, "Consistency rationing in the cloud: pay only when it matters," in Proc. 2009 VLDB.
4. S. Esteves, J. Silva, and L. Veiga, "Quality-of-service for consistency of data geo-replication in cloud computing," Euro-Par 2012 Parallel Processing, vol. 7484, 2012.
5. D. Bermbach and S. Tai, "Eventual consistency: how soon is eventual?" in Proc. 2011 MW4SOC.
6. M. Rahman, W. Golab, A. AuYoung, K. Keeton, and J. Wylie, "Toward a principled framework for benchmarking consistency," in Proc. 2012 Workshop on HotDep.
7. M. Armbrust, A. Fox, R. Griffith, A. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, et al. , "A view of cloud computing," Commun. ACM, vol. 53, no. 4, 2010.
8. W. Golab, X. Li, and M. Shah, "Analyzing consistency properties for fun and profit," in Proc. 2011 ACM PODC.
9. Douglas B. Terry, Vijayan Prabhakaran, Ramakrishna Kotla, Mahesh Balakrishnan, Marcos K. Aguilera, Hussam Abu-Libdeh, " Consistency-Based Service Level Agreements for Cloud Storage ".
10. R. Anandhi, K. Chitra , "A Challenge in Improving the Consistency of Transactions in Cloud Databases – Scalability".
11. M. Rahman, W. Golab, A. AuYoung, K. Keeton, and J. Wylie,"Toward a principled framework for benchmarking consistency," in Proc. 2012 Workshop on HotDep.
12. A. Tanenbaum and M. Van Steen, Distributed Systems: Principles and Paradigms. Prentice Hall PTR, 2002.
13. W. Vogels, "Data access patterns in the Amazon. com technology platform," in Proc. 2007 VLDB.
14. "Pushing the CAP: strategies for consistency and availability,"Computer, vol. 45, no. 2, 2012.
15. G. DeCandia, D. Hastorun, M. Jampani, G. Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, P. Vosshall, and W. Vogels, "Dynamo: Amazon's highly available key-value store," in Proc. 2007 ACM SOSP.

Cloud Storage Consistency As A Service (caas) Two-level Auditing And Heuristic Auditing Strategy.