CONSISTENCY AS A SERVICE: AUDITING CLOUD CONSISTENCY
Cloud storage services have become commercially popular due to their overwhelming advantages. To provide ubiquitous always-on access, a cloud service provider (CSP) maintains multiple replicas for each piece of data on geographically distributed servers. A key problem of using the replication technique in clouds is that it is very expensive to achieve strong consistency on a worldwide scale. In this paper, we first present a novel consistency as a service (CaaS) model, which consists of a large data cloud and multiple small audit clouds. In the CaaS model, a data cloud is maintained by a CSP, and a group of users that constitute an audit cloud can verify whether the data cloud provides the promised level of consistency or not. We propose a two-level auditing architecture, which only requires a loosely synchronized clock in the audit cloud. Then, we design algorithms to quantify the severity of violations with two metrics: the commonality of violations, and the staleness of the value of a read. Finally, we devise a heuristic auditing strategy (HAS) to reveal as many violations as possible. Extensive experiments were performed using a combination of simulations and a real cloud deployment to validate HAS.
Cloud storage services can be regarded as a typical service in cloud computing, which involves the delivery of data storage as a service, including database-like services and network attached storage, often billed on a utility computing basis, e.g., per gigabyte per month. Examples include Amazon SimpleDB1, Microsoft Azure storage2, and so on. By using the cloud storage services, the customers can access data stored in a cloud anytime and anywhere,using any device, without caring about a large amount of capital investment when deploying the underlying hardware infrastructures.
DISADVANTAGES OF EXISTING SYSTEM:
- Very Expensive.
- User cannot see the latest updates.
- Traffic enables during the updating of new one.
In cloud storage, consistency not only determines correctness but also the actual cost per transaction. In this paper, we present a novel consistency as a service (CaaS) model for this situation. The CaaS model consists of a large data cloud and multiple small audit clouds. The data cloud is maintained by a CSP, and an audit cloud consists of a group of users that cooperate on a job, e.g., a document or a project. A service level agreement (SLA) will be engaged between the data cloud and the audit cloud, which will stipulate what level of consistency the data cloud should provide, and how much (monetary or otherwise) will be charged if the data cloud violates the SLA.
ADVANTAGES OF PROPOSED SYSTEM:
- Audit cloud is identified by a unique ID.
- User can read and revise data’s at anywhere.
- Less Expensive.
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 512 MB(min)
Hard Disk - 40 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - LCD/LED
Operating system : Windows XP.
Coding Language : .Net
Data Base : SQL Server 2005
Tool : VISUAL STUDIO 2008.
Qin Liu, Guojun Wang, Member, IEEE, and Jie Wu, Fellow, IEEE., “Consistency as a Service: Auditing Cloud Consistency” IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, VOL. 11, NO. 1, MARCH 2014