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Friday, 2 February 2018

Consistency as a Service Auditing Cloud Consistency(2014)

Consistency as a Service Auditing Cloud Consistency(2014)

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 realcloud deployments to validate HAS.
Ø 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.
Ø The cloud service provider (CSP) stores data replicas on multiple geographically distributed servers.
Ø Where a user can read stale data for a period of time. The domain name system (DNS) is one of the most popular applications that implement eventual consistency. Updates to a name will not be visible immediately, but all clients are ensured to see them eventually.
Ø The replication technique in clouds is that it is very expensive to achieve strong consistency.
Ø Hard to verify replica in the data cloud is the latest one or not.
Ø In this paper, we presented a consistency as a service (CaaS) model and a two-level auditing structure to help users verify whether the cloud service provider (CSP) is providing the promised consistency, and to quantify the severity of the violations, if any.
Ø With the CaaS model, the users can assess the quality of cloud services and choose a right CSP among various candidates, e.g, the least expensive one that still provides adequate consistency for the users’ applications.
Ø Do not require a global clock among all users for total ordering of operations.
Ø The users can assess the quality of cloud services.
Ø choose a right CSP
Ø Among various candidates, e.g, the least expensive one that still provides adequate consistency for the users’ applications.
1.     System Module
2.     User operation table
3.     Local Consistency Auditing
4.     Global Consistency Auditing
System Module:
*    In the first module, we develop the System Module with User Module, Admin Module, and Auditor Module.
*    In user module, user should register their details and get the secret key for login and user can upload the file regarding the auditing. In user module, the user uploaded files can be stored in cloud database. Auditor can view the file from the database it can be much secured.
*    In admin module admin can view all the user details; user uploads details, and TPA activities regarding the auditing strategy.
*    In auditor module, auditor can do the auditing based on the heuristic auditing strategy. It relates with document verification. Auditor can check the auditing file he can reject or accept the file he can revise the report and check whether it’s good or bad. And auditor can give revision report like accept or waiting. If status in accept means user can view the file else status is waiting means user cant view the file.
User Operation Table:
Each user maintains a UOT for recording local operations. Each record in the UOT is described by three elements: operationlogical vector, and physical vector. While issuing an operation, a user will record this operation, as well as his current logical vector and physical vector, in his UOT. Each user will maintain a logical vector and a physical vector to track the logical and physical time when an operation happens, resepectively.
Local Consistency Auditing:
Local consistency auditing is an online algorithm. In this module, each user will record all of his operations in his UOT. While issuing a read operation, the user will perform local consistency auditing independently.
Global Consistency Auditing:
Global consistency auditing is an offline algorithm. Periodically, an auditor will be elected from the audit cloud to perform global consistency auditing. In this case, all other users will send their UOTs to the auditor for obtaining a global trace of operations. After executing global auditing, the auditor will send auditing results as well as its vectors to all other users. Given the auditor’s vectors, each user will know other users’ latest clocks up to global auditing.
Ø System                          :         Pentium IV 2.4 GHz.
Ø Hard Disk                      :         40 GB.
Ø Floppy Drive                 :         1.44 Mb.
Ø Monitor                         :         15 VGA Colour.
Ø Mouse                            :         Logitech.
Ø Ram                               :         512 Mb.
Ø Operating system           :         Windows XP/7.
Ø Coding Language         :,
Ø Tool                                  :         Visual Studio 2010
Ø Database                        :         SQL SERVER 2008

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