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Scalable Transaction Management with Snapshot Isolation for NoSQL Data Storage Systems
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Scalable Transaction Management with Snapshot Isolation for NoSQL Data Storage Systems

Category : Data Mining


Sub Category : DOTNET


Project Code : ITDCC09


Project Abstract

SCALABLE TRANSACTION MANAGEMENT WITH SNAPSHOT ISOLATION FOR NOSQL DATA STORAGE SYSTEMS

ABSTRACT

As a cloud computing systems refers to the demand delivery of IT resources via the internet with pay as you go pricing. A cloud offers many services to the end users such as software, infrastructure and platform go on. We develop scalable techniques for transaction management utilizing the snapshot isolation (SI) model. Because the SI model can lead to non-serializable transaction executions, we investigate two conflict detection techniques for ensuring serializability. To support scalability, we investigate system architectures and mechanisms in which the transaction management functions are decoupled from the storage system and integrated with the application-level processes. We present two system architectures and demonstrate their scalability under the scale-out model of cloud computing platforms. In the first system architecture all transaction management functions are executed in a fully decentralized manner by the application processes. The second architecture is based on a hybrid approach in which the conflict detection functions are performed by a dedicated service. We perform a comparative evaluation of these architectures using the TPC-C benchmark and demonstrate their scalability.

           

 

 

 

 

 

 

 

 

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

In existing new replica contacts all other existing replicas in the group and obtains information regarding the pending requests for which it was either a coordinator or a participant and the lock status for the items involved in these requests.

 

PROPOSED CONCEPT:-

The proposed approaches the focus was on evaluating the scalability of different approaches under the scale-out model and comparison of the service-based model and the decentralized model in terms of transaction throughput and scalability and comparison of the basic SI and the transaction serializability approaches based on the cycle-prevention and the cycle-detection techniques

EXISTING TECHNIQUE:-

Cycle-detection Techniques

 

PROPOSED TECHNIQUE:-

Cycle Prevention Approach.

TECHNIQUE DEFNITION:-

 

The cycle detection approach requires tracking all dependencies among transactions, i.e., anti-dependencies (both incoming and outgoing) among concurrent transactions, and write-read and write-write dependencies among nonconcurring transactions. We maintain this information in the form of a dependency serialization graph (DSG), in the global storage. Since an active transaction may form dependencies with a certain committed transaction, we need to retain information about such transactions in the DSG.

TECHNIQUE DEFNITION:-

 

When two concurrent transactions Ti and Tj have anti-dependency, one of them is aborted. This ensures that there can never be a pivot transaction, thus guaranteeing serializability. We implemented and evaluated the above approaches in both the fully decentralized model and the service-based model. The cycle prevention approach can sometimes abort transactions that may not lead to serialization anomalies.

DRAWBACKS:-

Not so efficient if there is heavy interaction between branches

Data should be carefully maintained

ADVANTAGES:-

This technique is very efficient.

We can store the data normally and efficiently.

 
 
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