Concurrent programming vs. concurrency control: shared events or shared data

Simultaneous access of a shared record by multiple transactions leads to conflicts while writing. Such scenario generates the problems like lost update, dirty read, nonrepeatable read etc . In such a case, transaction need to be rolled back to get the system into a consistent state. To handle these conflicts Multiversion Concurrency control (MVCC) is used. MVCC has the ability to avoid the read-write conflicts by performing the read operations using the older version when the write request is in progress. When the multiple write operation concurrently executes then the transaction is aborted or rolled back. To address the problem of rollbacks, a methodology using the Precedence Graph generation based algorithm to reschedule the sequence of the transaction is proposed. In the proposed methodology whenever there is a system failure or network failure the transaction need not be started again, rather it is partially rolled back. The proposed methodology is executed and compared with the other MVCC approached on same set of transactions defined on shared and non shared data items. It is observed that the proposed methodology achieves better execution time as compared to the methods available in the literature

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Verification and Identification Approach to Maintain MVCC in Cloud Computing

International Journal of Cloud Applications and Computing ◽

10.4018/ijcac.2017100103 ◽

2017 ◽

Vol 7 (4) ◽

pp. 41-59 ◽

Cited By ~ 1

Author(s):

Niharika Singh ◽

Upasana Lakhina ◽

Ajay Jangra ◽

Priyanka Jangra

Keyword(s):

Concurrency Control ◽

Database Systems ◽

Data File ◽

Data Consistency ◽

Service Environment ◽

Shared Data ◽

Efficient Access ◽

Multiple Processes ◽

Identification Approach ◽

Set Up

MultiVersion concurrency control is maintained over transactional database systems for secure, fast and efficient access to the shared data file implementation scenario. Most of the services and application offered in cloud world are real-time, which entails optimized compatibility service environment between master and slave clusters. In the paper, offered methodology supports replication and triggering methods intended for data consistency and dynamicity. Here, cluster based communication is set up for processing. Intercommunication among different clusters is administered through middleware besides slave intra-communication is handled by verification and identification protection. The proposed approach incorporates resistive flow to handle high impact systems that identifies and verifies multiple processes. Statistical analysis determines that the new scheme reduces the overheads from different master and slave servers as they are co-located in clusters which allow increased horizontal and vertical scalability of resources.

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