Journal of Computer Science

Solving Two Deadlock Cycles through Neighbor Replication on Grid Deadlock Detection Model

Noriyani Mohd Zin, A. Noraziah, Ahmed N. Abdalla and Ainul Azila CheFauzi

DOI : 10.3844/jcssp.2012.265.271

Journal of Computer Science

Volume 8, Issue 2

Pages 265-271


A data grid is compose of hundreds of geographically distributed computers and storage resources usually locate under different places and enables users to share data and other resources. Problem statement: Data replication is one of the mechanisms in managing data grid architecture that receive particular attention since it can provide efficient access to data, fault tolerance, reduce access latency and also can enhance the performance of the system. However, during transaction deadlock may occur that can reduce the throughput by minimizing the available resources, so it becomes an important resource management problem in distributed systems. Approach: The Neighbor Replication on Grid Deadlock Detection (NRGDD) transaction model has been developed to handle two deadlock cycle problems on grid. By deploying this method, the transactions communicate with each other by passing the probe messages. The victim message has been used to detect the deadlock when the number of waiting resource by other transaction is highest and become as the cause of deadlock occurs. In addition, this transaction must be aborted to solve the problem. Results: NRGDD transaction model are able to detect and solve more than one cycle of deadlocks. Conclusion: NRGDD has resolve the deadlock problem by sending the minimum number of probes message to detect the deadlock and it can resolve the deadlock to ensure the transaction can be done smoothly.


© 2012 Noriyani Mohd Zin, A. Noraziah, Ahmed N. Abdalla and Ainul Azila CheFauzi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.