Data Synchronization Methods Based on ShuffleNet and Hypercube for Networked Information Systems
David J. Houck, K. K. Leung, Peter M. Winkler · 2006
Abstract – In contrast to a typical single source of data updates in Internet applications, data files in a networked information system are often distributed, replicated, accessed and updated by multiple nodes. Due to concurrent updates, replicated data files must be synchronized. For certain applications, stringent concurrency control must be employed to ensure data integrity, while for other applications, periodic data synchronization may enable very efficient data sharing. For the latter applications, this paper devises the ShuffleNet and hypercube schemes for data synchronization in such networked information systems. Their performance in terms of update delay, processing complexity, failure tolerance and growth complexity is examined. Our results reveal that the ShuffleNet and hypercube scheme provide identical maximum update delay and similar processing complexity. However, as the number of nodes in the system changes (e.g., due to failure or temporary out of service for maintenance), the hypercube scheme maintains all existing synchronization sessions and greatly simplifies system administration overhead such as moving files from node to node for the purpose of data synchronization. The ShuffleNet scheme does provide a higher degree of failure tolerance for global data files, but the hypercube scheme provides more than adequate failure tolerance. Lastly, a generalization of the hypercube scheme, based on the ideas of shift registers, is also proposed for systems where the number of nodes is a perfect power of 2. I.