International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 49 - Number 15 |
Year of Publication: 2012 |
Authors: Y. D. Jayaweera |
10.5120/7701-1052 |
Y. D. Jayaweera . Automatic File Indexing Framework: An Effective Approach to Resolve Dangling File Pointers. International Journal of Computer Applications. 49, 15 ( July 2012), 6-11. DOI=10.5120/7701-1052
Today managing files in a server system has the same magnitude as managing the World Wide Web due to the dynamic nature of the file system. Even searching for files over the file system is time consuming because finding a file on hard disk is a long-running task. Every file on the disk has to be read with dangling pointers to files which no longer exist because they have been changed, moved or deleted. This makes the user frustrated. The Automatic file indexing framework facilitates users to resolve file names and locate documents stored in file repositories. The main design objective of the framework is to maintain sub-indexes at the folder level that have the full knowledge of the revisions that are made at the folder level automatically. This research proposes a framework that manages the creation and maintenance of the file index, with the use of Resources Description Framework (RDF) and retrieval using semantic query languages i. e. SPARQL. The sub-indexes are maintained hierarchically starting from the leaf node to the root node recursively. The proposed framework will monitor the file system continuously and update individual folder descriptors (sub-indexes) stored on each node as the file system changes making the cached indexes resilient to any file changes. The framework is resilient of file or folder name changes. Further, the study explores avenues to build an offline semantic index that can be used by the clients to perform distribute file search without performing the search on the server itself. This is viable since the framework uses semantic languages to describe and build file descriptors that can easily integrate semantic indexing and hence this makes the index readily available for the Web.