Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases

Multimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity....

Full description

Bibliographic Details
Main Authors: Bo Yang, Ali R. Hurson
Format: Article
Language:English
Published: Hindawi Limited 2005-01-01
Series:Mobile Information Systems
Online Access:http://dx.doi.org/10.1155/2005/317136
id doaj-987c815b982c4a748954742005dcf114
record_format Article
spelling doaj-987c815b982c4a748954742005dcf1142021-07-02T02:40:42ZengHindawi LimitedMobile Information Systems1574-017X1875-905X2005-01-011425327310.1155/2005/317136Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia DatabasesBo Yang0Ali R. Hurson1Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802-6106, USADepartment of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802-6106, USAMultimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity. To provide an efficient platform for multimedia retrieval, we propose to cluster ad hoc multimedia databases based on their semantic contents, and construct a virtual hierarchical indexing infrastructure overlaid on the mobile databases. This content-aware clustering scheme uses a semantic-aware framework as the theoretical foundation for data organization. Several novel techniques are presented to facilitate the representation and manipulation of multimedia data in ad hoc networks: 1) using concise distribution expressions to represent the semantic similarity of multimedia data, 2) constructing clusters based on the semantic relationships between multimedia entities, 3) reducing the cost of content-based multimedia retrieval through the restriction of semantic distances, and 4) employing a self-adaptive mechanism that dynamically adjusts to the content and topology changes of the ad hoc networks. The proposed scheme is scalable, fault-tolerant, and efficient in performing content-based multimedia retrieval as demonstrated in our combination of theoretical analysis and extensive experimental studies.http://dx.doi.org/10.1155/2005/317136
collection DOAJ
language English
format Article
sources DOAJ
author Bo Yang
Ali R. Hurson
spellingShingle Bo Yang
Ali R. Hurson
Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
Mobile Information Systems
author_facet Bo Yang
Ali R. Hurson
author_sort Bo Yang
title Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
title_short Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
title_full Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
title_fullStr Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
title_full_unstemmed Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases
title_sort similarity-based clustering strategy for mobile ad hoc multimedia databases
publisher Hindawi Limited
series Mobile Information Systems
issn 1574-017X
1875-905X
publishDate 2005-01-01
description Multimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity. To provide an efficient platform for multimedia retrieval, we propose to cluster ad hoc multimedia databases based on their semantic contents, and construct a virtual hierarchical indexing infrastructure overlaid on the mobile databases. This content-aware clustering scheme uses a semantic-aware framework as the theoretical foundation for data organization. Several novel techniques are presented to facilitate the representation and manipulation of multimedia data in ad hoc networks: 1) using concise distribution expressions to represent the semantic similarity of multimedia data, 2) constructing clusters based on the semantic relationships between multimedia entities, 3) reducing the cost of content-based multimedia retrieval through the restriction of semantic distances, and 4) employing a self-adaptive mechanism that dynamically adjusts to the content and topology changes of the ad hoc networks. The proposed scheme is scalable, fault-tolerant, and efficient in performing content-based multimedia retrieval as demonstrated in our combination of theoretical analysis and extensive experimental studies.
url http://dx.doi.org/10.1155/2005/317136
work_keys_str_mv AT boyang similaritybasedclusteringstrategyformobileadhocmultimediadatabases
AT alirhurson similaritybasedclusteringstrategyformobileadhocmultimediadatabases
_version_ 1721342920503590912