Journal of Information Processing Systems, Vol. 4, No.2, 2008
Sunil Kumar, Mahasweta Sarkar, Supraja Gurajala and John D. Matyjas
Page: 41~52, Vol. 4, No.2, 2008
10.3745/JIPS.2008.4.2.041
Keywords: Medium Access Control, MAC, Ad Hoc Networks, Multi Hop, QoS, Multimedia
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In this paper, we discuss a novel reservation-based, asynchronous MAC protocol called¡®Multi-rate Multi-hop MAC Protocol¡¯ (MMMP) for multi-hop ad hoc networks that provides QoS guarantees for multimedia traffic. MMMP achieves this by providing service differentiation for multirate real-time traffic (both constant and variable bit rate traffic) and guaranteeing a bounded end-to-end delay for the same while still catering to the throughput requirements of non real time traffic. In addition, it administers bandwidth preservation via a feature called ¡®Smart Drop¡¯ and implements efficient bandwidth usage through a mechanism called ¡®Release Bandwidth¡¯. Simulation results on the QualNet simulator indicate that MMMP outperforms IEEE 802.11 on all performance metrics and can efficiently handle a large range of traffic intensity. It also outperforms other similar state-of-the-art MAC protocols.
An Autonomic
Khaled Ragab
Page: 53~60, Vol. 4, No.2, 2008
10.3745/JIPS.2008.4.2.053
Keywords: Ubiquities Web Service Discovery Service, Registry Overlay Network P2P.
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The Web Services infrastructure is a distributed computing environment for service-sharing. Mechanisms for Web services Discovery proposed so far have assumed a centralized and peer-to-peer (P2P) registry. A discovery service with centralized architecture, such as UDDI, restricts the scalability of this environment, induces performance bottleneck and may result in single points of failure. A discovery service with P2P architecture enables a scalable and an efficient ubiquities web service discovery service that needs to be run in self-organized fashions. In this paper, we propose an autonomic -interleaving Registry Overlay Network (RgON) that enables web-services¡¯ providers/consumers to publish/discover services¡¯ advertisements, WSDL documents. The RgON, doubtless empowers consumers to discover web services associated with these advertisements within constant D logical hops over constant K physical hops with reasonable storage and bandwidth utilization as shown through simulation.
Developing Protege Plug-in: OWL Ontology Visualization using Social Network
Minsoo Kim and Minkoo Kim
Page: 61~66, Vol. 4, No.2, 2008
10.3745/JIPS.2008.4.2.061
Keywords: OWL visualization, Protege, Protege plug-in
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In recent years, numerous studies have been attempted to exploit ontology in the area of ubiquitous computing. Especially, some kinds of ontologies written in OWL are proposed for major issues in ubiquitous computing such like context-awareness. OWL is recommended by W3C as a descriptive language for representing ontology with rich vocabularies. However, developers struggle to design ontology using OWL, because of the complex syntax of OWL. The research for OWL visualization aims to overcome this problem, but most of the existing approaches unfortunately do not provide efficient interface to visualize OWL ontology. Moreover, as the size of ontology grows bigger, each class and relation are difficult to represent on the editing window due to the small size limitation of screen. In this paper, we present OWL visualization scheme that supports class information in detail. This scheme is based on concept of social network, and we implement OWL visualization plug-in on Protégé that is the most famous ontology editor.
Inverted Index based Modified Version of K-Means Algorithm for Text Clustering
Taeho Jo
Page: 67~76, Vol. 4, No.2, 2008
10.3745/JIPS.2008.4.2.067
Keywords: String Vector, K Means Algorithm, Text Clustering
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This research proposes a new strategy where documents are encoded into string vectors and modified version of k means algorithm to be adaptable to string vectors for text clustering. Traditionally, when k means algorithm is used for pattern classification, raw data should be encoded into numerical vectors. This encoding may be difficult, depending on a given application area of pattern classification. For example, in text clustering, encoding full texts given as raw data into numerical vectors leads to two main problems: huge dimensionality and sparse distribution. In this research, we encode full texts into string vectors, and modify the k means algorithm adaptable to string vectors for text clustering.
Neural Text Categorizer for Exclusive Text Categorization
Taeho Jo
Page: 77~86, Vol. 4, No.2, 2008
10.3745/JIPS.2008.4.2.077
Keywords: Disk Neural Text Categorizer, Text Categorization, NewsPage.com
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This research proposes a new neural network for text categorization which uses alternative representations of documents to numerical vectors. Since the proposed neural network is intended originally only for text categorization, it is called NTC (Neural Text Categorizer) in this research. Numerical vectors representing documents for tasks of text mining have inherently two main problems: huge dimensionality and sparse distribution. Although many various feature selection methods are developed to address the first problem, the reduced dimension remains still large. If the dimension is reduced excessively by a feature selection method, robustness of text categorization is degraded. Even if SVM (Support Vector Machine) is tolerable to huge dimensionality, it is not so to the second problem. The goal of this research is to address the two problems at same time by proposing a new representation of documents and a new neural network using the representation for its input vector.
