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Advanced Resource Discovery Protocol for Semantic-Enabled M-Commerce

Advanced Resource Discovery Protocol for Semantic-Enabled M-Commerce
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Author(s): Michele Ruta (Politecnico di Bari, Italy), Tommaso Di Noia (Politecnico di Bari, Italy), Eugenio Di Sciascio (Politecnico di Bari, Italy), Francesco Maria Donini (Università della Tuscia, Italy) and Giacomo Piscitelli (Politecnico di Bari, Italy)
Copyright: 2009
Pages: 12
Source title: Mobile Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): David Taniar (Monash University, Australia)
DOI: 10.4018/978-1-60566-054-7.ch222

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Abstract

New mobile architectures allow for stable networked links from almost everywhere; and more and more people make use of information resources for work and business purposes on mobile systems. Although technological improvements in the standardization processes proceed rapidly; many challenges; mostly aimed at the deployment of value-added services on mobile platforms; are still unsolved. In particular the evolution of wireless-enabled handheld devices and their capillary diffusion have increased the need for more sophisticated service discovery protocols (SDPs). Here we present an approach; which improves Bluetooth SDP; to provide m-commerce resources to the users within a piconet; extending the basic service discovery with semantic capabilities. In particular we exploit and enhance the SDP in order to identify generic resources rather than only services. We have integrated a “semantic layer” within the application level of the standard Bluetooth stack in order to enable a simple interchange of semantically annotated information between a mobile client performing a query and a server exposing available resources. We adopt a simple piconet configuration where a stable networked zone server; equipped with a Bluetooth interface; collects requests from mobile clients and hosts a semantic facilitator to match requests with available resources. Both requests and resources are expressed as semantically annotated descriptions; so that a semantic distance can be computed as part of the ranking function; to choose the most promising resources for a given request.

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