A Semantic Service Discovery Network for Large-Scale Ubiquitous Computing Environments

Abstract

This paper presents an efficient semantic service discovery scheme called UbiSearch for a large-scale ubiquitous computing environment. A semantic service discovery network in the semantic vector space is proposed where services that are semantically close to each other are mapped to nearby positions so that the similar services are registered in a cluster of resolvers. Using this mapping technique, the search space for a query is efficiently confined within a minimized cluster region while maintaining high accuracy in comparison to the centralized scheme. The proposed semantic service discovery network provides a number of novel features to evenly distribute service indexes to the resolvers and reduce the number of resolvers to visit. Our simulation study shows that UbiSearch provides good semantic searchability as compared to the centralized indexing system. At the same time, it supports scalable semantic queries with low communication overhead, balanced load distribution among resolvers for service registration and query processing, and personalized semantic matching.

Mitigating the ICA Attack against Rotation-Based Transformation for Privacy Preserving Clustering

“…In addition to these applications, it easy to recall and extend other applications from the literature such like those in [8] and [9] in which the privacy of clustering (data or location information) can be of a great benefit.…”

Towards a Semantic and Dynamic Cluster based Web Service Discovery System for Ubiquitous Environments

“…Despite the fact that availability and rapidity of access are guaranteed with systems using centralized directories (Chen et al, 2006), (Hwang et al, 2007), these systems suffer from problems like SPOF and bottleneck as the number of registration and discovery queries increases. To address the scalability issues related to centralized architectures, solutions have been proposed dealing mainly with decentralization of directory nodes (Kang et al, 2007), (Xu et al, 2008), (Gao and Steenkiste, 2004), (Kim et al, 2005), (Liu et al, 2002). Kim et al proposed a fully distributed architecture by electing for every service requestor or provider, K volunteer nodes (directory nodes) to which publication and discovery queries are sent (Kim et al, 2005).…”

“…Problems of SPOF and bottleneck are thus avoided but this decentralization has its cost because voluntary nodes are announced by flooding the query and even in case of updating the volunteers list, flooding is used. To avoid the flooding problem, Xu et al and Kang et al proposed web service discovery systems based on a clustered architecture that reduces the search space and thus avoids overloading the network (Kang et al, 2007), (Xu et al, 2008). To add semantic search capability, Kang et al proposed a clustering method based on semantic similarity where each cluster contains descriptions of the most semantically similar services.…”

“…"Ubiquitous computing is a technology in which invisible computers are embedded and connected with all things so that anyone can communicate, exchange and share information anywhere, anytime" (Kang et al, 2007). Currently, we are surrounded by computers, mobile phones and personal digital assistants (PDA).…”

Survey of Semantic Similarity Measures in Pervasive Computing

“…The subsumption relation in a common ontology (Bandara et al 2007) is the tool used for measuring the semantic similarity between the symbolic attributes of the query and the available services. The semantics of each attribute of the query and services, as described by an ontology with "is-a" and "part-of" relations, is shared by all nodes of the PCS (Kang et al 2007). The semantic similarity measure between attributes is thus given as follows:…”