Knarig Arabshian

GloServ: global service discovery architecture

Due to the growth in ubiquitous computing technology in the past few years, the need for context-aware service discovery across wide area networks is becoming prevalent. We propose GloServ, which is a global service discovery architecture that locates services throughout wide and local area networks. It supports services encompassing different domains such as events, people or places. Services can be described semantically using the resource description framework (RDF) and can be queried using the RDF query language (RQL). GloServ hierarchically defines services using RDF schemas and assigns each service a URI according to its location within the hierarchy. The hierarchical architecture for GloServ is similar to how domain names are categorized in DNS. Service discovery can either be initiated by the user or by the system. For automated service discovery, users are detected with sensors and are presented with services available according to their preferences. Graphical user interfaces for querying data is dynamically generated through the processing of RDF data.

Providing emergency services in Internet telephony

Our primary focus is on emergency calling and notification. We describe the components of the existing emergency calling and notification systems and our proposed IP-based architectures, each of which uses the session initiation protocol (SIP) as the signaling framework. The architecture could increase speed, scalability, and functionality in communication services.

A SIP-based medical event monitoring system

The medical industry is transitioning to Internet-based communication as the field of telemedicine broadens to include medical event monitoring systems. A medical event monitor generates different types of messages and alerts for healthcare providers, institutions and patients. We describe how the Session Initiation Protocol (SIP), a signaling protocol for Internet conferencing, telephony, presence, event notification and instant messaging, can be used to create a medical event monitoring system. SIP can work on a variety of devices; its adoption as the protocol of choice for third generation wireless networks allows for a robust and scalable environment that can easily extend across institutions. First, we describe the basics of SIP and how it can be used for event notifications. Secondly, we describe the use of medical logic modules (MLMs) in a clinical event monitoring system and we propose a SIP medical event monitoring system that can combine the use of MLMs, such as the Arden Syntax, with SIP event notification. We also propose an alternate method of event notification with the use of XML filters to deliver only relevant notifications. Finally, we discuss the different types of devices and wireless protocols that can be incorporated within the system, creating an integrated architecture.

Ontology-Based user-defined rules and context-aware service composition system

The World Wide Web is becoming increasingly personalized as users provide more of their information on the Web. Thus, Web service functionality is becoming reliant on user profile information and context in order to provide user-specific data. In this paper, we discuss enhancements to SECE (Sense Everything, Control Everything), a platform for context-aware service composition based on user-defined rules. We have enhanced SECE to interpret ontology descriptions of services. With this enhancement, SECE can now create user-defined rules based on the ontology description of the service and interoperate within any service domain that has an ontology description. Additionally, it can use an ontology-based service discovery system like GloServ as its service discovery back-end in order to issue more complex queries for service discovery and composition. This paper discusses the design and implementation of these improvements.

Ontology-Based Service Discovery Front-End Interface for GloServ

This paper describes an ontology-based service discovery front-end interface for GloServ. GloServ is a service discovery engine, which is an ontology-based distributed service discovery system that allows sophisticated querying of services. The working implementation of the front-end interface demonstrates how GloServ can be used for different types of web service discovery. The front-end generates a search form from the service class ontology. It also allows multiple services to be queried for in a single search by generating cascaded forms for combined service queries. It then converts the input to a GloServ query and displays the results to the user in a coherent manner. The use cases that are demonstrated with this implementation are service discovery for location-based services, tagged services and collaborative search with other users.

A Framework for Personalized Context-Aware Search of Ontology-Based Tagged Data

We describe a framework for personalized context aware search of ontology-based tagged data. As more services are offered on the Web, it is becoming increasingly difficult for users to manage their content online. We propose a framework that performs context-aware search of tagged data using a tag ontology that includes context information in addition to tagged keywords in order to present more meaningful search results to users.

A Hybrid Hierarchical and Peer-to-Peer Ontology-based Global Service Discovery System

Current service discovery systems fail to span across the globe and they use simple attribute-value pair or interface matching for service description and querying. We propose a global service discovery system, GloServ, that uses the description logic Web Ontology Language (OWL DL). The GloServ architecture spans both local and wide area networks. It maps knowledge obtained by the service classification ontology to a structured peer-to-peer network such as a Content Addressable Network (CAN). GloServ also performs automated and intelligent registration and querying by exploiting the logical relationships within the service ontologies.

COnTag: A Framework for Personalized Context-Aware Search of Ontology-Based Tagged Data

As more web services are offered on the Web, it is becoming increasingly difficult for users to manage and search for online content, using only flat keyword searching. Users often forget how they tagged their data but may remember generic information such as the location they were in when they took the picture. We describe a framework for personalized context-aware search of ontology-based tagged data. The tag ontology leverages additional information on data coming from a user and a resource, besides the tagged keyword, in order to augment search information. The framework uses general concepts taken from PeCMan, a personal content manager and GloServ, an ontology-based global service discovery system to implement the front-end and back-end of the overall system.

Combining ontology queries with key word search in the GloServ service discovery system

GloServ is a global service discovery system which aggregates different types of services in a globally distributed network. It improves on current service discovery systems by scaling across a globally distributed network and allowing intelligent querying and registration of services. It uses the OWL DL sublanguage of the Web Ontology Language to classify services in an ontology and map knowledge obtained by the ontology onto a scalable hierarchical peer-to-peer network. We present an enhanced novel querying mechanism for service discovery which combines ontology queries with key word search.

User Interface Design in Semi-automated Ontology Construction

This paper describes the graphical user interface design and implementation of LexOnt, a semi-automatic ontology creation tool. LexOnt is built as a Protégé plugin and uses the Programmable Web directory as its corpus. Current semi-automatic ontology creation systems are domain specific and rely on already structured text. LexOnt, on the other hand, is built specifically for those who are not experts within a domain, but want to understand the domain on a high-level and create an ontology that describes it. Using well-known NLP algorithms, LexOnt generates a list of top terms and phrases from the Programmable Web corpus to enable users to find high-level features that distinguish one Programmable Web service category from another. To also aid non-experts in a domain, LexOnt relies on outside sources such as Wikipedia and Wordnet to help the user identify the important terms within a service category. We describe the details of LexOnts interactive interface that allows users to semi-automatically find top terms and phrases of a service domain and create ontology entities describing it with these features.