Service discovery framework for distributed embedded real-time systems
Embedded systems are supporting the trend of moving away from centralised, high-cost products towards low-cost and high-volume products; yet, the non-functional constraints and the device heterogeneity can lead to system complexity. In this regard, Service-Oriented Architecture (SOA) is the best met...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Book Section |
| Published: |
IGI Global
2014
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/74713/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946002923&doi=10.4018%2f978-1-4666-6026-7.ch007&partnerID=40&md5=bea1a575f2b63bbe38c1fd9abef908b1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Embedded systems are supporting the trend of moving away from centralised, high-cost products towards low-cost and high-volume products; yet, the non-functional constraints and the device heterogeneity can lead to system complexity. In this regard, Service-Oriented Architecture (SOA) is the best methodology for developing a loosely coupled, dynamic, flexible, distributed, and cost-effective application. SOA relies heavily on services, and the Semantic Web, as the advanced form of the Web, handles the application complexity and heterogeneity with the help of ontology. With an ever-increasing number of similar Web services in UDDI, a functional description of Web services is not sufficient for the discovery process. It is also difficult to rank the similar services based on their functionality. Therefore, the Quality of Service (QoS) description of Web services plays an important role in ranking services within many similar functional services. Context-awareness has been widely studied in embedded and real-time systems and can also play an important role in service ranking as an additional set of criteria. In addition, it can enhance human-computer interaction with the help of ontologies in distributed and heterogeneous environments. In order to address the issues involved in ranking similar services based on the QoS and context-awareness, the authors propose a service discovery framework for distributed embedded real-time systems in this chapter. The proposed framework considers user priorities, QoS, and the context-awareness to enable the user to select the best service among many functional similar services. |
|---|