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A Hybrid Semantic Knowledge Integration and Sharing Approach for Distributed Smart Environments.

Furkh Zeshan1, Adnan Ahmad1, Abdel-Haleem Abdel-Aty2

  • 1Department of Computer Science, Lahore Campus, COMSATS University Islamabad, Lahore P.O. Box 54000, Pakistan.

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Summary
This summary is machine-generated.

This study introduces a hybrid framework to improve service discovery in distributed systems. It addresses limitations in context-aware modeling and Quality of Service (QoS) for more accurate results.

Keywords:
context-awarenessknowledge sharingquality of servicesemantic service matchmakingsmart systems

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Area of Science:

  • Distributed Systems and Pervasive Computing
  • Service-Oriented Architecture (SOA)
  • Ontology Engineering

Background:

  • Integrating numerous heterogeneous smart objects in distributed systems is challenging.
  • Existing approaches struggle with context-awareness, Quality of Service (QoS), and incomplete domain knowledge.
  • Service-Oriented Architecture (SOA) is used for smart object integration, but faces limitations in modeling complex interactions.

Purpose of the Study:

  • To propose a novel semantic and logic-based formal framework for enhanced service discovery.
  • To address limitations in current frameworks regarding context-aware modeling, QoS, and uncertainty.
  • To improve the accuracy of discovering the best service among heterogeneous candidates.

Main Methods:

  • Development of a hybrid (semantic and logic-based) formal framework.
  • Incorporation of context-awareness, Quality of Service (QoS) attributes, user priorities, grouping, and value type direction.
  • Modeling of incomplete or partial domain knowledge during ontology engineering.

Main Results:

  • The proposed framework demonstrates improved accuracy in discovering the most suitable service.
  • Experimental results validate the effectiveness of the hybrid approach in overcoming existing limitations.
  • Enhanced consideration of context, QoS, and domain knowledge leads to better service selection.

Conclusions:

  • The developed hybrid framework offers a more robust solution for service discovery in complex distributed systems.
  • Addressing the nuances of context-aware modeling and QoS significantly enhances system performance.
  • This approach provides a foundation for more intelligent and efficient integration of smart objects.