الفهرس 
Research MotivationOnly 14 pages are availabe for public view
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Abstract
Substantial number of vendors are offering their applications as Cloud Services (CS) to leverage the benefits of Cloud Computing (CC). Businesses and
individuals have to select the CS that suits their requirements from a large pool
of services. Consequently, there is an increasing demand for enhancing such a
time-consuming and error-prone task.
This thesis proposes CSRDS, a semantic-based system that allows the registration, discovery and selection of cloud services. The main building blocks of
the proposed system include: Hybrid matchmaking of CSs, metadata semantic
similarity model, semantic-based business-oriented request-service matchmaking algorithm and CS selection based on non-functional requirements.
Despite its efficiency, the proposed CSRDS system provides the same set of
services to all users, with no consideration of users interest or history. Motivated by the fact that the cloud users appreciate customized recommendations,
we propose CSRec, a personalized reputation-based QoS-aware recommender
system for CSs. Its main building blocks include: Feedback-based CS evaluation, hybrid collaborative filtering approach for personalized CS recommendation, new users similarity measure, dynamically built user profile, reputation
calculation for CSs and 3-D justification for the recommended CSs.
The key enabler to the realization of the proposed work is the proposed CS
ontology, a comprehensive full-fledged CS domain ontology with querying capabilities. It serves as a knowledge base for the proposed systems.
Extensive experimental evaluation is conducted in order to assess our proposed work. In order to carry out reliable evaluation, three real-world service
datasets are used. The evaluation metrics include matchmaking, prediction and
set recommendation metrics. The proposed work is compared to benchmark approaches. Case studies demonstrate that the proposed system is feasible, effective and relevant. Experimental results show that the proposed system has superior performance against the traditional approaches in real use-cases. The performance enhancement is investigated under different parameter settings.
Besides, the evaluation of the introduced CS ontology consists of three
processes. First, its coverage, consistency and expressiveness were verified via
semantic reasoner and semantic modeling. Second, its feasibility was confirmed
via prototype implementation while its practicability was validated via case
study. Finally, the ontology quality evaluation metrics prove that CS ontology
captures a comprehensive, consistent, rich, accurate and relevant representation
of the CS domain and that its concepts are interpretable.