Generic-distributed framework for cloud services marketplace based on unified ontology.

Area of Science:

• Computer Science
• Cloud Computing
• Service-Oriented Architecture

Background:

• Cloud computing offers on-demand resources via a pay-as-you-use model.
• Current search engines struggle to efficiently discover adequate cloud services.
• A gap exists between cloud service providers and consumers in the marketplace.

Purpose of the Study:

• To present a generic, distrusted framework for an automated cloud services marketplace.
• To facilitate the discovery and selection of cloud services.
• To bridge the gap between cloud service providers and consumers.

Main Methods:

• Developed a generic framework for cloud service discovery and selection.
• Implemented two matching algorithms: dominant/recessive attributes and semantic similarity.
• Created a unified cloud service ontology for modeling services.

Main Results:

• The semantic similarity approach reduced execution time by 20% with comparable recall.
• The dominant and recessive attributes approach reduced execution time by 57% but with lower recall.
• The framework enables cloud services to be traded as utilities.

Conclusions:

• The proposed framework effectively automates cloud service discovery and selection.
• Different matching algorithms offer trade-offs between execution time and recall.
• This work represents a novel approach to a cloud services marketplace.