Indiana University-Purdue University Indianapolis (IUPUI) / This dissertation proposes a framework (TruSStReMark - Trust-based Service Selection and Recommendation for Online Software Marketplaces) to model, quantify, and monitor trust of software services and to perform trust-based service selection and recommendations. It provides methods to analyze and aggregate external reviews, pertaining to specific QoS attributes, of software services by performing subjective logic-based operations. This framework, first, defines trust of a software service using theory of belief and extends the multi-level software specifications to represent the trust-based attributes. It, then, proposes enhancements to two prevalent algorithms for selecting and recommending software services from a marketplace. Finally, the performances of the enhanced selection and recommendation algorithms are improved by parallelizing them. When compared with the prevalent Content-based and Collaborative filtering-based approaches, the results show that, the TruSStReMark is able to produce better results in terms of quality measured using HR (Hit Ratio) and ARHR (Average Reciprocal Hit-Rank) metrics. In addition, the parallelized versions of the trust-based selection and recommendation algorithms improve the end-to-end runtime. The TruSStReMark will enable users to select services, which are trustworthy, from online software marketplaces and use them in composing quality-aware distributed systems.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11830 |
| Date | 05 December 2016 |
| Creators | Pileththuwasan Gallege, Lahiru Sandakith |
| Contributors | Raje, Rajeev |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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