De-Centralized Reputation-Based Trust Model to Discriminate between Cloud Providers Capable of Processing Big Data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Trust and reputation systems represent a significant trend in decision support including selection of best match cloud providers to process Big Data. Reputation is often considered as a collective measure of trustworthiness based on the referrals or ratings from members in a community. Reputation systems have been applied in various applications such as online service provision. However, reputation models do not reflect user's quality of service (QoS) preferences and thus they might not be satisfied with the recommendations from others. In this paper, we propose a de-centralized reputation-based trust model that incorporates the user QoS preferences to select the best match Cloud Service Provider to process Big Data. Our trust model relies on three multi-attribute decision-making (MADM) methods including Simple Additive Weighting (SAW), Weighted Product Method (WPM), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We conducted several experiments using simulated cloud environment to validate our trust model and assess the three MADM methods. The results show that the proposed model is pliable to users' requirements and efficiently evaluate trust of cloud providers.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE 6th International Congress on Big Data, BigData Congress 2017
EditorsGeorge Karypis, Jia Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages266-273
Number of pages8
ISBN (Electronic)9781538619964
DOIs
Publication statusPublished - Sep 7 2017
Event6th IEEE International Congress on Big Data, BigData Congress 2017 - Honolulu, United States
Duration: Jun 25 2017Jun 30 2017

Publication series

NameProceedings - 2017 IEEE 6th International Congress on Big Data, BigData Congress 2017

Other

Other6th IEEE International Congress on Big Data, BigData Congress 2017
Country/TerritoryUnited States
CityHonolulu
Period6/25/176/30/17

Keywords

  • Big Data
  • Big Data processing
  • Multi-criteria decision-making
  • SAW
  • TOPSIS
  • WPM
  • cloud computing
  • cloud selection
  • reputation
  • trust evaluation
  • trust model

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management

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