Data-driven and Feedback-Enhanced Trust Computing Pattern for Large-scale Multi-Cloud Collaborative Services
Abstract— Data-driven and Feedback-Enhanced Trust Computing Pattern for Large-scale Multi-Cloud Collaborative Services. Multi-cloud collaborative environment consists of multiple data centers, which is a typical processing platform for big data. This paper focuses on the trust computing requirement of multi-cloud collaborative services and develops a Data-driven and Feedback-Enhanced Trust DFET < Final Year Projects 2016 > computing pattern across multiple data centers with several innovative mechanisms. First, a trust-aware service monitoring architecture is proposed based on distributed soft agents to serve as middleware for multi-cloud trust computing and task scheduling. A data-driven trust computation scheme based on multi-indicator monitoring data is then proposed. The integration of several key service indicators into trust computing makes this scheme suitable for service-oriented cloud applications.
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