Trust-Aware and Fast Resource Matchmaking for Personalized Collaboration Cloud Service

Abstract

In data-intensive cloud collaboration services with tens of thousands of users and million-level resources, means of providing personalized and trust-aware services quickly and simultaneously is a challenging issue. In this paper, we propose Per-trust, a trust-aware and fast resource matchmaking scheme for personalized QoS guaranteeing in collaboration cloud service. First, an integrated and trust-aware service broking architecture is proposed across the collaborative cloud computing environment; this architecture can provide trust computing and personalized resource matchmaking capacities. Then, a resource clustering method is proposed based on the multidimensional properties of cloud resources; this method can accurately, quickly meet the personalized requirements of users. Finally, an innovative algorithm is proposed for the trust computing of service resources based on real-time and dynamic monitoring of data, thereby quickly and effectively providing trust-aware resource matchmaking. Different from existing methods, which focus only on QoS and trust issues, our approach adds a resource clustering step before QoS and trust evaluation. Three key components are organically combined, namely, service broking architecture, resource clustering, and security and QoS-related trust computing. To the best of our knowledge, this paper is the first to construct an integrated solving scheme for cloud resource matchmaking that can simultaneously satisfy the trustworthiness and personalization required by users. Theoretical and experimental results verify the effectiveness of the proposed scheme.