Enabling Trust Assessment In Clouds-of-Clouds: A Similarity-Based Approach

In multi-cloud paradigm, cloud providers collaborate to form adhoc and ephemeral groups to fullfill the request of a single customer. In such settings, malevolent cloud providers may be tempted to provide cloud services that are below the expected quality. This temptation is further exacerbated by the inability of customers to effectively identify the responsible of service outage or degradation.
Furthermore, the highly competitive nature of cloud marketplaces leads each provider to propose regularly innovative new services, making the system open and highly dynamic. The introduction of new cloud services into the system challenges the established trust order as customers and providers must accept the risk of taking decisions under uncertainty. This problem, known as the cold-start problem, have been studied in the literature from the perspective of the individuals (providers/customers) but to the best of our knowledge, no prior work tried to address it from the perspective of the exchanged services and resources. To that aim, we propose in this paper a similarity-based trust model that tackles both multi-cloud (i.e., group-reputation) and services high turnover (i.e., cold-start). In our model, past similar experiences are transferred to the providers proposing new services to enable and boost decision making and collaboration. We propose also a schema to derive multi-cloud trust using both customers and providers feedback experiences. We present also evaluations results to show the benefit of using our proposal and their impact on the simulated cloud-marketplace.