Modeling Operational Fairness of Hybrid Cloud Brokerage

TL;DR

This paper introduces a formal fairness model for hybrid cloud brokerage, using temporal logic and probabilistic algorithms to verify trustworthiness and neutrality over time, considering provider variability.

Contribution

It proposes a novel calculus of fairness and an algorithm to assess broker neutrality and fairness in hybrid cloud environments.

Findings

Developed a temporal logic-based fairness calculus.

Designed a probabilistic algorithm for fairness verification.

Incorporated provider cost and capacity factors into the model.

Abstract

Cloud service brokerage is an emerging technology that attempts to simplify the consumption and operation of hybrid clouds. Today's cloud brokers attempt to insulate consumers from the vagaries of multiple clouds. To achieve the insulation, the modern cloud broker needs to disguise itself as the end-provider to consumers by creating and operating a virtual data center construct that we call a meta-cloud, which is assembled on top of a set of participating supplier clouds. It is crucial for such a cloud broker to be considered a trusted partner both by cloud consumers and by the underpinning cloud suppliers. A fundamental tenet of brokerage trust is vendor neutrality. On the one hand, cloud consumers will be comfortable if a cloud broker guarantees that they will not be led through a preferred path. And on the other hand, cloud suppliers would be more interested in partnering with a cloud broker who promises a fair apportioning of client provisioning requests. Because consumer and supplier trust on a meta-cloud broker stems from the assumption of being agnostic to supplier clouds, there is a need for a test strategy that verifies the fairness of cloud brokerage. In this paper, we propose a calculus of fairness that defines the rules to determine the operational behavior of a cloud broker. The calculus uses temporal logic to model the fact that fairness is a trait that has to be ascertained over time; it is not a characteristic that can be judged at a per-request fulfillment level. Using our temporal calculus of fairness as the basis, we propose an algorithm to determine the fairness of a broker probabilistically, based on its observed request apportioning policies. Our model for the fairness of cloud broker behavior also factors in inter-provider variables such as cost divergence and capacity variance.