B2RAM: Design and practical implementation of a secured information management framework for dynamic resource allocation using a novel 2-Tier blockchain model

Abstract

Resource allocation problems involve the intricate task of equitably and consistently distributing typically limited resources among competing clients, all while dealing with the issues of fairness, starvation, scalability and deadlock. The effectiveness of these solutions hinges on a secure and transparent underlying information flow model, ensuring timely and synchronized exchange of information about resource usage among the clients. Both centralized and distributed system architectures present their own challenges when devising such information flow strategies for optimal resource allocation. This paper efficiently addresses the constraints inherent in resource allocation and the associated information flows within a hybrid system-of-systems framework. It further integrates both distributed and centralized models while maintaining an optimal trade-off between the computational and communication costs. In this context, a secure and transparent information management framework is proposed, leveraging a novel 2-Tier blockchain model — B2RAM. The first Tier establishes a consortium blockchain within a distributed network, while the second Tier creates multiple private blockchain networks in centralized client–server models. Together, these two tiers establish a distinctive resource allocation policy that engages both cooperative and competitive users, further incorporating a novel dual-token model and resource ranking strategy. Extensive performance evaluation facilitates fine-tuning of B2RAM through parameter configurations and enhancement strategies. This not only refines its performance but also solidifies its superiority over existing models like greedy, Markov, prediction, random, and rank-based approaches. Finally, practical applicability of B2RAM is established through its implementation in Cognitive Radio Networks, where the operational feasibility is ensured through successful test-bed design and execution using a modular system framework.