Practical Modeling and Analysis of Blockchain Radio Access Network

The continually rising demand for wireless services and applications in the era of Internet of things (IoT) and artificial intelligence (AI) presents a significant number of unprecedented challenges to existing network structures. To meet the rapid growth need of mobile data services, blockchain radio access network (B-RAN) has emerged as a decentralized, trustworthy radio access paradigm spurred by blockchain technologies. However, many characteristics of B-RAN remain unclear and hard to characterize. In this study, we develop an analytical framework to model B-RAN and provide some basic fundamental analysis. Starting from block generation, we establish a queuing model based on a time-homogeneous Markov chain. From the queuing model, we evaluate the performance of B-RAN with respect to latency and security considerations. By connecting latency and security, we uncover a more comprehensive picture of the achievable performance of B-RAN. Further, we present experimental results via an innovative prototype and validate the proposed model.Comment: 30 pages, 15 figures Submitted to IEEE Transactions on Communication

Stochastic Modeling Approaches for Analyzing Blockchain: A Survey

Blockchain technology has been attracting much attention from both academia and industry. It brings many benefits to various applications like Internet of Things. However, there are critical issues to be addressed before its widespread deployment, such as transaction efficiency, bandwidth bottleneck, and security. Techniques are being explored to tackle these issues. Stochastic modeling, as one of these techniques, has been applied to analyze a variety of blockchain characteristics, but there is a lack of a comprehensive survey on it. In this survey, we aim to fill the gap and review the stochastic models proposed to address common issues in blockchain. Firstly, this paper provides the basic knowledge of blockchain technology and stochastic models. Then, according to different objects, the stochastic models for blockchain analysis are divided into network-oriented and application-oriented (mainly refer to cryptocurrency). The network-oriented stochastic models are further classified into two categories, namely, performance and security. About the application-oriented stochastic models, the widest adoption mainly concentrates on the price prediction of cryptocurrency. Moreover, we provide analysis and comparison in detail on every taxonomy and discuss the strengths and weaknesses of the related works to serve guides for further researches. Finally, challenges and future research directions are given to apply stochastic modeling approaches to study blockchain. By analyzing and classifying the existing researches, we hope that our survey can provide suggestions for the researchers who are interested in blockchain and good at using stochastic models as a tool to address problems