A Secure Interconnected Autonomous System Architecture for Multi-Domain IoT Ecosystems

【Author】 Xu, Ronghua; Nagothu, Deeraj; Chen, Yu; Aved, Alex; Ardiles-Cruz, Erika; Blasch, Erik

【Source】IEEE COMMUNICATIONS MAGAZINE

【影响因子】9.030

【Abstract】The rapid merge of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain technologies atop the fifth generation and beyond (B5G) communication networks is envisioned to promote Next Generation Networks (NGNs), which aim for a large-scale, high-dimensional, intelligent, decentralized, and autonomous network infrastructure for complex and heterogeneous IoT ecosystems. To develop such an ecosystem, highly connected devices and user-defined applications bring serious connectivity, security, scalability, and interoperability issues to fragmented and isolated domain-specific autonomous networks. This article presents a Secure Interconnected Autonomous System Architecture (SIASA), which combines Software Defined Network (SDN) with the hierarchical blockchain federation to improve dynamicity, scalability, and interoperability for multi-domain IoT networks. Through softwarization and virtualization provided by network slicing (NS), a logic IoT ecosystem consists of multiple isolated physical networks as autonomous systems (ASs) that rely on heterogeneous blockchains to provide decentralization and security for each domain. SIASA adopts a hierarchical network of federated blockchains for inter-blockchain communication. In addition, an intelligent SDN-enabled Blockchain gateway framework is proposed to support scalable and secure transactions and data-sharing operations among interconnected autonomous systems. The experimental results based on a preliminary proof-of-concept prototype verify the feasibility of the proposed SIASA architecture in terms of end-to-end latency and throughput in the inter-blockchain scene.

【Keywords】Autonomous networks; Scalability; Ecosystems; Computer architecture; Logic gates; Blockchains; Security; Autonomous systems; Internet of Things; Artificial intelligence

【发表时间】2024 JUL

【收录时间】2024-07-20

【文献类型】实验仿真

【主题类别】

区块链技术-协同技术-物联网