Supplementary information for Reputation-based coalition formation for secure self-organized and scalable sharding in IoT blockchains with mobile-edge computing
Article abstract
We propose a fully distributed system architecture and a scalable self-organized sharding scheme for the Internet-of-Things (IoT) blockchains that can guarantee system security without reducing its throughput. In the system, the IoT devices are supported by the set of blockchain peers that gather, process, verify, and store the blocks of IoT transaction records. To support communications among peers, the system is realized in the mobile-edge computing (MEC) network. We design a new consensus mechanism in which each peer votes on the outputs of each block task in its shard. The peer's voting power is computed from its reputation, i.e., trustworthiness in the system. By adopting a reputation-based coalitional game model, we formulate a novel self-organized shard formation algorithm in which each peer acts as a rational player aiming to maximize both its payoff and the coalitional reputation. We prove that the algorithm converges to the reputation-based stable shard structure, i.e., a structure that maximizes the payoff and coalitional reputation of each peer without negatively affecting other peers. The algorithm shows a superior performance in terms of system security and throughput when compared to state-of-the-art sharding schemes and reputation-based blockchains.
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Funding
National Natural Science Foundation of China (NSFC) Project No.61950410603
National Research Foundation (NRF), Singapore, through Singapore Energy Market Authority, Energy Resilience: grant NRF2017EWT-EP003-04
Singapore NRF: grant NRF2015-NRF-ISF001-2277
Singapore NRF National Satellite of Excellence, Design Science and Technology for Secure Critical Infrastructure NSoE: grant DeST-SCI2019-0007
A*STAR-NTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing: grant RGANS1906
Wallenberg AI, Autonomous Systems and Software Program and Nanyang Technological University: grant M4082187 (4080)
History
School
- Science
Department
- Computer Science