dynamic partitioning
در نشریات گروه برق-
Journal of Artificial Intelligence in Electrical Engineering, Volume:11 Issue: 44, Winter 2023, PP 1 -13
With the emergence of smart cities vision, its large distributed applications such as intelligent transportation systems demand scalable low-latency trusted data exchange architecture with high storage and computational resources for storing the high-volume of IoT data and providing real-time services. In recent years, blockchain technology has gained extensive attention to fulfil the requirements of such highly distributed large systems. However, there are a number of technical challenges in the integration of blockchain and IoT applications. Firstly, Bitcoin blockchain with low scalability and throughput is not able to provide fast services. Secondly, there are limitations like constrained spaces for establishing big blockchain nodes storing a massive volume of data generated by numerous smart IoT devices or sensors inside the streets of cities. This paper argues that solving both issues in one large blockchain network is infeasible. Therefore, we prioritize this two weakness of blockchain in relation to such systems and propose two separate level of blockchain networks cooperating with each other asynchronously to address them. One network called Fast BlockChain (FBC) composed of multiple scalable sub-blockchain networks responsible for fast services. Another network, CityBC, supports the networks of FBC through the long-term storing of their data and providing their smart manager with knowledge for dynamic autonomous partitioning of them in order to decrease network-to-network communications and avoid wasting storage resources and network bandwidth. Furthermore, this paper evaluates the ideal size of sub-blockchain and then proposes a novel idea for an initial partitioning technique before using collected data by blockchain nodes for dynamic partition of network.
Keywords: decentralized management systems, interoperable blockchain framework, Internet of Things, pervasive systems, dynamic partitioning
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