An Adaptive Sharding-based Blockchain for Network Slicing in 5G

Fifth-generation wireless technology, or 5G, promises increased data speeds, lower latency and greater capacity for mobile communications, enabling the growth of the Internet of Things (IoT). Network slicing is an advantageous feature of 5G that enables the creation of multiple virtual networks to meet the performance, security, and reliability needs of different services. This feature, combined with blockchain technology, provides secure and transparent data sharing between devices and networks. In addition, blockchain-enabled network slicing improves 5G network management and creates new business models for industries such as healthcare, transportation, and manufacturing. However, most current blockchain systems are limited in their ability to handle high throughput, which is not equivalent to what 5G can do. Therefore, sharding-based blockchain is proposed as a possible solution to improve the scalability and throughput of blockchain networks. By dividing the network into parts or shards, transactions can be processed simultaneously, allowing for faster transaction verification times and increased network capacity. Although current sharding-based blockchain networks have some limitations, such as static sharding policies that cannot cope with the dynamic blockchain environment, an adaptive sharding blockchain system using Deep Reinforcement Learning (DRL) methods has been proposed to address this situation. The approach allows the system to change or adapt the shard specifications, such as shard size or block size, whenever necessary to ensure maximum throughput while maintaining the security and integrity of the blockchain network.