Blockchain technology is a unique distributed ledger technology that has been widely used in various areas. With the increase in data on the blockchain and the append-only nature of the blockchain, the traditional blockchain’s full replica storage technique leads to blockchain storage scalability problem. Existing methods prioritize minimizing the storage strain on blockchain nodes while ignoring the availability of data, resulting in a lengthy average response time for users to access the blockchain. To address the shortcomings, this paper proposes an Information-Centric Networking-based blockchain storage architecture. The architecture uses the enhanced resolution system for community division to build blockchain node partitions and store blockchain ledgers in the underlying network. It introduces virtual chain for rapid blockchain indexing and adopts a collaborative block replica deletion algorithm across neighboring partitions, including replica number decision based on blockchain access decay characteristics and replica deletion based on resource relationship. Finally, we compare and analyze the proposed blockchain storage architecture with BC-store and KASARASA, and the results demonstrate that this architecture has significantly lower average access time than others. The replica data volume of this method is reduced by 57.2% compared to the full replica policy, but the access time is only 5.2% slower when compared to the full replica policy, which substantially increases the replica storage utilization.

In the era of the digital economy, blockchain has developed well in various fields, such as finance and digital copyright, due to its unique decentralization and traceability characteristics. However, blockchain gradually exposes the storage problem, and the current blockchain stores the block data in third-party storage systems to reduce the node storage pressure. The new blockchain storage method brings the blockchain transaction retrieval problem. The problem is that when unable to locate the block containing this transaction, the user must fetch the entire blockchain ledger data from the third-party storage system, resulting in huge communication overhead. For this problem, we exploit the semi-structured data in the blockchain and extract the universal blockchain transaction characteristics, such as account address and time. Then we establish a blockchain transaction retrieval system. Responding to the lacking efficient retrieval data structure, we propose a scalable secondary search data structure BB+ tree for account address and introduce the I2B+ tree for time. Finally, we analyze the proposed scheme’s performance through experiments. The experiment results prove that our system is superior to the existing methods in single-feature retrieval, concurrent retrieval, and multi-feature hybrid retrieval. The retrieval time under single feature retrieval is reduced by 40.54%, and the retrieval time is decreased by 43.16% under the multi-feature hybrid retrieval. It has better stability in different block sizes and concurrent retrieval scales.

The integration of blockchain with Information-Centric Networking (ICN) enhances content distribution efficiency in areas such as the Internet of Things (IoT) and 5G/6G communications. This integration implies that the network state information of ICN can significantly impact consensus efficiency. However, the Ethereum Casper FFG consensus algorithm overlooks the network heterogeneity among consensus nodes, leading to a potential bottleneck in consensus efficiency, especially when nodes with inferior network quality participate. To address this issue, this paper proposes a multidimensional reputation model based on an ICN-enabled blockchain architecture. The model combines on-chain stake and network contributions to evaluate the reputation of ICN consensus nodes. Furthermore, a reputation-based hybrid consensus mechanism, RepuICN, is introduced, which enhances the network layer of the Casper FFG algorithm. This mechanism selects higher-reputation ICN consensus nodes as proposers for checkpoint blocks, mitigating the impact of network latency fluctuations on block propagation. Additionally, RepuICN improves block propagation efficiency through ICN multicast and caching techniques. Simulation results show that, under identical conditions with a network of 5000 nodes and 2% ICN nodes, RepuICN reduces broadcast latency by 17% for regular blocks and 61.4% for checkpoint blocks and achieves 3.4 times higher transaction throughput than Casper FFG.

The Interplanetary File System (IPFS), a new type of P2P file system, enables people to obtain data from other peer nodes in a distributed system without the need to establish a connection with a distant server. However, IPFS suffers from low resolution efficiency and duplicate data delivery, resulting in poor system availability. The new Information-Centric Networking (ICN), on the other hand, applies the features of name resolution service and caching to achieve fast location and delivery of content. Therefore, there is a potential to optimize the availability of IPFS systems from the network layer. In this paper, we propose an ICN-based IPFS high-availability architecture, called IBIHA, which introduces enhanced nodes and information tables to manage data delivery based on the original IPFS network, and uses the algorithm of selecting high-impact nodes from the entitled network (PwRank) as the basis for deploying enhanced nodes in the network, thus achieving the effect of optimizing IPFS availability. The experimental results show that this architecture outperforms the IPFS network in terms of improving node resolution efficiency, reducing network redundant packets, and improving the rational utilization of network link resources.

The Computing Network is an emerging network paradigm that aims to realize computing resource scheduling through the intrinsic capabilities of the network. However, existing resource scheduling architectures based on conventional TCP/IP networks for the Computing Network suffer from deficiencies in routing flexibility and a lack of user preference awareness, while Information-Centric Networking (ICN) holds the potential to address these issues. ICN inherently supports dynamic routing in scenarios such as multi-homing and mobility due to its routing mechanism that is based on content names rather than host addresses, and it is further enhanced by the integration with Software-Defined Networking (SDN) technologies, which facilitate convenient network-layer route readdressing, thus offering a conducive environment for flexible routing scheduling. Furthermore, ICN introduces novel routing protocols that, compared with the more rigid protocol designs in conventional TCP/IP networks, offer greater flexibility in field usage. This flexibility allows for the incorporation of customized fields, such as “preference”, enabling the perception of user preferences within the network. Therefore, this paper proposes a novel ICN-based on-path computing resource scheduling architecture named IPCRSA. Within this architecture, an original design for computing resource request packet format is developed based on the IPv6 extension header. Additionally, preference-based computing resource scheduling strategies are incorporated, which employ the technique for order preference by similarity to ideal solution (TOPSIS) combined with the entropy weight method, to comprehensively evaluate computing resource nodes and use a roulette-selection algorithm to accomplish the probability selection of destination nodes. Experimental results indicate that, in comparison to alternative scheduling schemes, IPCRSA exhibits significant advantages in enhancing scheduling flexibility, improving scheduling success rates, and catering to diverse user requirements.

The various integration systems of blockchain and information-centric network (ICN) have been applied to provide a trusted and neutral approach to cope with large-scale content distribution in IoT, AR/VR, or 5G/6G scenarios. As a result, the scalability problem of blockchain has been an increasing concern for researchers. The sharding mechanism is recognized as a promising approach to address this challenge. However, there are still many problems in the existing schemes. Firstly, real-time processing speed trades off security of validation. Secondly, simply randomly assigning nodes to the shards may make nodes located very far from each other, which increases the block propagation time and reduces the efficiency advantage brought by the sharding mechanism. Therefore, we optimize a reputation-based sharding consensus model by multi-dimension trust and leverage the affinity propagation (AP) algorithm for gathering consensus nodes into shards. Given the minimal possibility to be at fault in the security of validation, clients can achieve real-time processing speed with assurance. The evaluation results show that the normalized mean square error (NMSE) between the estimated reputation value and the real reputation value of our reputation scheme is less than 0.02. Meanwhile, compared with the classical sharding scheme Omniledger, TPS performance can achieve 1.4 times promotion in the case of a large-scale blockchain network of 1000 nodes.