The Internet of Vehicles (IoV) is emerging as a pivotal technology for enhancing traffic management and safety. Its rapid development demands solutions for enhanced communication efficiency and reduced latency. However, traditional centralized networks struggle to meet these demands, prompting the exploration of decentralized solutions such as blockchain. Addressing blockchain's scalability challenges posed by the growing number of nodes and transactions calls for innovative solutions, among which sharding stands out as a pivotal approach to significantly enhance blockchain throughput. However, existing schemes still face challenges related to a) the impact of vehicle mobility on blockchain consensus, especially for cross-shard transaction; and b) the strict requirements of low latency consensus in a highly dynamic network. In this paper, we propose a DAG (Directed Acyclic Graph) consensus leveraging Robust Dynamic Sharding and Tree-broadcasting (DRDST) to address these challenges. Specifically, we first develop a standard for evaluating the network stability of nodes, combined with the nodes' trust values, to propose a novel robust sharding model that is solved through the design of the Genetic Sharding Algorithm (GSA). Then, we optimize the broadcast latency of the whole sharded network by improving the tree-broadcasting to minimize the maximum broadcast latency within each shard. On this basis, we also design a DAG consensus scheme based on an improved hashgraph protocol, which can efficiently handle crossshard transactions. Finally, the simulation proves the proposed scheme is superior to the comparison schemes in latency, throughput, consensus success rate, and node traffic load.

The Internet of Vehicles (IoV) is emerging as a pivotal technology for enhancing traffic management and safety. Its rapid development demands solutions for enhanced communication efficiency and reduced latency. However, traditional centralized networks struggle to meet these demands, prompting the exploration of decentralized solutions such as blockchain. The scalability of blockchain systems, particularly within the context of IoV, requires innovative approaches to manage the growing number of nodes and transactions. In this paper, we propose a DAG (Directed Acyclic Graph) consensus leveraging Robust Dynamic Sharding and Tree-broadcasting (DRDST) to address these challenges. Specifically, we initially develop a standard for evaluating the network stability of nodes, combined with the nodes' trust values, to propose a novel robust sharding model that is solved through the design of the Genetic Sharding Algorithm (GSA). Then, we optimize the broadcast latency of the whole sharded network by improving the tree-broadcasting to minimize the maximum broadcast latency within each shard. On this basis, we also design a DAG consensus scheme based on an improved hashgraph protocol, which can efficiently handle cross-shard transactions. Finally, the simulation proves the proposed scheme is superior to the comparison schemes in terms of latency, throughput, and consensus success rate.

The Generation-Grid-Load-Storage (GGLS) integrated network was born in the context of carbon neutrality to deal with the unstable impact on power grid operation by renewable energy. The network contains many different entities that generate a large amount of power data along with power transmission, known as Power Big Data (PBD). It assists power companies in formulating marketing and pricing strategies, and also helps to develop power generation and dispatching. Nevertheless, the intensive PBD transaction poses privacy breaches, particularly erroneous transactions misleading the formulation of the above strategies, and causing significant economic losses. As a decentralized system, blockchain offers a trusted environment for PBD interactions. However, the intricate blockchain consensus mechanisms contribute to low processing speeds and scalability challenges, rendering it less suitable for effectively handling high-frequency and extensive PBD transactions. To address this limitation, this study proposes a multi-chain system tailored to the data sources and its parallel consensus mechanism, facilitating efficient processing of PBD transactions. Simulation outcomes demonstrate that our design can meet the transaction requirements with notable efficiency and scalability.

Existing strong leader consensus algorithms, such as the Raft algorithm and its prevote optimization, can encounter significant vote splitting rate and relatively long timeout periods during leader elections, resulting in prolonged election latency and extended service interruptions, especially in wide-area networks. This paper introduces SCRaft, a consensus algorithm that leverages the centralized advantages of a predecessor leader to reduce the latency associated with leader transitions in distributed systems. SCRaft is a re-invented Raft consensus algorithm that, by pre-designating a successive leader during the current leader’s term, which significantly speeds up the election process and minimizes service interruptions due to network packet loss or node failures. This approach not only minimizes disruptions due to network failures or node outages but also preserves the high throughput characteristic of the original Raft algorithm. We detail the algorithm design considerations and the critical aspects of its implementation. Theoretical proof formally demonstrates that SCRaft ensures log consistency, and empirical results confirm its efficacy in reducing election latency without compromising system throughput. Our algorithm provides a robust solution for enhancing the availability of distributed systems.

Existing blockchain technologies and consensus protocols are primarily designed for static, ideal peer-to-peer (P2P) networks, which don't suit the highly dynamic and diverse Internet of Things (IoT) environment. This results in issues such as increased node overhead, network data synchronization delays, block failures, and system crashes. To address the limitations posed by network dynamics and heterogeneity, this paper proposes a structured overlay protocol that can adapt to network dynamics, reduce data broadcast latency and bandwidth load, named DHBN. DHBN logically layers the network based on the survival time of nodes and communication resource heterogeneity, maintaining multiple Minimum Latency Broadcast Trees (MLBT) in a distributed manner in each layer. Nodes communicate with neighbors through tree connections and with other trees through random connections, balancing participant relay tasks. Simulation results demonstrate that compared to other structured broadcast protocols and gossip, DHBN reduces broadcast latency by 34%, bandwidth consumption by 25%, and increases the number of nodes participating in consensus by 14%, offering improved scalability and security.

Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine fault tolerance (PBFT) and RAFT are seen as the most applicable consensus mechanisms (CMs) in blockchain-enabled wireless networks. However, previous studies on PBFT and RAFT rarely consider the channel performance of the physical layer, such as path loss and channel fading, resulting in research results that are far from real networks. Additionally, 6G communications will widely deploy high-frequency signals, such as terahertz (THz) and millimeter wave (mmWave), while performances of PBFT and RAFT are still unknown when these signals are transmitted in wireless PBFT or RAFT networks. Therefore, it is urgent to study the performance of nonideal wireless PBFT and RAFT networks with THz and mmWave signals, to better make PBFT and RAFT play a role in the 6G era. In this article, we study and compare the performance of THz and mmWave signals in nonideal wireless PBFT and RAFT networks, considering rayleigh fading (RF) and close-in free space (FS) reference distance path loss. Performance is evaluated by five metrics: 1) consensus success rate; 2) latency; 3) throughput; 4) reliability gain; and 5) energy consumption. Meanwhile, we find and derive that there is a maximum distance between two nodes that can make CMs inevitably successful, and it is named the active distance of CMs. The results show that the two consensus networks have a lower consensus success rate, higher delay, lower throughput, and lower energy consumption in mmWave than THz. Compared with the wireless RAFT consensus, wireless PBFT consensus has a lower consensus success rate, higher delay, lower throughput, and higher energy consumption. The research results provide important references for the future transmission of THz and mmWave signals in PBFT and RAFT networks.

UAV (unmanned aerial vehicle) is rapidly gaining traction in various human activities and has become an integral component of the satellite-air-ground-sea (SAGS) integrated network. As high-speed moving objects, UAVs not only have extremely strict requirements for communication delay, but also cannot be maliciously controlled as a weapon by the attacker. Therefore, it is necessary to design an efficient and secure communication mechanism (ESCM) for the UAV network (a mobile ad hoc network composed of multiple UAVs). For high efficiency, ESCM provides a routing protocol based on the artificial bee colony (ABC) algorithm to accelerate communications between UAVs. Meanwhile, we use blockchain to guarantee the security of UAV networks. However, blockchain has unstable links in high-mobility networks resulting in low consensus efficiency and high communication overhead. Consequently, ESCM introduces digital twin (DT), which transforms the UAV network into a static network by mapping UAVs from the physical world into Cyberspace. This virtual UAV network is called CyberUAV. Then, in CyberUAV, we design a blockchain consensus based on network coding, named Proof of Network Coding (PoNC). Analysis and simulation show that the above modules in ESCM have advantages over existing schemes. Through ablation studies, we demonstrate that these modules are indispensable for efficient and secure communication of UAV networks.

The wireless blockchain network (WBN) concept, born from the blockchain deployed in wireless networks, has appealed to many network scenarios. Blockchain consensus mechanisms (CMs) are key to enabling nodes in a wireless network to achieve consistency without any trusted entity. However, consensus reliability will be seriously affected by the instability of communication links in wireless networks. Meanwhile, it is difficult for nodes in wireless scenarios to obtain a timely energy supply. Energy-intensive blockchain functions can quickly drain the power of nodes, thus degrading consensus performance. Fortunately, a symbiotic radio (SR) system enabled by cognitive backscatter communications can solve the above problems. In SR, the secondary transmitter (STx) transmits messages over the radio frequency (RF) signal emitted from a primary transmitter (PTx) with extremely low energy consumption, and the STx can provide multipath gain to the PTx in return. Such an approach is useful for almost all vote-based CMs, such as the Practical Byzantine Fault-tolerant (PBFT)-like and the RAFT-like CMs. This paper proposes symbiotic blockchain consensus (SBC) by transforming 6 PBFT-like and 4 RAFT-like state-of-the-art (SOTA) CMs to demonstrate universality. These new CMs will benefit from mutualistic transmission relationships in SR, making full use of the limited spectrum resources in WBN. Simulation results show that SBC can increase the consensus success rate of PBFT-like and RAFT- like by 54.1% and 5.8%, respectively, and reduce energy consumption by 9.2% and 23.7%, respectively.

Wireless blockchain networks have played an important role in many network scenarios, among which wireless Practical Byzantine Fault Tolerance (PBFT) consensus is regarded as one of the most important consensus mechanisms. It enables nodes in wireless networks to reach consistency without any trusted entity. However, due to the instability of wireless communication links, the reliability of the PBFT consensus will be seriously affected. Meanwhile, it is difficult for nodes in wireless scenarios to obtain a timely energy supply. The high-energy-consumption blockchain functions will quickly consume the power of nodes, thus, affecting consensus performance. Fortunately, the symbiotic radio (SR) system enabled by cognitive backscatter communications can provide a solution to the above problems. In SR, the secondary transmitter (STx) transmits messages by modulating its information over the radio frequency (RF) signal of the primary transmitter (PTx) with extremely low energy consumption, and the STx can provide multipath gain to the PTx in return. In our paper, we propose the symbiotic PBFT (S-PBFT) consensus benefited from the mutualistic transmission in SR, which can increase the consensus security by 54.82 %, and save energy consumption by about 10%.

In robotic insertion tasks where the uncertainty exceeds the allowable tolerance, a good search strategy is essential for successful insertion and significantly influences efficiency. The commonly used blind search method is time-consuming and does not exploit the rich contact information. In this paper, we propose a novel search strategy that actively utilizes the information contained in the contact configuration and shows high efficiency. In particular, we formulate this problem as a Partially Observable Markov Decision Process (POMDP) with carefully designed primitives based on an in-depth analysis of the contact configuration's static stability. From the formulated POMDP, we can derive a novel search strategy. Thanks to its simplicity, this search strategy can be incorporated into a Finite-State-Machine (FSM) controller. The behaviors of the FSM controller are realized through a low-level Cartesian Impedance Controller. Our method is based purely on the robot's proprioceptive sensing and does not need visual or tactile sensors. To evaluate the effectiveness of our proposed strategy and control framework, we conduct extensive comparison experiments in simulation, where we compare our method with the baseline approach. The results demonstrate that our proposed method achieves a higher success rate with a shorter search time and search trajectory length compared to the baseline method. Additionally, we show that our method is robust to various initial displacement errors.

Since the Practical Byzantine Fault Tolerance (PBFT) consensus mechanism can avoid the performance bottleneck of blockchain systems caused by Proof of Work (PoW), it has been widely used in many scenarios. However, in the blockchain system, each node is required to back up all transactions and block data of the system, which will waste a lot of storage resources. It is difficult to apply to scenarios with limited storage resources such as unmanned aerial vehicle networks and smart security protection, thus, is often used in small-scale networks. In order to deploy PBFT-based blockchain systems in large-scale network scenarios, we propose an ultra-low storage overhead PBFT consensus (ULS-PBFT), which groups nodes hierarchically to limit the storage overhead within the group. In this paper, we first propose an optimal double-layer PBFT consensus from the perspective of minimizing the storage overhead, and prove that this consensus can significantly reduce the storage overhead. In addition, we also investigate the superiority of ULS-PBFT in terms of communication overhead, while giving the security threshold in the presence of the possibility of Byzantine nodes. Simulation results demonstrate the advantages of ULS-PBFT. Then, we extend such grouping idea to the blockchain system with X-layer PBFT, and analyze its storage and communication overhead. Finally, the node grouping strategy of double-layer PBFT is studied for four application scenarios when the performance of storage overhead, communication overhead, and security are considered comprehensively.

How muscles are used is a key to understanding the internal driving of fish swimming. However, the underlying mechanisms of some features of the muscle activation patterns and their differential appearance in different species are still obscure. In this study, we explain the muscle activation patterns by using 3D computational fluid dynamics models coupled to the motion of fish with prescribed deformation and examining the torque and power required along the fish body with two primary swimming modes. We find that the torque required by the hydrodynamic forces and body inertia exhibits a wave pattern that travels faster than the curvature wave in both anguilliform and carangiform swimmers, which can explain the traveling wave speeds of the muscle activations. Notably, intermittent negative power (i.e., power delivered by the fluid to the body) on the posterior part, along with a timely transfer of torque and energy by tendons, explains the decrease in the duration of muscle activation towards the tail. The torque contribution from the body elasticity further clarifies the wave speed increase or the reverse of the wave direction of the muscle activation on the posterior part of a carangiform swimmer. For anguilliform swimmers, the absence of the aforementioned changes in the muscle activation on the posterior part is consistent with our torque prediction and the absence of long tendons from experimental observations. These results provide novel insights into the functions of muscles and tendons as an integral part of the internal driving system, especially from an energy perspective, and they highlight the differences in the internal driving systems between the two primary swimming modes.