Asynchronous Protocol Research Articles

A consensus-based solution for cryptocurrencies arbitrage bots in intelligent blockchain

Intelligent blockchain is an emerging field that integrates Artificial Intelligence (AI) techniques with blockchain networks, with a particular emphasis on improving the performance of blockchain, especially in cryptocurrencies exchanges. Meanwhile, arbitrage bots are widely deployed and increasing in intelligent blockchain. These bots exploit the characteristics of cryptocurrencies exchanges to engage in frontrunning, generating substantial profits at the expense of ordinary users. In this paper, we address this issue by proposing a more efficient asynchronous Byzantine ordered consensus protocol, which can be used to prevent arbitrage bots from changing the order of the transactions for profits in intelligent blockchain-based cryptocurrencies. Specifically, we present two signal asynchronous common subset protocols, the more optimal one with only constant time complexity. We implement both our protocol and the optimal existing solution Chronos with Go language in the same environment. The experiment results indicate that our protocols achieve a threefold improvement over Chronos in consensus latency and nearly a tenfold increase in throughput.

Exploring Scalability of BFT Blockchain Protocols through Network Simulations

Novel Byzantine fault-tolerant (BFT) state machine replication protocols improve scalability for their practical use in distributed ledger technology, where hundreds of replicas must reach consensus. Evaluating the performance of BFT protocol implementations requires careful evaluation. We propose a new methodology using scalable network simulations to predict BFT protocol performance. Our simulation architecture allows for the integration of existing BFT implementations without modification or re-implementation, offering a cost-effective alternative to large-scale cloud experiments. We validate our method by comparing simulation results with real-world cloud deployments, showing that simulations can accurately predict performance at larger scales when network limitations dominate. In our study, we applied this methodology to assess the performance of several “blockchain-generation” BFT protocols, including HotStuff, Kauri, Narwhal & Tusk, and Bullshark, under realistic network conditions (with constrained 25 Mbit/s bandwidth) and induced faults. Kauri emerges as the top performer, achieving 6742 operations per second (op/s) with 128 replicas, outperforming BullShark (2318 op/s) and Tusk (1952 op/s). HotStuff, using secp256k1 and BLS signatures, reaches 494 op/s and 707 op/s, respectively, demonstrating the efficiency of BLS-signature aggregation for saving bandwidth. This study demonstrates that state-of-the-art asynchronous BFT protocols can achieve competitive throughput in large-scale, real-world scenarios.

Staleness aware semi-asynchronous federated learning

As the attempts to distribute deep learning using personal data have increased, the importance of federated learning (FL) has also increased. Attempts have been made to overcome the core challenges of federated learning (i.e., statistical and system heterogeneity) using synchronous or asynchronous protocols. However, stragglers reduce training efficiency in terms of latency and accuracy in each protocol, respectively. To solve straggler issues, a semi-asynchronous protocol that combines the two protocols can be applied to FL; however, effectively handling the staleness of the local model is a difficult problem. We proposed SASAFL to solve the training inefficiency caused by staleness in semi-asynchronous FL. SASAFL enables stable training by considering the quality of the global model to synchronise the servers and clients. In addition, it achieves high accuracy and low latency by adjusting the number of participating clients in response to changes in global loss and immediately processing clients that did not to participate in the previous round. An evaluation was conducted under various conditions to verify the effectiveness of the SASAFL. SASAFL achieved 19.69%p higher accuracy than the baseline, 2.32 times higher round-to-accuracy and 2.24 times higher latency-to-accuracy. Additionally, SASAFL always achieved target accuracy that the baseline can't reach.

TortoiseBFT: An asynchronous consensus algorithm for IoT system

Traditional partial synchronous Byzantine fault tolerant (BFT) protocols are confronted with new challenges when applied to large-scale networks like IoT systems, which bring about rigorous demand for the liveness and consensus efficiency of BFT protocols in asynchronous network environments. HoneyBadgerBFT is the first practical asynchronous BFT protocol, which employs a reliable broadcast protocol (RBC) to broadcast transactions and an asynchronous binary agreement protocol (ABA) to determine whether transactions should be committed. DumboBFT is a follow-up proposal that requires fewer instances of ABA and achieves higher throughput than HoneyBadgerBFT, but it does not optimize the communication overhead of HoneyBadgerBFT.In this paper, we propose TortoiseBFT, a high-performance asynchronous BFT protocol with three stages. We can significantly reduce communication overhead by determining the order of transactions first and requesting missing transactions after. Our two-phase transaction recovery mechanism enables nodes to recover missing transactions by seeking help from 2f+1 nodes. To improve the overall throughput of the system, we lower the verification overhead of threshold signatures in HoneyBadgerBFT, DumboBFT, and DispersedLedger from On3 to On2. We develop a node reputation model that selects producers with stable network conditions, which helps to reduce the number of random lotteries. Experimental results show that TortoiseBFT improves system throughput, reduces transaction delays, and minimizes communication overhead compared to HoneyBadgerBFT, DumboBFT, and DispersedLedger.

Channel utilization of media access control protocols for underwater acoustic networks with propagation delay and mobilitya).

This paper investigates the impact of mobility on underwater acoustic communication networks in which the propagation delay is comparable to or larger than the packet duration. An underwater acoustic wireless network, consisting of static and mobile nodes, is studied for its link-layer channel utilization. Synchronous and asynchronous media access control (MAC) protocols are employed with ALOHA, TDMA (time-division multiple access), and artificial intelligence (AI) agent nodes. The simulation results of a multi-node network show that the asynchronous MAC protocols achieve up to 6.66× higher channel utilization than synchronous protocols by allowing time slots to be shorter than the maximum propagation delay among nodes and permitting asynchronous transmission time. The high mobility of a few mobile nodes also favors asynchronous protocols and increases the overall channel utilization. However, node mobility causes more difficulties for the AI node to learn the environment, which may be ineffective to achieve higher gains in channel utilization.

Towards secure and efficient integration of blockchain and 6G networks.

The future of communication systems is undergoing a transformative shift towards intelligence, efficiency, and flexibility. Presently, the amalgamation of blockchain technology and the sixth-generation mobile communication network (6G) has garnered significant attention, as their fusion is poised to profoundly impact the digital economy and society at large. However, the convergence of blockchain and 6G networks poses challenges pertaining to security and performance. In this article, we propose an approach based on the design of secure mechanisms and performance optimization to delve into the key issues surrounding the integration of blockchain and 6G networks from both security and performance perspectives. Specifically, we first introduce the application scenarios of 6G networks and blockchain's empowerment of them to highlight the necessity of combining blockchain technology with 6G. Subsequently, in order to ensure the security of communication and data transmission between blockchain and 6G networks, we have investigated the design requirements for security mechanisms. Furthermore, we discuss the efficient realization of the amalgamation between blockchain and 6G networks by proposing a solution based on Directed Acyclic Graph (DAG) for blockchain's asynchronous consensus protocol, alongside optimization strategies for storage and communication to meet the desired characteristics and requirements of 6G networks. Lastly, we provide valuable research directions that serve as references and guidance for the future development of the integration between blockchain and 6G networks.

An attack-resistant target localization in underwater based on consensus fusion

Target localization has been regarded as one of the most important techniques of underwater sensor networks (USNs). However, the challenges posed by weak communication, inhomogeneous medium, and openness of underwater environment make localization more difficult. With consideration of the asynchronous clock, isogradient sound speed and forging attack, this paper presents a consensus fusion-based target localization solution with USNs. The localization procedure is mainly divided into two phases, i.e., internal position estimation and external information fusion. In the first phase, the received signal strength (RSS) and the time of flight (TOF) measurements are jointly employed to develop an asynchronous localization protocol. Particularly, a ray compensation strategy is incorporated to remove the localization bias from assuming the straight-line transmission. Based on this, a consensus fusion based localization estimator is designed in the second phase to mitigate data falsification attacks introduced by malicious sensor nodes. It is worth mentioning that, the proposed localization solution in this paper can fuse the RSS and TOF measurements by the consensus interaction procedure. Furthermore, it is resistant to data falsification attacks in inhomogeneous water medium. Finally, simulation and experimental results reveal that our solution can reduce the influences of data forging attacks and improve the localization accuracy as compared with the other works.

FlexBFT: A Flexible and Effective Optimistic Asynchronous BFT Protocol

Currently, integrating partially synchronous Byzantine-fault-tolerant protocols into asynchronous protocols as fast lanes represents a trade-off between robustness and efficiency, a concept known as optimistic asynchronous protocols. Existing optimistic asynchronous protocols follow a fixed path order: they execute the fast lane first, switch to the slow lane after a timeout failure, and restart the fast lane after the slow lane execution is completed. However, when confronted with prolonged network fluctuations, this fixed path sequence results in frequent failures and fast lane switches, leading to overhead that diminishes the efficiency of optimistic asynchronous protocols compared with their asynchronous counterparts. In response to this challenge, this article introduces FlexBFT, a novel and flexible optimistic asynchronous consensus framework designed to significantly enhance overall consensus performance. The key innovation behind FlexBFT lies in the persistence of slow lanes. In the presence of persistent network latency, FlexBFT can continually operate round after round within the slow lane—the current optimal path—until the network conditions improve. Furthermore, FlexBFT offers the flexibility to combine consensus modules adaptively, further enhancing its performance. Particularly in challenging network conditions, FlexBFT’s experimental outcomes highlight its superiority across a range of network scenarios compared with state-of-the-art algorithms. It achieves a performance with 31.6% lower latency than BDT, effectively merging the low latency characteristic of deterministic protocols with the robustness inherent in asynchronous protocols.

Asynchronous entanglement routing for the quantum internet

With the emergence of the Quantum Internet, the need for advanced quantum networking techniques has significantly risen. Various models of quantum repeaters have been presented, each delineating a unique strategy to ensure quantum communication over long distances. We focus on repeaters that employ entanglement generation and swapping. This revolves around establishing remote end-to-end entanglement through repeaters, a concept we denote as the “quantum-native” repeaters (also called “first-generation” repeaters in some literature). The challenges in routing with quantum-native repeaters arise from probabilistic entanglement generation and restricted coherence time. Current approaches use synchronized time slots to search for entanglement-swapping paths, resulting in inefficiencies. Here, we propose a new set of asynchronous routing protocols for quantum networks by incorporating the idea of maintaining a dynamic topology in a distributed manner, which has been extensively studied in classical routing for lossy networks, such as using a destination-oriented directed acyclic graph or a spanning tree. The protocols update the entanglement-link topology asynchronously, identify optimal entanglement-swapping paths, and preserve unused direct-link entanglements. Our results indicate that asynchronous protocols achieve a larger upper bound with an appropriate setting and significantly higher entanglement rate than existing synchronous approaches, and the rate increases with coherence time, suggesting that it will have a much more profound impact on quantum networks as technology advances.

Asynchronous Pattern-Designed Channel Access Protocol in Underwater Acoustic Wireless Sensor Networks

Due to the significant propagation delay in underwater sensor networks, conflict retransmission in channel access protocols comes at a high cost. This poses a challenge in scenarios where multiple sensor nodes generate data frames with strong temporal correlations, such as in disaster warning applications. Traditional channel allocation and timeout-based retransmission mechanisms lead to considerable access delays, making it difficult to meet the requirements. To tackle this issue, we propose the asynchronous pattern-designed random access (APDRA) protocol. This protocol enhances the access probability by designing retransmission time intervals for data frames based on pattern design. Additionally, we introduce a successive interference cancellation (SIC) mechanism at the receiver for decoding. This mechanism facilitates the transformation of the conventional method of discarding conflicted data frames into iterative decoding, thereby enhancing transmission efficiency. Via the utilization of simulations, we compare the APDRA protocol conventional underwater medium access control (MAC) protocols and existing retransmission mechanisms. The results demonstrate that the APDRA protocol has the ability to improve both the transmission success ratio (TSR) and reduces the access delay to some extent.

Control for a Class of Two-Time-Scale Cyber-Physical Systems: An Asynchronous Dynamic Event-Triggered Protocol.

In this article, the control problem is investigated for a class of two-time-scale cyber-physical systems (TTSCPSs). In order to reduce the network bandwidth occupation and lighten the computation burden, an asynchronous dynamic event-triggered protocol (ADETP) is designed to arrange the signal transmissions from sensors to the composite controllers, in which the triggering sequences of fast and slow system components are determined separately. A novel composite controller based on the proposed ADETP is designed dependent on the singular perturbation parameter (SPP) such that the closed-loop TTSCPS is asymptotically stable with meeting a required performance index when the SPP is no more than a given upper bound. Gain matrices of the desired composite controller are parameterized in terms of the solutions to certain matrix inequalities that are readily solvable. Finally, simulation results of a nuclear reactor are presented to verify the effectiveness of the proposed approach.

Federated Learning-Based Cell-Free Massive MIMO System for Privacy-Preserving

Cell-free massive MIMO (CF mMIMO) is a promising next generation wireless architecture to realize federated learning (FL). However, sensitive information of user equipments (UEs) may be exposed to the involved access points or the central processing unit in practice. To guarantee data privacy, effective privacy-preserving mechanisms are defined in this paper. In particular, we demonstrate and characterize the possibility in exploiting the inherent quantization error, caused by low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs), for privacy-preserving in a FL CF mMIMO system. Furthermore, to reduce the required uplink training time in such a system, a stochastic non-convex design problem that jointly optimizing the transmit power and the data rate is formulated. To address the problem at hand, we propose a novel power control method by utilizing the successive convex approximation approach to obtain a suboptimal solution. Besides, an asynchronous protocol is established for mitigating the straggler effect to facilitate FL. Numerical results show that compared with the conventional full power transmission, adopting the proposed power control method can effectively reduce the uplink training time under various practical system settings. Also, our results unveil that our proposed asynchronous approach can reduce the waiting time at the central processing unit for receiving all user information, as there are no stragglers that requires a long time to report their local updates.

A Dynamic Opportunistic Routing Protocol for Asynchronous Duty-Cycled WSNs

Opportunistic routing (OR) is widely adopted in Wireless Sensor Networks (WSNs) running asynchronous duty-cycled MAC protocols. In conventional routing, where packets are forwarded along predetermined routes, the sender may wait for the receiver to wake up for a long time. To reduce the sender waiting time, the OR protocols allow nodes to select multiple neighbors as the forwarders so that the packets could be forwarded by multi-path. Thus, the forwarders selection algorithm affects network performance seriously. However, an excessive number of forwarders increases the probability that more than one forwarders wake up simultaneously. This will consume more energy since each of them will receive the packet. To address the two issues, a Dynamic Opportunistic Routing protocol using Analytical Hierarchy Process (AHP) and Fuzzy Inference System (FIS) called DORAF is proposed in this paper. DORAF is implemented in three steps. First, multiple criteria (i.e., residual energy, distance, and angle) at the network layer are defined to evaluate the nodes where the importance of these criteria is determined by AHP. Second, the pairwise comparison matrices in AHP are generated by using mathematical functions (i.e., Boltzmann function and Logistic function) and FIS. Third, each node uses AHP and FIS to prioritize its neighbors based on the criteria and selects appropriate ones as the forwarders dynamically in a distributed manner. The experimental results demonstrate that our protocol performs better than other state-of-the-art in terms of network lifetime, energy consumption, and average redundant transmissions.

Asynchronous Heart Rate Variability Biofeedback Protocol Effects on Adolescent Athletes' Cognitive Appraisals and Recovery-Stress States.

This study examined the effect of an asynchronous heart rate variability biofeedback (HRV-BFBasync) protocol on national-level adolescent swimmers' cognitive appraisals and recovery-stress states during a six-week ecological training period. A polynomial mixed-effects multilevel regression analysis approach was used with 27 adolescent national-level swimmers randomly assigned to an intervention group (n = 14) and a control group (n = 13). Six waves of assessments of cognitive appraisals and recovery-stress states were completed during six weeks of training preparation in ecological conditions. The results revealed that the HRV-BFBasync protocol significantly predicts lower levels of biopsychosocial stress states and cognitive stress. However, no significant effects were found for biopsychosocial recovery scales and cognitive perceived control. The results suggested that total stress states, sport-specific stress, and cognitive perceived stress evolutions are a function of polynomial time third-degree interactions with HRV-BFB protocol. Overall, this study suggested that the HRV-BFBasync protocol leads adolescent athletes to experience lower biopsychosocial and cognitive stress levels during training periodization. Our results also suggest that HRV-BFB induces complex evolutions over time for stress and recovery states but does not have a predictive function for the recovery states and perceived control.

Ultraviolet random access collaborative networking protocol based on time division multiple access

The ultraviolet network, with its advantages of high security, non-line-of-sight communication, and all-weather operation, has broad military application potential. This study proposes an ultraviolet random access collaborative networking protocol based on time division multiple access that combines the benefits of synchronous and asynchronous media access control protocols. Considering the physical layer characteristics, the frame structure of the protocol is constructed based on a cross-layer design. Compared with the time division multiple access protocol, the proposed protocol can achieve higher throughput with a lower delay and packet loss rate by the dynamic timeslot allocation mechanism. Then, the effects of maximum cache capacity and burst traffic on network performance are investigated. Finally, the conducted network experiments prove the cooperative forwarding and random access capabilities of the ultraviolet random access collaborative networking protocol. The proposed protocol provides a reliable and effective method for independent and flexible ultraviolet networks.

Asynchronous broadcast‐based event‐triggered control for discrete‐time clock synchronization

AbstractPrecise timing plays a key role in the time‐sensitive industrial Internet of Things (IIoT). However, precise time synchronization requires more frequent packet exchange, which consumes more communication bandwidth and energy. This is a particular challenge in battery‐powered wireless nodes, and low communication costs have become an important factor in clock synchronization. To address the challenge of achieving low communication cost clock synchronization in distributed wireless sensor networks, this paper proposes an improved event‐triggered control and synchronization scheme with a novel asynchronous broadcast packet exchange protocol. Unlike the traditional event‐triggered control scheme which is based on synchronous polling packet exchange, this proposed asynchronous broadcast packet exchange is more communication efficient and requires fewer number of packet exchanges. And it is worth noting that the proposed algorithm in this paper is a distributed algorithm and does not require real‐time acquisition of information from neighbouring nodes. Finally, a numerical example is given to illustrate the effectiveness of the proposed event‐triggered control strategy. The efficiency and precision of the proposed clock synchronization method is evaluated by intensive simulations, which show that the number of packet exchange is reduced by 60% for a moderate IIoT network and is particularly useful for large scale network.

ASAA: Multihop and Multiuser Channel Hopping Protocols for Cognitive-Radio-Enabled Internet of Things

The devices of Internet of Things (IoT) are integrated and interconnected by using the traditional wireless communication technology. Unavailability of spectrum sharing occurs in traditional wireless communication due to the presence of a massive number of IoT devices. Thus, Cognitive Radio Network (CRN) is introduced as a promising technology to utilize the spectrum efficiently. Channel Hopping Sequence (CHS) is used to establish communication among CRN users. However, the majority of CHS mechanisms only focus on multi-user single-hop scenarios, which can lead to bottleneck and throughput degradation problems. It is also found that few existing CHS mechanisms still have a low percentage of rendezvous that can cause difficulties for the Secondary Users (SUs) to communicate. Thus, it is a challenge to design efficient CHS for establishing fast communication among SUs under multi-user, multi-hop scenarios and asymmetric asynchronous environments. In this paper, Asymmetric Synchronous and Asymmetric Asynchronous (ASAA) Channel Hopping (CH) algorithms are designed for the multi-user CRN-enabled IoT devices to share the unused spectrum in the multi-hop scenario. The Multi-User Asymmetric Synchronous (MUAS) and Multi-User Asymmetric Asynchronous (MUAA) protocols are designed in the proposed ASAA channel hopping mechanism. The simulation results show that the proposed ASAA CHS algorithms outperform the existing CHS mechanisms in terms of throughput, Channel Loading (CL), Channel Utilization (CU), Maximum Time To Rendezvous (MTTR), Average Time to Rendezvous (ATTR) and Maximum Inter Rendezvous Interval (MIRI).

Leaderless and Leader-Following Bipartite Consensus of Multiagent Systems With Sampled and Delayed Information.

This article proposes a hybrid systems approach to address the sampled-data leaderless and leader-following bipartite consensus problems of multiagent systems (MAS) with communication delays. First, distributed asynchronous sampled-data bipartite consensus protocols are proposed based on estimators. Then, by introducing appropriate intermediate variables and internal auxiliary variables, a unified hybrid model, consisting of flow dynamics and jump dynamics, is constructed to describe the closed-loop dynamics of both leaderless and leader-following MAS. Based on this model, the leaderless and leader-following bipartite consensus is equivalent to stability of a hybrid system, and Lyapunov-based stability results are then developed under hybrid systems framework. With the proposed method, explicit upper bounds of sampling periods and communication delays can be calculated. Finally, simulation examples are given to show the effectiveness.

Synchronous Bladder Neck Contracture Dilation at the Time of Artificial Urinary Sphincter Placement Is Safe and Effective

To treat men with bladder neck contracture and stress urinary incontinence, neither long-term nor comparative data exist to support the superiority of simultaneous bladder neck contracture intervention at the time of artificial urinary sphincter placement (synchronous) or staged bladder neck contracture intervention followed by artificial urinary sphincter placement (asynchronous). This study aimed to compare outcomes of patients treated with synchronous and asynchronous protocols. Using a prospectively maintained quality improvement database, we identified all men between the years of 2001-2021 with a history of bladder neck contracture and artificial urinary sphincter placement. Baseline patient characteristics and outcome measures were collected. Categorical data was assessed with Pearson's Chi-square and continuous data was assessed using independent sample t-tests or Wilcoxon Rank-Sum test. In total, 112 men met inclusion criteria. Thirty-two patients were treated synchronously and 80 were treated asynchronously. There were no significant differences between groups across 15 relevant variables. Overall follow-up duration was 7.1 (2.8,13.1) years. Three (9.3%) in the synchronous group and 13 (16.2%) in the asynchronous group experienced an erosion. There were no significant differences in frequency of erosion, time to erosion, artificial sphincter revision, time to revision, or bladder neck contracture recurrence. Bladder neck contracture recurrences after artificial sphincter placement were treated with serial dilation with no early device failure or erosion. Similar outcomes are achieved following synchronous and asynchronous treatment of bladder neck contracture and stress urinary incontinence. Synchronous approaches should be considered safe and effective for men with stress urinary incontinence and bladder neck contracture.

Chronos: An Efficient Asynchronous Byzantine Ordered Consensus

Abstract Byzantine ordered consensus, introduced by Zhang et al. (OSDI 2020), is a new consensus primitive that additionally guarantees a correctness specification of transaction order, allowing nodes to assign fairly an ordering indicator to the committed transaction. Zhang et al. also presented a concrete Byzantine ordered consensus protocol called Pompē in the partially synchronous network model. However, Pompē cannot prevent an adversary from manipulating message delivery time. In this paper, we present Chronos, the first Byzantine ordered consensus protocol in the asynchronous network model, where an adversary can arbitrarily manipulate message delivery time. To construct Chronos, we propose a variant of asynchronous common subset called signal asynchronous common subset protocol, which guarantees the liveness of Chronos. We implement both Chronos and its baseline HoneyBadgerBFT using Go language and deploy them on 100 Amazon t3.medium instances distributed throughout 10 regions across the world. The experimental results show that Chronos is more efficient than HoneyBadgerBFT for small network, achieving peak throughput of 59 368 tx/s when the batch size is 100 000 and the number of nodes is 4, while the peak of HoneyBadgerBFT is 57 077 tx/s.