Broadcast Algorithm Research Articles

VCubeChain: A scalable permissioned blockchain

This work presents vCubeChain, a scalable permissioned blockchain based on the vCube virtual topology. vCube is a virtual hierarchical topology that presents several logarithmic properties. vCubeChain employs a leader election algorithm that relies on the failure detection information that vCube provides. The leader employs a vCube-based autonomic reliable broadcast algorithm to disseminate blocks, each consisting of multiple transactions. In case multiple leaders end up concurrently elected due to false suspicions, vCubeChain is proven to recover to a consistent state upon the discovery of contradictory blocks. vCubeChain is described, specified, and correctness and liveness draft proofs are presented. The blockchain was implemented on the Blocksim simulator, and a set of experiments are presented, including comparisons with Bitcoin, Ethereum and Hyperledge Fabric. Results demonstrate the scalability of the solution.

Enhancing MPI remote memory access model for distributed-memory systems through one-sided broadcast implementation

Efficiently processing vast and expanding data volumes is a pressing challenge. Traditional high-performance computers, utilizing distributed-memory architecture and a message-passing model, grapple with synchronization issues, hampering their ability to keep up with the growing demands. Remote Memory Access (RMA), often referred to as one-sided MPI communications, offers a solution by allowing a process to directly access another process’s memory, eliminating the need for message exchange and significantly boosting performance. Unfortunately, the existing MPI RMA standard lacks a collective operation interface, limiting efficiency. To overcome this constraint, we introduce an algorithm design that enables efficient parallelizable collective operations within the RMA framework. Our study focuses primarily on the advantages of collective operations, using the broadcast algorithm as a case study. Our implementations surpass traditional methods, highlighting the promising potential of this technique, as indicated by initial performance tests.

Privacy-Preserving Adaptive Resilient Consensus for Multiagent Systems Under Cyberattacks

This article investigates the secure and privacy-preserving consensus problem of multi-agent systems (MASs) with directed interaction topologies under multiple cyber attacks, which contain deception attacks and DoS attacks. First, a unified attack model is introduced to characterize such a multiple attack phenomenon. Besides, considering the existence of eavesdroppers who can intercept the data transmitted on the links, a fully distributed agent value reconstruction method based on the idea of state decomposition is designed to prevent the leakage of the agent's initial information. Then, a novel privacy-preserving adaptive resilient consensus algorithm (PPARCA) with certain graph robustness condition for MASs under the multiple cyber attacks is proposed. The algorithm adaptively takes different countermeasures in the face of different cyber attacks. PPARCA uses the reconstructed agents' states and combines with the modified Secure Acceptance and Broadcast Algorithm (SABA). Theoretical analysis shows that the proposed algorithm can effectively protect the privacy of the initial state of the agents, and reach resilient consensus in the face of cyber attacks. Finally, numerical simulations and Raspberry Pi MASs practical application experiments demonstrate the effectiveness of the proposed results.

Алгоритм широковещательной рассылки на основе биномиального дерева в модели удаленного доступа к памяти

This article introduces a broadcast (one-to-all scheme) algorithm, designed to enhance the efficiency of utilizing Remote Memory Access (RMA), a one-sided communication model within the MPI standard, for parallel programming in distributed computing systems. The algorithm leverages a binomial tree structure to organize interprocess interactions, a scheme widely employed for classic collective operations within the MPI standard. With logarithmic complexity, this algorithm proves to be more efficient than linear counterparts. The article also provides analytical complexity estimates within the LogP and LogGP models. Experimental results confirm the algorithm's advantages, although the ultimate efficiency depends on several factors, including the number of processes in the communicator, data transmission size, and the performance of the interconnect.

Scalable atomic broadcast: A leaderless hierarchical algorithm

Atomic Broadcast is an essential broadcast primitive as it ensures the consistency of distributed replicas. However, it is notoriously non-scalable. In this work, we introduce the Leaderless Hierarchical Atomic Broadcast (LHABcast) algorithm, which has two properties to improve scalability. First, it is a fully decentralized algorithm that does not rely on a sequencer/leader, which is often a significant bottleneck. Processes running LHABcast send messages with local sequence numbers and order messages received from other processes using timestamps inspired on Lamport's logical clocks. A process that receives the required set of timestamps can make a decision about the overall sequence of message delivery. Second, the algorithm is hierarchical: processes are organized on a vCube logical overlay network, which has several logarithmic properties and allows the construction of autonomous spanning trees. vCube also works as a failure detector, assuming crash faults and an asynchronous system model. In this paper, LHABcast is described, specified, and proven to be correct. Both simulation and experimental results are presented. A comparison with an all-to-all strategy shows that the number of messages sent by LHABcast is significantly lower in both fault-free and faulty scenarios. An implementation of LHABcast in Akka.io achieved up to 3.9 times higher throughput in fault-free scenarios than an implementation of the Raft-based Apache Ratis.

MPI reduction and broadcast algorithms for computer clusters with multistage interconnection networks

Algorithms for MPI Allreduce, Bcast and Reduce collective operations have been developed. They are based on the dynamic construction of process groups at all levels of the memory hierarchy within the computing node and levels of the multistage interconnection network. The description of the network topology is loaded from an external file. Аlgorithms are implemented on the basis of the Open MPI library in an isolated collective component. Experiments on a cluster with a two-tier InfiniBand EDR network have shown the effectiveness of the algorithms for messages up to 16KB.

Asynchronous Byzantine reliable broadcast with a message adversary

This paper considers the problem of reliable broadcast in asynchronous authenticated systems, in which n processes communicate using signed messages and up to t processes may behave arbitrarily (Byzantine processes). In addition, for each message m broadcast by a correct (i.e., non-Byzantine) process, a message adversary may prevent up to d correct processes from receiving m. (This message adversary captures network failures such as transient disconnections, silent churn, or message losses.) Considering such a “double” adversarial context and assuming n>3t+2d, a reliable broadcast algorithm is presented. Interestingly, when there is no message adversary (i.e., d=0), the algorithm terminates in two communication steps (so, in this case, this algorithm is optimal in terms of both Byzantine tolerance and time efficiency). It is then shown that the condition n>3t+2d is necessary for implementing reliable broadcast in the presence of both Byzantine processes and a message adversary (whether the underlying system is enriched with signatures or not).

Dynamic Probabilistic Broadcast based on Neighbour Discovery

Broadcasting in Ad hoc networks is an important information dissemination way. However, flooding may give rise to broadcast storm problem which causes severe contention, collision and delay. This paper proposes a dynamic probabilistic broadcast algorithm based on neighbour discovery that ensures the higher reliability at lower retransmission. The dynamic probabilistic broadcast algorithm forwards the information from the node (INode) that has obtained it to the node (UNode) that has not received it. By counting the number of UNode and INode of neigbors, INodes dynamically adjust the probability of broadcasting to reduce the number of information replication but cover more UNodes. Dynamic probabilistic algorithm can not only effectively reduce the number of retransmission, but also ensure the effectiveness and reliability. Simulation results show that the number of broadcasting of this algorithm is significantly lower than other algorithms.

All-to-All Broadcast Algorithm in Galaxyfly Networks

The design of interconnection networks is a fundamental aspect of high-performance computing (HPC) systems. Among the available topologies, the Galaxyfly network stands out as a low-diameter and flexible-radix network for HPC applications. Given the paramount importance of collective communication in HPC performance, in this paper, we present two different all-to-all broadcast algorithms for the Galaxyfly network, which adhere to the supernode-first rule and the router-first rule, respectively. Our performance evaluation validates their effectiveness and shows that the first algorithm has a higher degree of utilization of network channels, and that the second algorithm can significantly reduce the average time for routers to collect packets from the supernode.

시분할 다중 접속 기반 무선 메쉬 네트워크에서 브로드캐스트 스케줄링 문제를 위한 타부서치 알고리즘

시분할 다중 접속 기반에서 브로드캐스트 스케줄링 문제는 타임 슬롯을 사용하여 모든 단말이 충돌 없이 전송할 수 있도록 설계하는 문제이다. 본 논문에서는 시분할 다중 접속 기반의 무선 메쉬 네트워크에서 브로드캐스트를 사용하는 노드의 전송 스케줄을 최적화하여 전체 전송 횟수와 타임 슬롯 이용률을 최대화하는 브로드캐스트 스케줄링 최적화 알고리즘을 제안한다. 제안된 최적화 알고리즘은 메타휴리스틱 방식 중 하나인 타부서치 알고리즘을 사용한다. 제안된 타부서치 알고리즘은 전체 전송 횟수를 최대화하는 목적함수를 사용하여 효율적인 이웃해 생성방식을 설계하였다. 본 논문에서는 네트워크에서 발생하는 모든 브로드캐스팅에 대하여 전체 전송 횟수와 타임 슬롯 이용률 관점에서 제안된 타부서치 알고리즘의 성능평가를 수행하였다. 성능평가 결과에서 제안된 타부서치 알고리즘은 이전에 제안된 다른 최적화 알고리즘보다 더 우수한 결과를 나타내었다.

Broadcast Scheduling Protocols in Multi-Hop Mobile Ad hoc Networks

When packets are sending in multi-hop mobile unintended networks numerous problems occur like flooding, rebroadcast, broadcast latency, power conservation and collision. If multiple transmission of packets simultaneously in MANETs that using the slot assignments approach, when additional channels are transmitting at the same time as the first slot allocations, interference may occur at the nodes. Because of the multi-hops data transfer, the network performance is hampered by the constrained bandwidth and therefore the self-initiated topological alterations. Therefore, a broadcast algorithm is important within the mobile ad hoc network for collision control and reliable communication. This paper proposes two new broadcasting protocols: modify SRBS and DSB algorithms. The planned algorithms outperform context of efficiency, reliability, traffic overload and reachability in highly mobile networks is an enhanced performance within the different environments. Evaluation of simulation results with other well-known exiting protocols as DFCN and PEGSP algorithms shows that the proposed protocol performance is best within the wireless network and channel bandwidths are well utilized within the network.

Efficient distributed broadcasting algorithms for cognitive radio networks-enabled smart agriculture

Smart agriculture has a broad prospect with the fast development of information technologies, such as Internet of Things, big data, edge computing and artificial intelligence. As more intelligent devices are deployed for agricultural scenarios, such as quality monitoring and information aggregation, the communication channels among these devices will be crowded and the performance can be greatly affected. Cognitive Radio Networks (CRNs) are promising in promoting better spectrum utilization, where unlicensed users can opportunistically use the vacant spectrum assigned to licensed users. On the basis of CRNs, many agricultural scenarios can be empowered with efficient communication capabilities. However, the broadcasting problem, which handles the information dissemination, has not been thoroughly studied in CRNs. Existing works are either centralized solutions performing broadcast on single/multiple channels, or distributed algorithms without performance guarantee for general networks. In this paper, we propose efficient distributed algorithms with short broadcast delay and high success ratio. The difficulties lie in the non-uniform channel availability, which entails broadcasting on multiple channels even for single-hop neighbors, and the distributed behaviors, where the users are only aware of the local information. Our contributions are threefold. First, we propose an efficient distributed rendezvous algorithm which spurs the neighbors to find the common channels in a short time. Second, we handle the single-hop broadcast by presenting two distributed algorithms and they guarantee a successful broadcast in O(Δ2loglogN) and Δ time slots respectively, where N is the number of channels and Δ is the maximum number of neighbors. Finally, we extend these algorithms to multi-hop broadcast and the broadcast delay is only up to D times the delay of single-hop, where D is the network diameter. We also conduct extensive simulations and the results corroborate our theoretical analyses.

Voice broadcast based on 5G sensor in urban fire emergency system application

With the rapid development of 5G sensors, the development of low cost, low power consumption, and miniaturization is also constantly progressing, and 5G sensor networks have achieved great development. Node positioning technology is an important support for 5G sensors, so it has been a hot research direction in recent years. This article has carried on the basic discussion to the speech broadcasting technology, and introduced the speech broadcasting coding in many aspects, including the development history, the current situation and the compression coding algorithm. This article has launched a basic analysis and discussion on the voice broadcast algorithm, such as its basic principles and classification. In order to minimize the property losses and casualties caused by urban fires and improve the efficiency and success rate of urban fire emergency systems, it is necessary to be able to query fire information in a timely and effective manner and formulate emergency protection. As we all know, China’s current economic development is in a period of steady improvement, and the process of urbanization is gradually accelerating, especially the number of high-rise and super high-rise buildings has increased significantly. Therefore, once a city fire occurs, it will not only cause huge losses of property, but also may cause a large number of casualties. Although the current fire protection system in Chinese cities is relatively complete, there are still some problems that have not been resolved in actual work, such as insufficient technical equipment and insufficient response speed in some areas due to economic constraints. Therefore, it is very necessary to establish an efficient urban fire emergency information system, not only to be able to query fire information in a timely and effective manner, but also to be able to formulate emergency support plans for specific actual situations.

Broadcast efficiency in mobile ad hoc networks: Dynamic methods and constant approximation

The term "MANET," which stands for "Mobile Adhoc Network," refers to an ad hoc wireless network incorporating routing mechanism atop an ad hoc link layer network. These networks consist of wirelessly linked mobile nodes that selfconfigure and self-heal. Due to frequent changes in network architecture, MANET nodes have the freedom to move. Each node in the network serves as a router, forwarding traffic to specified nodes. Broadcast algorithms in wireless ad hoc networks typically follow two main approaches: static and dynamic. In the static approach, local algorithms proactively determine each node's status based on local topology information and a globally known priority function. This paper reveals that existing local broadcast algorithms based on the static approach fail to achieve a satisfactory approximation factor for the optimum solution to an NP-hard problem. However, it is demonstrated that a constant approximation factor is attainable when relative position information is available. The hybrid broadcast method dynamically determines each node's state "on-the-fly," ensuring complete delivery and maintaining a consistent value approaching the ideal outcome as closely as possible.

Synthesis of Fault-Tolerant Reliable Broadcast Algorithms With Reinforcement Learning

Synthesis of Fault-Tolerant Reliable Broadcast Algorithms With Reinforcement Learning

Data Propagation for Low Latency Blockchain Systems

Broadcasting plays a vital role in the consensus mechanisms of blockchain systems, since the consensus of each block must wait until the previous block is received by (nearly) all the nodes in the blockchain systems. Therefore, optimizing the performance of broadcasting can significantly improve the performance of the blockchain system. However, compared with other traditional P2P applications such as file downloading or video delivery, the broadcasting in blockchain has two new requirements, namely low redundancy and low propagation latency, which all the existing mechanisms (e.g. flooding, structural DHT etc.) can not meet well. In this paper, we propose Swift, a new broadcasting mechanism for blockchain systems. It optimizes the P2P topology construction and broadcast algorithm in the structured network based on unsupervised learning and greedy algorithm, effectively reducing the propagation latency of the blockchain P2P network while avoiding the waste of redundant bandwidth. We implemented a prototype of Swift and evaluated its performance on a testbed network that consists of 1000 blockchain nodes. The experimental findings show that Swift can reduce propagation latency by 19.8% with similar bandwidth consumption, generating an 18% increase in the throughput performance of the blockchain. Finally, with the increase in connections, Swift can simultaneously achieve low latency and maintain a relatively stable redundant bandwidth waste, instead of linearly increasing in flooding.

Efficient and competitive broadcast in multi-channel radio networks

Consider a single-hop, multi-channel, synchronous radio network in which a source node needs to disseminate a message to all other n−1 nodes. An adversary called Eve, which captures environmental noise and potentially malicious interference, aims to disrupt this process via jamming. Assume sending, listening, or jamming on one channel for one time slot costs one unit of energy. The question is, if Eve spends T units of energy on jamming, can we devise broadcast algorithms in which each node's cost is o(T)? Previous results show such resource competitive algorithms do exist in the single-channel setting: for large T values, each node can receive the message within O(T) time slots while spending only O˜(T/n) energy.In this work, we devise new broadcast algorithms and show that the existence of multiple channels allows faster message dissemination while preserving resource competitiveness. Specifically, if C channels are available, for large T values, our algorithms guarantee each node's runtime is O(T/C), and each node's energy cost is O˜(T/n). Moreover, our algorithms require minimal prior knowledge and allow Eve to be adaptive. Our technical contributions lie in using “epidemic broadcast” in algorithm design to achieve time efficiency and resource competitiveness, and employing coupling techniques in the analysis to handle the adaptivity of the adversary.We also complement algorithmic results with lower bounds, proving both the time complexity and the energy complexity of our algorithms are optimal or near-optimal. In particular, to obtain the lower bound on resource competitiveness, we first prove a new lower bound showing any multi-channel 1-to-1 communication algorithm succeeding with constant probability incurs expected cost of at least Ω(T); then, via simulation and reduction arguments, we show for the broadcast problem, some node incurs a cost of at least Ω(T/n), even in the multi-channel setting.

Dynamic resource scheduling for real-time group broadcasting in 6G cellular vehicular networks

Vehicle-to-Vehicle (V2V) messaging is an indispensable component of connected autonomous vehicle systems. The 3rd Generation Partnership Project (3GPP) is designed to support V2V communication without any infrastructure using sensing-based Semi-Persistent Scheduling (SPS) in order to avoid resource collisions for Cooperative Awareness Messages (CAMs) transmission. However, the legacy system suffers from significant collisions in a traffic congestion environment and resource waste in light traffic conditions. To address these problems, in this paper we propose a novel dynamic resource scheduling algorithm for real-time group broadcasting, inspired by the Lyapunov optimization framework, where the optimization objective is to minimize time-average failure probability subject to queue stability. Through extensive simulations, we show that the proposed scheduling algorithm outperforms the standard in both traffic jams and leisurely road environments.

Model-based selection of optimal MPI broadcast algorithms for multi-core clusters

The performance of collective communication operations determines the overall performance of MPI applications. Different algorithms have been developed and implemented for each MPI collective operation, but none proved superior in all situations. Therefore, MPI implementations have to solve the problem of selecting the optimal algorithm for the collective operation depending on the platform, the number of processes involved, the message size(s), etc. The current solution method is purely empirical.Recently, an alternative solution method using analytical performance models of collective algorithms has been proposed and proved both accurate and efficient for one-process-per-CPU configurations. The method derives the analytical performance models of algorithms from their code implementation rather than from high-level mathematical definitions, and estimates the parameters of the models separately for each algorithm. The method is network and topology oblivious and uses the Hockney model for point-to-point communications. In this paper, we extend that selection method to the case of clusters of multi-core processors, where each core of the platform runs a process of the MPI application.We present the proposed approach using Open MPI broadcast algorithms, and experimentally validate it on three different clusters of multi-core processors, Grisou, Gros and MareNostrum4.

Dynamic Byzantine Broadcast in Asynchronous Message-Passing Systems

The <i>reconfiguration</i> problem is considered a key challenge in distributed systems, especially in <i>dynamic</i> asynchronous message-passing systems. To keep the data reliability and availability in long-lived systems, any protocols should support reconfigurations, to dynamically add resources, or remove old and slow machines with newer faster ones. Previous results in reconfigurations either rely on consensus, or study the problem restricted to crash failures only. However, it is difficult to argue that real-world systems experience crash failures only. In this paper, we study the dynamic reconfiguration problem in fully asynchronous message-passing systems with Byzantine faults. We first specify dynamic Byzantine broadcast, and then specify a clean and explicit liveness condition. We show that dynamic Byzantine broadcast is solvable by presenting a dynamic Byzantine consistent broadcast algorithm and a dynamic Byzantine reliable broadcast algorithm.