This paper investigates the obstacle avoidance problem for a multi-unmanned surface vehicle (USV) team based on the use of stream function and consensus algorithm. A new collision avoidance strategy for multi-USV form...
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This paper investigates the obstacle avoidance problem for a multi-unmanned surface vehicle (USV) team based on the use of stream function and consensus algorithm. A new collision avoidance strategy for multi-USV formation is proposed, where the complex potential derived from a stream function is utilized based on a consensus control algorithm with each USV being a particle mimicking the flow around the fluid along its streamline to avoid obstacles. After obstacle avoidance, each USV quickly continues to achieve the formation movement along the original trajectory. Collision avoidance between two multi-USV teams with master-slave is discussed. According to the proposed strategy, each USV of the slave multi-USV team could actively avoid the master multi-USV team treated as a moving obstacle. The effectiveness of the proposed algorithms is verified through simulation studies.
The continuous growth of the mobile apps industry creates a competition among apps developers. To succeed, app developers must attract and retain users. User reviews provide a wealth of information about bugs to fix a...
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ISBN:
(数字)9781728173030
ISBN:
(纸本)9781728173030
The continuous growth of the mobile apps industry creates a competition among apps developers. To succeed, app developers must attract and retain users. User reviews provide a wealth of information about bugs to fix and features to add and can help app developers offer high-quality apps. However, apps may receive hundreds of unstructured reviews, which makes transforming them into change requests a difficult task. Approaches exist for analyzing and extracting topics from mobile app reviews, however, prioritizing these reviews has not gained much attention. In this study, we introduce the use of a consensus algorithm to help developers prioritize user reviews for the purpose of app evolution. We evaluate the usefulness of our approach and meaningfulness of its consensus rankings on four Android apps. We compare the rankings against reviews ranked by app developers manually and show that there is a strong correlation between the two (average Kendall rank correlation coefficient = 0.516). Thus, our approach can prioritize user reviews and help developers focus their time/effort on improving their apps instead of on identifying reviews to address in the next release.
consensus algorithms in distributed systems have attracted much attention in recent studies. However, there is a need for a classification that leads to better understanding and helps direct the deployment of such alg...
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ISBN:
(数字)9781728137834
ISBN:
(纸本)9781728137834
consensus algorithms in distributed systems have attracted much attention in recent studies. However, there is a need for a classification that leads to better understanding and helps direct the deployment of such algorithms. In this paper, we classify common consensus algorithms based on how they decide the order of system state changes. We then determine the extent to which each category prioritizes scalability, decentralization, and security. As with other engineering design scenarios, this is a choose-two tradeoff. Our key contribution is that, based on this taxonomy of tradeoffs, we are able to discern the types of consensus algorithms that work well within the application area(s) for a given distributed system. We find that a dichotomy of algorithms between leader-based and voting-based consensus algorithms emerges from this taxonomy. Applications of this classification scheme include several different categories of distributed ledgers such as blockchains and directed acyclic graphs (DAGs).
In this brief, a distributed control algorithm is proposed to solve the economic dispatch problem. Without a central control unit, the generators work collaboratively to minimize the generation cost while balancing th...
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In this brief, a distributed control algorithm is proposed to solve the economic dispatch problem. Without a central control unit, the generators work collaboratively to minimize the generation cost while balancing the supply and demand. The proposed method is based on consensus protocols and the saddle point dynamics. The consensus protocols are employed to estimate the global information in a distributed fashion, and the saddle point dynamics are leveraged to search for the optimal solution of the economic dispatch problem. By utilizing Lyapunov stability analysis, exponential stability of the optimal solution is derived if the capacity limits of the generators are not considered;with the capacity limits, practical stability of the optimal solution is obtained. No global information is needed in the proposed method, and the requirement on initial conditions of the state variables is mild. Several case studies on the IEEE 9-bus and IEEE 118-bus systems are presented to demonstrate the effectiveness of the proposed algorithms.
How to reach an agreement in a blockchain network is a complex and important task that is defined as a consensus problem and has wide applications in reality including distributed computing, load balancing, and transa...
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How to reach an agreement in a blockchain network is a complex and important task that is defined as a consensus problem and has wide applications in reality including distributed computing, load balancing, and transaction validation in blockchains. Over recent years, many studies have been done to cope with this problem. In this paper, a comparative and analytical review on the state-of-the-art blockchain consensus algorithms is presented to enlighten the strengths and constraints of each algorithm. Based on their inherent specifications, each algorithm has a different domain of applicability that yields to propose several performance criteria for the evaluation of these algorithms. To overview and provide a basis of comparison for further work in the field, a set of incommensurable and conflicting performance evaluation criteria is identified and weighted by the pairwise comparison method. These criteria are classified into four categories including algorithms' throughput, the profitability of mining, degree of decentralization and consensus algorithms vulnerabilities and security issues. Based on the proposed framework, the pros and cons of consensus algorithms are systematically analyzed and compared in order to provide a deep understanding of the existing research challenges and clarify the future study directions. (C) 2020 Elsevier Ltd. All rights reserved.
In a Blockchain network multiple nodes across the network verify each transaction and preserve them without having a centralized authority. Verification and insertion of transactions are achieved through distributed c...
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ISBN:
(纸本)9781728158754
In a Blockchain network multiple nodes across the network verify each transaction and preserve them without having a centralized authority. Verification and insertion of transactions are achieved through distributed cryptographic mechanism called consensus protocol. consensus protocol involves the application of reputable concepts like Distributed Computing (P2P Networks), Cryptography and consensus algorithms. Traditional motivation for application of consensus Protocols is to warrant reliability in the distributed systems. The basic assumption behind this protocol is, a 'value' must have been proposed by some truthful node in the distributed system. Distributed consensus is attained once all the nodes present in the system agrees and approves the same value. At any given time, all nodes have a sequence of block of transactions, they have already reached consensus on. Also each node has a set of outstanding transactions it has heard about from other nodes. This consensus is achieved via various algorithms which serve as the backbone for Blockchain architecture. Once the transactions are verified, they will be included in the existing chain. The main advantage of such systems is the fact that they are immutable, transparent and distributed. Though stated simple, reaching consensus may be difficult due to various reasons such as crash of active node, presence of malicious nodes, faults in the network, latency (no global time) and not all pairs may be connected. A consensus algorithm ensures that the one and only version of truth gets added into the network, in addition to keeping malevolent people from tampering the network. It also makes sure that the system is fully decentralized. If everyone in the network is strictly honest, there is no need of consensus, however the probability of such existence is very less. Hence, we are undeniably in need of virtuous consensus algorithms for a strong, immortal Blockchain network. The process of selection and enactment of the
Determining the network size is a critical process in numerous areas (e.g., computer science, logistic, epidemiology, social networking services, mathematical modeling, demography, etc.). However, many modern real-wor...
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Determining the network size is a critical process in numerous areas (e.g., computer science, logistic, epidemiology, social networking services, mathematical modeling, demography, etc.). However, many modern real-world systems are so extensive that measuring their size poses a serious challenge. Therefore, the algorithms for determining/estimating this parameter in an effective manner have been gaining popularity over the past decades. In the paper, we analyze five frequently applied distributed consensus gossip-based algorithms for network size estimation in multi-agent systems (namely, the Randomized gossip algorithm, the Geographic gossip algorithm, the Broadcast gossip algorithm, the Push-Sum protocol, and the Push-Pull protocol). We examine the performance of the mentioned algorithms with bounded execution over random geometric graphs by applying two metrics: the number of sent messages required for consensus achievement and the estimation precision quantified as the median deviation from the real value of the network size. The experimental part consists of two scenarios-the consensus achievement is conditioned by either the values of the inner states or the network size estimates-and, in both scenarios, either the best-connected or the worst-connected agent is chosen as the leader. The goal of this paper is to identify whether all the examined algorithms are applicable to estimating the network size, which algorithm provides the best performance, how the leader selection can affect the performance of the algorithms, and how to most effectively configure the applied stopping criterion.
With the development of Internet of Things (IoT) and blockchain technologies, people find more and more blockchain applications in the IoT domain. While it is reasonable that IoT systems use hierarchical network struc...
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ISBN:
(纸本)9781538679753
With the development of Internet of Things (IoT) and blockchain technologies, people find more and more blockchain applications in the IoT domain. While it is reasonable that IoT systems use hierarchical network structures, their sheer large scales may lead to hundreds or even thousands of non-leaf nodes, which may serve as full nodes when participating in IoT blockchains. From IoT blockchain design perspective, it is important to understand the scalability of the energy consumption feature of IoT blockchains. In our research we have collected real-world data that reflect the energy consumption features of several consensus algorithms of blockchain. In this work-in-progress paper, we report our results based on linear regression models. These models provide reference estimations of the energy consumption impact in designing blockchains for IoT systems.
Cryptocurrencies have seen a massive surge in popularity and behind these new virtual currencies is an innovative technology called the blockchain: a distributed digital ledger in which cryptocurrency transactions are...
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ISBN:
(纸本)9789532330953
Cryptocurrencies have seen a massive surge in popularity and behind these new virtual currencies is an innovative technology called the blockchain: a distributed digital ledger in which cryptocurrency transactions are recorded after having been verified. The transactions within a ledger are verified by multiple clients or "validators," within the cryptocurrency's peer-to-peer network using one of many varied consensus algorithms for resolving the problem of reliability in a network involving multiple unreliable nodes. The most widely used consensus algorithms are the Proof of Work (PoW) algorithm and the Proof of Stake (PoS) algorithm;however, there are also other consensus algorithms which utilize alternative implementations of PoW and PoS, as well as other hybrid implementations and some altogether new consensus strategies. In this paper, we perform a comparative analysis of typical consensus algorithms and some of their contemporaries that are currently in use in modern blockchains. Our analysis focuses on the algorithmic steps taken by each consensus algorithm, the scalability of the algorithm, the method the algorithm rewards validators for their time spent verifying blocks, and the security risks present within the algorithm. Finally, we present our conclusion and some possible future trends for consensus algorithms used in blockchains.
We consider a distributed consensus problem over a network, where at each time instant every node receives two pieces of information from disjoint neighboring sets: a weighted average of current states of neighbors fr...
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We consider a distributed consensus problem over a network, where at each time instant every node receives two pieces of information from disjoint neighboring sets: a weighted average of current states of neighbors from a primary network, and a weighted average of one-hop delayed states of neighbors from a secondary network. The proposed algorithm makes each node update its state to a weighted average of these individual averages. We show that convergence to consensus is guaranteed with non-trivial weights. We also present an explicit formula for the weights allocated to each piece of the information for the optimal rate of convergence, when the secondary network is the complement of the primary network. Finally numerical examples are given to explore the case when the neighbor sets of the agents do not cover the whole network. (C) 2017 Elsevier Ltd. All rights reserved.
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