Communicating over multi-hop connections simplifies the establishment of wireless multi-hop networks but brings new challenges such as limited reliability, bottlenecks, and weak connections. The minimum cut of a graph...
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Communicating over multi-hop connections simplifies the establishment of wireless multi-hop networks but brings new challenges such as limited reliability, bottlenecks, and weak connections. The minimum cut of a graph is the smallest subset of edges whose removal disconnects some nodes from the others. Finding minimum cuts of a wireless multi-hop network may reveal useful information such as bottlenecks and critical areas. This article introduces a distributed algorithm for detecting minimum cuts of a given witless multi-hop network by finding available edge-disjoint paths. Initially, the paths between two arbitrary neighbors are detected and these nodes are grouped as visited nodes. Then, the other nodes are added to the visited group one by one by finding at most O(n) paths in total where n is the number of nodes. The comprehensive simulation results showed that the proposed asynchronous algorithm detects minimum cuts with up to 37.1 and 55.8 percent lower sent bytes than the existing synchronous and central algorithms, respectively.
We study a multi-agent resilient consensus problem, where some agents are of the Byzantine type and try to prevent the normal ones from reaching consensus. In our setting, normal agents communicate with each other asy...
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We study a multi-agent resilient consensus problem, where some agents are of the Byzantine type and try to prevent the normal ones from reaching consensus. In our setting, normal agents communicate with each other asynchronously over multi-hop relay channels with delays. To solve this asynchronous Byzantine consensus problem, we develop the multi-hop weighted mean subsequence reduced (MWMSR) algorithm. The main contribution is that we characterize a tight graph condition for our algorithm to achieve Byzantine consensus, which is expressed in the novel notion of strictly robust graphs. We show that the multi-hop communication is effective for enhancing the network's resilience against Byzantine agents. As a result, we also obtain novel conditions for resilient consensus under the malicious attack model, which are tighter than those known in the literature. Furthermore, the proposed algorithm can be viewed as a generalization of the conventional flooding-based algorithms, with less computational complexity. Lastly, we provide numerical examples to show the effectiveness of the proposed algorithm. (c) 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license
Stable communication is a vital and challenging requirement in wireless multi-hop networks because nodes failure may disconnect other active nodes. Minimum s-t cuts can help to measure the reliability of a network reg...
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Stable communication is a vital and challenging requirement in wireless multi-hop networks because nodes failure may disconnect other active nodes. Minimum s-t cuts can help to measure the reliability of a network regarding the nodes or links failure. A minimum s-t cut is the smallest subset of links that their failure disconnects all communication paths between nodes s and t. Minimum s-t cuts can also reveal the bottlenecks, bridges, and clusters in the network. This paper proposes an asynchronousdistributed algorithm for finding minimum s-t cuts in wireless multi-hop networks. The proposed algorithm iteratively finds link-disjoint paths from s to t and changes the direction of the selected edges to ignore them in the next iteration. After finding all paths, the undiscovered nodes in the last search determine the minimum s-t cut. The comprehensive simulation results on different networks with up to 500 nodes show that the proposed algorithm finds minimum s-t cuts in reasonable time with up to 64% and 39% lower energy consumption than the existing central and distributedalgorithms, respectively. (C) 2020 Elsevier B.V. All rights reserved.
asynchronous executions of a distributed algorithm differ from each other due to the nondeterminism in the order in which the messages exchanged are handled. In many situations of interest, the asynchronous executions...
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asynchronous executions of a distributed algorithm differ from each other due to the nondeterminism in the order in which the messages exchanged are handled. In many situations of interest, the asynchronous executions induced by restricting nondeterminism are more efficient, in an application-specific sense, than the others. In this work, we define partially ordered executions of a distributed algorithm as the executions satisfying some restricted orders of their actions in two different frameworks, those of the so-called event- and pulse-driven computations. The aim of these restrictions is to characterize asynchronous executions that are likely to be more efficient for some important classes of applications. Also, an asynchronous algorithm that ensures the occurrence of partially ordered executions is given for each case. Two of the applications that we believe may benefit from the restricted nondeterminism are backtrack search, in the event-driven case. and iterative algorithms for systems of linear equations. in the pulse-driven case. We provide some experimental evidence in these two cases. (c) 2008 Elsevier B.V. All rights reserved.
This paper presents Worm-IT, a new intrusion-tolerant group communication system with a membership service and a view-synchronous atomic multicast primitive. The system is intrusion-tolerant in the sense that it behav...
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This paper presents Worm-IT, a new intrusion-tolerant group communication system with a membership service and a view-synchronous atomic multicast primitive. The system is intrusion-tolerant in the sense that it behaves correctly even if some nodes are corrupted and become malicious. It is based on a novel approach that enhances the environment with a special secure distributed component used by the protocols to execute securely a few crucial operations. Using this approach, we manage to bring together two important features: Worm-IT tolerates the maximum number of malicious members possible;it does not have to detect the failure of primary-members, a problem in previous intrusion-tolerant group communication systems. (C) 2006 Elsevier Inc. All rights reserved.
Motivation. Recommendation systems are an important ingredient of modern life, where people must make decisions with partial information [6]. Everyday examples include buying books, going to a movie, choosing an on-li...
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We propose a heuristic for solving the maximum independent set problem for a set of processors in a network with arbitrary topology. We assume an asynchronous model of computation and we use modified Hopfield neural n...
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We propose a heuristic for solving the maximum independent set problem for a set of processors in a network with arbitrary topology. We assume an asynchronous model of computation and we use modified Hopfield neural networks to find high quality solutions. We analyze the algorithm in terms of the number of rounds necessary to find admissible solutions both in the worst case (theoretical analysis) and in the average case (experimental Analysis). We show that our heuristic is better than the greedy one at 1% significance level.
Group mutual exclusion is an interesting generalization of the mutual exclusion problem. This problem was introduced by Joung, and some algorithms for the problem have been proposed by incorporating mutual exclusion a...
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Group mutual exclusion is an interesting generalization of the mutual exclusion problem. This problem was introduced by Joung, and some algorithms for the problem have been proposed by incorporating mutual exclusion algorithms. Group mutual exclusion occurs naturally in a situation where a resource can be shared by processes of the same group, but not by processes of a different group. It is also called the congenial talking philosophers problem. In this paper we propose two algorithms based on ticket orders for the group mutual exclusion problem on the asynchronous shared memory model. These algorithms are some modifications of the Bakery algorithm. They satisfy lockout freedom and a high degree of concurrency performance. Each of these algorithms uses single-writer shared variables together with two multi-writer shared variables that are never concurrently written. One of these algorithms has another desirable property, called smooth admission. By this property, during the period that the resource is occupied by the leader (called the chair), a process wishing to join the same group as the leader's group can be granted use of the resource in constant time.
asynchronousdistributed decision-making (ADDM) systems constitute a special class of distributed problems and are characterized as large, complex systems wherein the principal elements are the geographically disperse...
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asynchronousdistributed decision-making (ADDM) systems constitute a special class of distributed problems and are characterized as large, complex systems wherein the principal elements are the geographically dispersed entities that communicate among themselves, asynchronously, through message passing and are permitted autonomy in local decision making. Such systems generally offer significant advantages over the traditional, centralized algorithms in the form of concurrency, scalability, high throughput, efficiency, low vulnerability to catastrophic failures, and robustness. A fundamental property of ADDM systems is stability that refers to their behavior under representative perturbations to their operating environments, given that such systems are intended to be real, complex, and to some extent, mission-critical, and are subject to unexpected changes in their operating conditions. This paper introduces the concept of stability in ADDM systems and proposes an intuitive yet practical and usable definition that is inspired by those used in control systems and physics. An ADDM system is defined as a stable system if it returns to a steady state in finite time, following perturbation, provided that it is initiated in a steady state. Equilibrium or steady state is defined through placing bounds on the measured error in the system. Where the final steady state is equivalent to the initial one, a system is referred to as strongly stable, If the final steady state is potentially worse then the initial one, a system is deemed marginally stable. When a system fails to return to steady state following the perturbation, it is unstable. The perturbations are classified as either changes in the input pattern or changes in one or more environmental characteristics of the system, such as hardware failures. For a given ADDM system, the definitions are based on the performance indices that must be judiciously identified by the system architect and are likely to be unique. To facil
asynchronous, distributed, decision-making (ADDM) systems constitute a special class of distributed problems and are characterized as large, complex systems wherein the principal elements are the geographically-disper...
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asynchronous, distributed, decision-making (ADDM) systems constitute a special class of distributed problems and are characterized as large, complex systems wherein the principal elements are the geographically-dispersed entities that communicate among themselves, asynchronously, through message passing and are permitted autonomy in local decisionmaking. A fundamental property of ADDM systems is stability that refers to their behavior under representative perturbations to their operating environments, given that such systems are intended to be real, complex, and to some extent, mission critical systems, and are subject to unexpected changes in their operating conditions. ADDM systems are closely related to autonomous decentralized systems (ADS) in the principal elements, the difference being that the characteristics and boundaries of ADDM systems are defined rigorously. This paper introduces the concept of stability in ADDM systems and proposes an intuitive yet practical and usable definition that is inspired by those used in Control Systems and Physics. A comprehensive stability analysis on an accurate simulation model will provide the necessary assurance, with a high level of confidence, that the system will perform adequately. An ADDM system is defined as a stable system if it returns to a steady-state in finite time, following perturbation, provided that it is initiated in a steady-state. Equilibrium or steady-state is defined through placing bounds on the measured error in the system. Where the final steady-state is equivalent to the initial one, a system is referred to as strongly stable. If the final steady-state is potentially worse then the initial one, a system is deemed marginally stable. When a system fails to return to steady-state following the perturbation, it is unstable. The perturbations are classified as either changes in the input pattern or changes in one or more environmental characteristics of the system such as hardware failures. Thus, the ke
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