What model and what conditions to implement unreliable failure detectors in dynamic networks?

Greve, Fabíola; Arantes, Luciana; Sens, Pierre

doi:10.1145/2034640.2034645

Cited by 11 publications

(9 citation statements)

References 18 publications

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“…Variants of these classes can be found in recent literature, e.g. in [33] where the assumption that connectivity over time eventually takes place among a stable subset of the nodes is used to implement failure detectors in dynamic networks.…”

Section: Tvg Classesmentioning

confidence: 99%

Time-varying graphs and dynamic networks

Casteigts

Flocchini

Quattrociocchi

et al. 2012

International Journal of Parallel, Emergent and Distributed Sys

523

484

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The past few years have seen intensive research efforts carried out in some apparently unrelated areas of dynamic systems -delay-tolerant networks, opportunistic-mobility networks, social networksobtaining closely related insights. Indeed, the concepts discovered in these investigations can be viewed as parts of the same conceptual universe; and the formal models proposed so far to express some specific concepts are components of a larger formal description of this universe. The main contribution of this paper is to integrate the vast collection of concepts, formalisms, and results found in the literature into a unified framework, which we call TVG (for time-varying graphs). Using this framework, it is possible to express directly in the same formalism not only the concepts common to all those different areas, but also those specific to each. Based on this definitional work, employing both existing results and original observations, we present a hierarchical classification of TVGs; each class corresponds to a significant property examined in the distributed computing literature. We then examine how TVGs can be used to study the evolution of network properties, and propose different techniques, depending on whether the indicators for these properties are a-temporal (as in the majority of existing studies) or temporal. Finally, we briefly discuss the introduction of randomness in TVGs.

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Section: Tvg Classesmentioning

confidence: 99%

Time-varying graphs and dynamic networks

Casteigts

Flocchini

Quattrociocchi

et al. 2012

International Journal of Parallel, Emergent and Distributed Sys

523

484

View full text Add to dashboard Cite

show abstract

“…The neighbourhood of a mobile node may change once moves. In addition, we assume that follows the passive mobility model [23], which means does not know that it is moving. Hence, it cannot inform its neighbours about its mobility.…”

Section: System Modelmentioning

confidence: 99%

“…That is, = | | − . Knowing that | | > 2 , and ≥ + 1 [23,34,37]. Indeed, the value of depends on the network type and the current topology of the network.…”

Section: Time-free Comparison-based Diagnostic Modelmentioning

confidence: 99%

“…The early idea of this model has been presented in [22]. This model is inspired by asynchronous implementations of failure detectors [23][24][25], and the computation model for dynamic systems [26]. The proposed model exploits message exchange patterns rather than timers to identify the faulty status of nodes and thus it is suitable for asynchronous systems and mobile wireless networks.…”

Section: Introductionmentioning

confidence: 99%

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The Time-Free Comparison Model for Fault Diagnosis in Wireless Ad Hoc Networks

et al. 2020

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This paper describes a new comparison-based model for fault diagnosis in wireless ad hoc networks. Fault diagnosis is crucial for ensuring the dependability of systems. Wireless ad hoc networks are highly prone to faults as consequence of their dynamical conditions. The comparison approach is a practical diagnosis model that has been used to develop self-diagnosis systems in wired and wireless networks. This approach can detect and diagnose hard and soft faults in systems. The traditional fault diagnostic models were designed for static networks. Thus, they cannot provide complete and correct fault diagnosis in mobile wireless networks. In this paper, we introduce a time-free self-diagnosis model that respects the design requirements of mobile wireless networks. That is, it adapts to the topology's changes, it imposes no known bounds on time delays, and it requires limited network information. Further, we develop a fault diagnosis protocol that can correctly diagnose faulty nodes undergoing static and dynamic faults in mobile ad-hoc networks (MANETs). Both an analytical model and a simulation study have been used to prove and evaluate the efficiency of our protocol under various scenarios. Furthermore, the performance of our protocol is compared with related protocols. The results show that our proposed protocol is efficient in terms of communication and time complexity.

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“…The performance evaluation of this protocol shows a significant overhead in message exchange. In the same authors discussed under which conditions the previous algorithm can be improved so that to better cope with MANET constraints. In , the previous protocol was improved by removing some of the assumptions so that it can better cope with mobile environment constraints.…”

Section: Failure Detector Protocolsmentioning

confidence: 99%

Towards an efficient failure detection in MANETs

Benkaouha

Abdelli

Ben‐Othman

et al. 2016

Wirel. Commun. Mob. Comput.

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Mobile ad hoc networks (MANETs) are characterized by a dynamic topology and generally deployed in a hostile environment with limited resources. As a result, the nodes are more vulnerable and are often subject to failures. Therefore, the design of an efficient failure detector in MANETs is a very challenging issue as the detection is proved to be unreliable. Such an achievement amounts to balance between the performances of the accuracy, the completeness and the resource consumption. We present and discuss in this paper a solution for an efficient failure detection in MANETs. This new protocol, called efficient failure detection for MANETs, exploits different mechanisms to improve the completeness and the accuracy of the detection while reducing the traffic overhead. The number of used timers are limited to two for each node thus reducing the complexity of the algorithm. The simulations performed on NS2 platform show the efficiency of efficient failure detection for MANETs comparing with other protocols.

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What model and what conditions to implement unreliable failure detectors in dynamic networks?

Cited by 11 publications

References 18 publications

Time-varying graphs and dynamic networks

Time-varying graphs and dynamic networks

The Time-Free Comparison Model for Fault Diagnosis in Wireless Ad Hoc Networks

Towards an efficient failure detection in MANETs

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