Reliability analysis of cluster-based ad-hoc networks

Cook, Jason L.; Ramírez-Márquez, José Emmanuel

doi:10.1016/j.ress.2007.09.002

Cited by 35 publications

(17 citation statements)

References 18 publications

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“…Connectivity reliability [1][2][3][4][5][6][7] investigates the probability that the network is still connected for a given period of time under the case of some nodes or links failure. Performance reliability [8,9] analyzes the end-to-end delay, packet delivery rate, and other network parameters.…”

Section: Related Workmentioning

confidence: 99%

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Transmission Reliability Evaluation for Wireless Sensor Networks

Zhu

Lü

Han

et al. 2016

International Journal of Distributed Sensor Networks

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Network reliability of Wireless Sensor Networks (WSNs) is difficult to be evaluated because of its complexity, multistates, and dynamic characteristics. To satisfy the user's need of reliability evaluation for network transmission we propose some evaluation models and a dynamical evaluation framework. The evaluation models are mission-oriented and based on transmission paths (uplink and downlink). The dynamic evaluation framework can be on-demand customized and it will be autoupdated once the communication environment changes or the nodes fail. Finally, we simulated clustered and mesh WSNs with NS-2. Simulation result shows that the proposed evaluation framework was effective and accurate.

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Section: Related Workmentioning

confidence: 99%

“…Network simulation becomes an important method to analyze network reliability. Monte Carlo [7], Petri nets [5], 2 International Journal of Distributed Sensor Networks Bayesian networks [11], and other simulation methods have been used.…”

Section: Related Workmentioning

confidence: 99%

Transmission Reliability Evaluation for Wireless Sensor Networks

Zhu

Lü

Han

et al. 2016

International Journal of Distributed Sensor Networks

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“…Cook and Ramirez-Marquez [1] and [5][6][7][8][9][10] have developed methods for the analysis of ad-hoc network reliability. These address the unique nature of ad-hoc networks which have no fixed infrastructure and as such take on a dynamic nature with respect to the reliability wise system description.…”

Section: Ad-hoc Network Reliabilitymentioning

confidence: 99%

“…A later extension of this work addresses a capacity based method [7]. While most recent papers look to solve the same problems for the analysis of multi-tier network reliability [8][9] and multitier network optimization [10].…”

Section: Ad-hoc Network Reliabilitymentioning

confidence: 99%

System of systems reliability for multi-state systems

Cook

2009

2009 Annual Reliability and Maintainability Symposium

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The proliferation of networking technologies in commercial, consumer, and industrial applications has been mirrored in the defense industry. The US Department of Defense, along with comparable organizations abroad, have adopted a network centric paradigm for emerging and future systems. This migration to an information based approach is akin to the move to Just-In-Time manufacturing. That is, both approaches seek to achieve synergies from Information rather than from bulk of material. In the JIT case, this material is the component parts or materials, and in the military SoS the material may be armor and/or ammunition. Specifically, the US military is attempting to leverage the synergies of net centricity in order to obtain a more mobile and lighter fighting fleet that retains the same lethality and survivability by shedding armor and ammo in favor of information (radios and computers). In previous years, this author has presented papers on network reliability [1] and multi-state reliability [2] to the RAMS. In this year's paper, the notion of multi-state reliability is combined with the ad-hoc network reliability methods. This integrated model provides the ability to measure, in capacity terms the reliability of a SoS level by considering the network's state (connectivity) temporally and the interactions and contributions of its elements. Specifically, this paper describes a mathematical construct for simulating the capacity of general functions including lethality, mobility, survivability, reconnaissance, and supportability based upon traditional probabilistic measures of reliability. Next, the paper will describe a new method to combine those platform capabilities to an aggregate SoS level capability that is dependent on the connectivity between those nodes and the resultant synergies realized due to said connectivity.

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“…High reliability is an important factor that improves customer satisfaction. The reliability theory and methods is well developed [5][6][7], such as the Monte Carlo method, fault tree, minimal cut sets, fuzzy theory, neural network, Markov state diagram, stochastic Petri net, can used to analyze and evaluate the reliability of complex systems. Although these methods have contributed to the evaluation of reliability, but still do not give the suggestion to improve reliability.…”

Section: Introductionmentioning

confidence: 99%

Reliability Design Model Research of Next-Generation Network Based on Bio-Network

Liang

Ding

Fang

et al. 2009

2009 Asia-Pacific Conference on Information Processing

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Inspired by the reliability maintenance mechanisms in biology systems, based on bio-network platform, a reliability design model for next-generation network is proposed. In designing the structures of bio-network and bio-entity, the reliability mechanisms are incorporated to gain the reliability maintenance capability when the entities delegate the function entities in the next-generation network. The simulation results show that the model can obtain the evolutionary capability of reliability maintenance in the frequently corrupted environments.

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Reliability analysis of cluster-based ad-hoc networks

Cited by 35 publications

References 18 publications

Transmission Reliability Evaluation for Wireless Sensor Networks

Transmission Reliability Evaluation for Wireless Sensor Networks

System of systems reliability for multi-state systems

Reliability Design Model Research of Next-Generation Network Based on Bio-Network

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