Capacitated Reliability for Ad-hoc Networks

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

doi:10.1109/rams.2007.328058

Cited by 3 publications

(7 citation statements)

References 8 publications

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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%

“…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. These publications include methods for terminal reliability in a binomial case [1], [5], and [6], where the network and its nodes are either operational or not. A later extension of this work addresses a capacity based method [7].…”

Section: Ad-hoc Network Reliabilitymentioning

confidence: 99%

“…For the binomial case, reliability takes on the traditional definition as the probability that the item is operational over a given time, t, see Equation 1. Although the failure probability may take on any distribution, the Exponential and Weibull are the most often used in reliability analyses, see Equation 2 and 3; respectively.…”

Section: Technical Considerationsmentioning

confidence: 99%

“…It is important to note the network simulated had a link reliability of 0.7, this is the probability of a link between platform i and j is 0.7, or as denoted in [1], P(l ij = 1) = 0.7. The results of the analysis are intuitively dependent upon the reliability characteristics of the network as well as the reliability (failure) parameters which describe the systems modes of failure or performance degradation.…”

Section: 25mentioning

confidence: 99%

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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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Section: Ad-hoc Network Reliabilitymentioning

confidence: 99%

Section: Ad-hoc Network Reliabilitymentioning

confidence: 99%

Section: Technical Considerationsmentioning

confidence: 99%

Section: 25mentioning

confidence: 99%

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System of systems reliability for multi-state systems

Cook

2009

2009 Annual Reliability and Maintainability Symposium

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“…To date, Cook and Ramirez-Marquez [8][9][10][11][12] have focused on a single cohesive MAWN rather than the cluster-based MAWN. The Monte Carlo simulation method in [8] is adapted in this paper to accommodate the more flexible and scalable cluster-based MAWN.…”

Section: Wireless and Ad-hoc Network Reliabilitymentioning

confidence: 99%

Reliability for cluster-based Ad-hoc Networks

Cook

Ramírez-Márquez²

2008

2008 Annual Reliability and Maintainability Symposium

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The Mobile Ad-hoc Wireless Network (MAWN) is a new and emerging network scheme that is being employed in a variety of applications. The MAWN varies from traditional networks because it is a self-forming and dynamic network. The MAWN is free of infrastructure and as such only the mobile nodes comprise the network. Nodes communicate either directly or through other nodes. To do so each node acts as source, destination, and relay. The virtue of a MAWN is the flexibility this provides however the challenge for reliability analyses is also brought about by this unique feature. The variability and volatility of the MAWN's configuration makes typical reliability methods (e.g. reliability block diagram) inappropriate because no single structure or configuration represents all manifestations of a MAWN. For this reason, new methods are being developed to analyze the reliability of this new networking technology. New published methods adapt to this feature by treating the configuration probabilistically or by inclusion of mobility models. This paper expands upon these works by modifying the problem formulation to utilize a Monte Carlo simulation technique for the reliability analysis of a cluster-based MAWN. The cluster-based MAWN is deployed in applications with constraints or limits on the networking resources such as bandwidth and energy. This paper presents the problem's formulation, a discussion of applicable reliability metrics for the MAWN, and illustration of the method through the analysis of several example networks. Within this paper, a new and innovative use of the general MC simulation approach will be described that allows the practitioner to quickly approximate the reliability of a MAWN and understand the interactions of the characteristics that describe the MAWN; namely node reliability, node mobility, and transport (cluster) layer design. This paper is a follow on from one presented at RAMS 2007.

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Reliability analysis of cluster-based ad-hoc networks

Cook

Ramírez-Márquez

2008

Reliability Engineering & System Safety

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Capacitated Reliability for Ad-hoc Networks

Cited by 3 publications

References 8 publications

System of systems reliability for multi-state systems

System of systems reliability for multi-state systems

Reliability for cluster-based Ad-hoc Networks

Reliability analysis of cluster-based ad-hoc networks

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