Link Capacity Distributions and Optimal Capacities for Competent Network Performance

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This paper evaluates link capacities using stochastic distributions to determine optimal capacities for competent network performance, aiming to eliminate congestion and ensure optimal operability.

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This paper studies traffic volume, link capacity, and congestion elimination in networks using packetized traffic flows, evaluating link capacities via stochastic distributions under assumptions about network topology, routing model, and packet flow information. The authors use the resulting capacity distributions to compute optimal link capacities that produce a “rigid” traffic-flow operating state, with the goal of avoiding congestion and link or network downtime and achieving 85% uptime. A major caveat is that the analysis depends on the specified presumptions about topology, routing, and packet flow characteristics, and the work is presented as a preprint without journal peer review. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract This work addresses traffic volume, link capacity, and elimination of congestion in networks with packetized traffic flows. We adopt an analytical approach for evaluating link capacities using stochastic distributions, under the presumptions regarding i) the graphical topology of the network, ii) the routing model, and iii) the flow information of the packets being transmitted in the network. Knowledge of the capacity distributions of the links has equipped us with the technique to determine the optimal link capacities. This optimal solution provides a rigid state of the traffic flow in the network which is characterized mathematically in this work. Circumventing congestion and downtime for an individual link and the network at large and thereby ensuring optimal operability are the main objectives of this paper. In this work, we analyze a network that achieves up-time 85% using the algorithm to determine the corresponding link capacities of any network.
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Link Capacity Distributions and Optimal Capacities for Competent Network Performance | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Link Capacity Distributions and Optimal Capacities for Competent Network Performance Shivam Anil Chougule, Dripto Bakshi, Ayan Chatterjee, Amitava Mukherjee This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6350005/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This work addresses traffic volume, link capacity, and elimination of congestion in networks with packetized traffic flows. We adopt an analytical approach for evaluating link capacities using stochastic distributions, under the presumptions regarding i) the graphical topology of the network, ii) the routing model, and iii) the flow information of the packets being transmitted in the network. Knowledge of the capacity distributions of the links has equipped us with the technique to determine the optimal link capacities. This optimal solution provides a rigid state of the traffic flow in the network which is characterized mathematically in this work. Circumventing congestion and downtime for an individual link and the network at large and thereby ensuring optimal operability are the main objectives of this paper. In this work, we analyze a network that achieves up-time 85% using the algorithm to determine the corresponding link capacities of any network. Networks Traffic Packets Link Capacity Congestion Control Optimal Capacity Allocation Traffic Flow Model Packet Generation Model Packet Routing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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