Hybrid Static−Dynamic Link Weighting for Blocking Probability Reduction in Elastic Optical Networks

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A hybrid static-dynamic link weighting algorithm is proposed to reduce blocking probability in elastic optical networks by balancing link criticality and real-time load.

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The paper studies how traffic concentration on “highway” links in elastic optical networks and SDM-EON contributes to spectral fragmentation, bottlenecks, and higher request blocking rates under dynamic traffic. It proposes a Hybrid Link Weighting algorithm that assigns each link a combined score from two components: a static criticality term based on the impact of removing the link on network DBR, and a dynamic term based on current load and a Golden Metric fragmentation index, combined linearly with coefficients α and β (α + β = 1). Simulation on standard topologies finds that an appropriate coefficient choice, particularly α = 0.25 and β = 0.75, significantly reduces blocking rate versus conventional approaches, by discouraging traffic concentration on critical high-use links. The study is presented as simulation-based and includes no stated clinical, real-world validation limitation in the provided text. 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 In Elastic Optical Networks (EON), the topology structure causes some links to bear more traffic load than others and act as traffic highways. The concentration of traffic on these links, especially in dynamic traffic conditions, leads to increased spectral fragmentation, bottlenecks, and ultimately increased request blocking rates. In this paper, an algorithm called Hybrid Link Weighting(HLW) is proposed for uniform load distribution and management of high-use links in EON and SDM-EON networks. In the proposed algorithm, each link is assigned a combined weight that includes two static and dynamic components. The static component measures the criticality of the link based on the impact of its removal on the network DBR, while the dynamic component evaluates the current state of the link based on the load and fragmentation index (Golden Metric). The final weight of each link is obtained from the linear combination of these two components with coefficients α and β (assuming α + β =1). Simulation results on standard topologies show that the appropriate choice of coefficients (especially α=0.25 and β=0.75) leads to a significant reduction in the blocking rate compared to conventional methods. The proposed algorithm, by simultaneously considering the topological criticality of links and their instantaneous utilization status, is able to prevent traffic concentration on highway links and improve the overall network efficiency.
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Hybrid Static−Dynamic Link Weighting for Blocking Probability Reduction in Elastic Optical Networks | 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 Hybrid Static−Dynamic Link Weighting for Blocking Probability Reduction in Elastic Optical Networks Yaghoub Khorasani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8937774/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 4 You are reading this latest preprint version Abstract In Elastic Optical Networks (EON), the topology structure causes some links to bear more traffic load than others and act as traffic highways. The concentration of traffic on these links, especially in dynamic traffic conditions, leads to increased spectral fragmentation, bottlenecks, and ultimately increased request blocking rates. In this paper, an algorithm called Hybrid Link Weighting(HLW) is proposed for uniform load distribution and management of high-use links in EON and SDM-EON networks. In the proposed algorithm, each link is assigned a combined weight that includes two static and dynamic components. The static component measures the criticality of the link based on the impact of its removal on the network DBR, while the dynamic component evaluates the current state of the link based on the load and fragmentation index (Golden Metric). The final weight of each link is obtained from the linear combination of these two components with coefficients α and β (assuming α + β =1). Simulation results on standard topologies show that the appropriate choice of coefficients (especially α=0.25 and β=0.75) leads to a significant reduction in the blocking rate compared to conventional methods. The proposed algorithm, by simultaneously considering the topological criticality of links and their instantaneous utilization status, is able to prevent traffic concentration on highway links and improve the overall network efficiency. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 24 Feb, 2026 Editor assigned by journal 23 Feb, 2026 Submission checks completed at journal 23 Feb, 2026 First submitted to journal 22 Feb, 2026 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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