Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network

Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network | 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 Routing Networking Technology Based on Improved Ant Colony Algorithm in Space-Air-Ground Integrated Network Wuzhou Nie, Yong Chen, Yuhao Wang, Peizheng Wang, Meng Li, Lei Ning This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3824153/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Mar, 2024 Read the published version in EURASIP Journal on Advances in Signal Processing → Version 1 posted 4 You are reading this latest preprint version Abstract Space-Air-Ground Integrated networks comprise a multi-level heterogeneous integrated network that combines satellite-based, aerial, and terrestrial networks. With the increasing human exploration of space and growing demands for internet applications, Space-Air-Ground Integrated networks have gradually emerged as the direction for communication network development. These networks face various challenges such as extensive coverage, diverse communication node types, low-quality communication links, and simultaneous operation of multiple network protocols. However, the rapid development and widespread application of artificial intelligence and machine learning technologies in recent years have offered new perspectives and solutions for the communication architecture and routing algorithm research within Space-Air-Ground Integrated networks. In these networks, not all nodes can typically communicate directly with satellites; instead, a specific set of specialized communication nodes facilitates data communication between aerial and satellite networks due to their superior communication capabilities. Consequently, in contrast to traditional communication architectures, Space-Air-Ground Integrated networks, particularly in the terrestrial layer, often need to address challenges related to the diversity of communication node types and low-quality communication links. A well-designed routing approach becomes crucial in addressing these issues. Therefore, this paper proposes an AODV routing network protocol based on an Improved Ant Colony Algorithm (AC-AODV), specifically designed for the terrestrial layer within the Space-Air-Ground Integrated networks. By integrating information such as the type, energy, and location of communication nodes, this protocol aims to facilitate network communication. The objective is to guide information flow through nodes that are more suitable for communication, either by relaying communication or by connecting with satellites through specialized nodes. This approach alleviates the burden on ordinary nodes within the terrestrial communication network, thereby enhancing the overall network performance. In this protocol, specialized nodes hold a higher forwarding priority than regular nodes. When a source node needs to transmit data, it enters the route discovery phase, utilizing its own type, location, and energy information as heuristic data to calculate forwarding probabilities. Subsequently, it broadcasts route request (RREQ) messages to find the path. Upon receiving the RREQ message, the destination node sends an RREP message for updating information elements and selects the optimal path based on these information elements. Compared to AODV, AC-AODV shows significant improvements in performance metrics such as transmission latency, throughput, energy conversion rate, and packet loss rate. Space-Air-Ground Integration Terrestrial layer network Ant colony algorithm Routing networking protocol. Full Text Cite Share Download PDF Status: Published Journal Publication published 13 Mar, 2024 Read the published version in EURASIP Journal on Advances in Signal Processing → Version 1 posted Editorial decision: Minor revision 27 Jan, 2024 Reviewers agreed at journal 14 Jan, 2024 Reviewers invited by journal 14 Jan, 2024 First submitted to journal 03 Jan, 2024 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. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3824153","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267129727,"identity":"bd65e387-2d77-47bc-b2b9-d8532830e676","order_by":0,"name":"Wuzhou 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With the increasing human exploration of space and growing demands for internet applications, Space-Air-Ground Integrated networks have gradually emerged as the direction for communication network development. These networks face various challenges such as extensive coverage, diverse communication node types, low-quality communication links, and simultaneous operation of multiple network protocols. However, the rapid development and widespread application of artificial intelligence and machine learning technologies in recent years have offered new perspectives and solutions for the communication architecture and routing algorithm research within Space-Air-Ground Integrated networks. In these networks, not all nodes can typically communicate directly with satellites; instead, a specific set of specialized communication nodes facilitates data communication between aerial and satellite networks due to their superior communication capabilities. 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