Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud

Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud | 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 Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud Musarrat Zeba, Mysun Mashira, Most. Marufatul Jannat Mim, Md. Motaharul Islam, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4127989/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 Edge Computing and the Internet of Things (IoT) have recently experienced significant growth and transformed how data is processed and analyzed. Edge computing improves efficiency and reduces latency by processing data locally. However, transmitting data efficiently while conserving energy is still a major issue today, especially considering the volume and redundancy of data. The computational capacity and memory of edge gateways in the network's edge layers are limited, making it challenging to process data effectively. As a result, data transmission often becomes inefficient. To address this issue, our research introduces an energy-efficient architecture for edge gateways in the edge layer. This architecture leverages data deduplication and compression techniques for IoT data transmission from edge to cloud. The research's unique deduplication algorithm eliminates duplicate data, while the Lempel Ziv 4 compression algorithm compresses large data sets effectively. This method not only reduces energy consumption but also minimizes memory usage, facilitating quicker and more efficient data transmission. Consequently, this approach significantly alleviates energy consumption challenges and limited data processing capabilities in the edge layer. Cloud computing data compression data deduplication data transmission delays edge computing energy efficiency Internet of Things. 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. 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-4127989","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281650978,"identity":"629a21f3-53f1-4afb-aca9-d9633a08557b","order_by":0,"name":"Musarrat Zeba","email":"","orcid":"","institution":"United International University","correspondingAuthor":false,"prefix":"","firstName":"Musarrat","middleName":"","lastName":"Zeba","suffix":""},{"id":281650979,"identity":"0ac30b42-697e-4610-b654-8d9eded3b1e0","order_by":1,"name":"Mysun Mashira","email":"","orcid":"","institution":"United International University","correspondingAuthor":false,"prefix":"","firstName":"Mysun","middleName":"","lastName":"Mashira","suffix":""},{"id":281650980,"identity":"392675c1-26a5-48a1-87c5-0ae0be7a2925","order_by":2,"name":"Most. Marufatul Jannat Mim","email":"","orcid":"","institution":"United International University","correspondingAuthor":false,"prefix":"","firstName":"Most.","middleName":"Marufatul Jannat","lastName":"Mim","suffix":""},{"id":281650981,"identity":"5e027350-6deb-4ab9-b541-e3ec14504c81","order_by":3,"name":"Md. Motaharul Islam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYJACZhDBx94A5vCAScYGZrwawLJsPAdI1iKRgCSIT4tue//BzwU19xLbJB8//vCB4bCMwQHmhx8Yd1jj1GJ25jCz9IxjxYlt0mlmkjMYDvMYHGAzlmA8k45by41kBmketgSglhw2Zh6wFgYzBsa2w/i0MP/m+QfUInmG+fMfsBb2b4S0sEnztgG1SPAwSDOAtfAQsOXMYTNr3r4E4zYeoF96DNJ5JA/zFEsk4vPL8cbHt3m+Jcj2sx9+/OFHhbU93/H2jR8+4gkxNGDAAEkMCcRqGAWjYBSMglGAFQAAGGlMV/0JB0UAAAAASUVORK5CYII=","orcid":"","institution":"United International University","correspondingAuthor":true,"prefix":"","firstName":"Md.","middleName":"Motaharul","lastName":"Islam","suffix":""},{"id":281650982,"identity":"3e25da54-1a08-479b-93be-045f2e898f0b","order_by":4,"name":"Md. Rafiul Hassan","email":"","orcid":"","institution":"University of Maine at Presque Isle","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Rafiul","lastName":"Hassan","suffix":""},{"id":281650983,"identity":"8948b5aa-7340-4cb1-88c2-a420b6fc5147","order_by":5,"name":"Mohammad Mehedi Hassan","email":"","orcid":"","institution":"King Saud University","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"Mehedi","lastName":"Hassan","suffix":""}],"badges":[],"createdAt":"2024-03-19 07:01:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4127989/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4127989/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53820207,"identity":"34b32edc-0150-4530-91e0-ce75cc839ef9","added_by":"auto","created_at":"2024-03-31 23:22:41","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1965119,"visible":true,"origin":"","legend":"","description":"","filename":"EnergyEfficientArchitectureforOptimizedIoT.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4127989/v1_covered_adac873a-fb87-45a1-befb-896e5f6da028.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cloud computing, data compression, data deduplication, data transmission, delays, edge computing, energy efficiency, Internet of Things.","lastPublishedDoi":"10.21203/rs.3.rs-4127989/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4127989/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEdge Computing and the Internet of Things (IoT) have recently experienced significant growth and transformed how data is processed and analyzed. Edge computing improves efficiency and reduces latency by processing data locally. However, transmitting data efficiently while conserving energy is still a major issue today, especially considering the volume and redundancy of data. The computational capacity and memory of edge gateways in the network's edge layers are limited, making it challenging to process data effectively. As a result, data transmission often becomes inefficient. To address this issue, our research introduces an energy-efficient architecture for edge gateways in the edge layer. This architecture leverages data deduplication and compression techniques for IoT data transmission from edge to cloud. The research's unique deduplication algorithm eliminates duplicate data, while the Lempel Ziv 4 compression algorithm compresses large data sets effectively. This method not only reduces energy consumption but also minimizes memory usage, facilitating quicker and more efficient data transmission. Consequently, this approach significantly alleviates energy consumption challenges and limited data processing capabilities in the edge layer.\u003c/p\u003e","manuscriptTitle":"Energy-Efficient Architecture for Optimized IoT Data Transmission from Edge to Cloud","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 06:52:51","doi":"10.21203/rs.3.rs-4127989/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f5334e49-dcd8-4f40-a481-0ade505188ea","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-31T23:14:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-21 06:52:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4127989","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4127989","identity":"rs-4127989","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}