A QoE/QoS based multilevel index for an efficient service selection in the IoT

A QoE/QoS based multilevel index for an efficient service selection in the IoT | 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 A QoE/QoS based multilevel index for an efficient service selection in the IoT Meriem Achir, abdelkrim abdelli This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6294816/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract The Internet of Things (IoT) has revolutionized various industries, including logistics, healthcare, and agriculture. The interconnectivity of these devices has expanded beyond digital areas, allowing for unprecedented levels of control and interaction with the physical world. To ensure the best user experience, efficient solutions for discovering and selecting IoT services are needed. Within this context, we propose a novel index structure called the Multi-Level Quality of Experience Index (MLQEI) that aims to enhance the speed and efficiency of discovery and selection processes for services by considering user requests expressed on multiple QoS parameters with different quantified importance. We introduce a similarity function to group requests with mutual QoS profiles into user classes that define the leaves of the MLQEI structure. We consider the TOPSIS method to compute service lists within these profiles based on the QoE of each class, with dynamic updates in service lists using pertinence thresholds. Furthermore, MLQEI can serve as a tool to monitor QoE and QoS by collecting and analyzing user experiences.Our solution's implementation and simulation have demonstrated its efficiency over the iterative approach (TOPSIS per request), achieving a reduction in response time by over 30 times in the worst-case scenario, while keeping the relevance of the results above 90%. Service selection TOPSIS MCDM Multilevel Index QoS QoE retrieval time Soft similarity Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Sep, 2025 Reviews received at journal 27 Jun, 2025 Reviews received at journal 19 Jun, 2025 Reviewers agreed at journal 19 Jun, 2025 Reviewers agreed at journal 17 Jun, 2025 Reviewers agreed at journal 15 Jun, 2025 Reviews received at journal 07 May, 2025 Reviewers agreed at journal 26 Apr, 2025 Reviewers invited by journal 24 Apr, 2025 Editor assigned by journal 26 Mar, 2025 Submission checks completed at journal 25 Mar, 2025 First submitted to journal 24 Mar, 2025 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-6294816","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448469143,"identity":"035c70da-e74e-478a-a810-2367cc0035e3","order_by":0,"name":"Meriem Achir","email":"","orcid":"","institution":"LSI laboratory, USTHB","correspondingAuthor":false,"prefix":"","firstName":"Meriem","middleName":"","lastName":"Achir","suffix":""},{"id":448469144,"identity":"b60f72c0-381a-4a0f-bbfe-9bf3e3d76f9c","order_by":1,"name":"abdelkrim abdelli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYHACNgYeBgsZNvYGBoYEBmaitUjwsPEcIFULg0QCiEOEFv4G5mcP3lRI8PBJPj784QGDtT1BLRIH2MwN55wBOkw6LQ1oUToR1hxgMJPmbQNpyTED+uUwG0Ed8gfYv0nz/gNqkTz/+QNQCw9BLQYHeIC2NAC1QELgsARBLYYHeMoN5xwDBXKamUSCQboBQS1yB9i3PXhTYyMn33748ccfFUSEGIP8AxR3EtYwCkbBKBgFo4AIAAAt0S4L96z40AAAAABJRU5ErkJggg==","orcid":"","institution":"ESI, high school of computer science","correspondingAuthor":true,"prefix":"","firstName":"abdelkrim","middleName":"","lastName":"abdelli","suffix":""}],"badges":[],"createdAt":"2025-03-24 11:23:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6294816/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6294816/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81497801,"identity":"84cf09b6-064a-4dd8-8229-79a4fc4e35a1","added_by":"auto","created_at":"2025-04-28 02:58:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1251855,"visible":true,"origin":"","legend":"","description":"","filename":"IotselectionbasedIndex.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6294816/v1_covered_13977159-88dc-407c-ab67-8adffbbbdd58.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A QoE/QoS based multilevel index for an efficient service selection in the IoT","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cluster-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Cluster Computing](https://www.springer.com/journal/10586)","snPcode":"10586","submissionUrl":"https://submission.nature.com/new-submission/10586/3","title":"Cluster Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Service selection, TOPSIS, MCDM, Multilevel Index, QoS, QoE, retrieval time, Soft similarity","lastPublishedDoi":"10.21203/rs.3.rs-6294816/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6294816/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The Internet of Things (IoT) has revolutionized various industries, including logistics, healthcare, and agriculture. The interconnectivity of these devices has expanded beyond digital areas, allowing for unprecedented levels of control and interaction with the physical world. To ensure the best user experience, efficient solutions for discovering and selecting IoT services are needed. Within this context, we propose a novel index structure called the Multi-Level Quality of Experience Index (MLQEI) that aims to enhance the speed and efficiency of discovery and selection processes for services by considering user requests expressed on multiple QoS parameters with different quantified importance. We introduce a similarity function to group requests with mutual QoS profiles into user classes that define the leaves of the MLQEI structure. We consider the TOPSIS method to compute service lists within these profiles based on the QoE of each class, with dynamic updates in service lists using pertinence thresholds. Furthermore, MLQEI can serve as a tool to monitor QoE and QoS by collecting and analyzing user experiences.Our solution's implementation and simulation have demonstrated its efficiency over the iterative approach (TOPSIS per request), achieving a reduction in response time by over 30 times in the worst-case scenario, while keeping the relevance of the results above 90\\%. ","manuscriptTitle":"A QoE/QoS based multilevel index for an efficient service selection in the IoT","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 02:50:02","doi":"10.21203/rs.3.rs-6294816/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-16T17:37:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-27T17:57:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-19T09:49:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204100092167068820893483904882588498048","date":"2025-06-19T09:14:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"129173264654422686423851008557094838219","date":"2025-06-17T07:09:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143335070275346480872517231567439586884","date":"2025-06-15T16:35:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-07T09:08:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268996310948288575834325805867123082887","date":"2025-04-26T21:39:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-24T07:08:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-26T09:44:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-26T01:27:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cluster Computing","date":"2025-03-24T11:21:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cluster-computing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Cluster Computing](https://www.springer.com/journal/10586)","snPcode":"10586","submissionUrl":"https://submission.nature.com/new-submission/10586/3","title":"Cluster Computing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"938ecbca-c0a1-4ed9-bf5f-2701dcf2af6c","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-20T14:11:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 02:50:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6294816","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6294816","identity":"rs-6294816","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}