{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cross-layer-framework-and-optimization-for","title":"Cross-layer framework and optimization for efficient use of the energy budget of IoT Nodes","arxiv_id":"1806.08624","date":"2020-03-20","proceeding":null,"authors":[],"abstract":"Both physical and MAC-layer need to be jointly optimized to maximize the\nautonomy of IoT devices. Therefore, a cross-layer design is imperative to\neffectively realize Low Power Wide Area networks (LPWANs). In the present\npaper, a cross-layer assessment framework including power modeling is proposed.\nThrough this simulation framework, the energy consumption of IoT devices,\ncurrently deployed in LoRaWAN networks, is evaluated. We demonstrate that a\ncross-layer approach significantly improves energy efficiency and overall\nthroughput. Two major contributions are made. First, an open-source LPWAN\nassessment framework has been conceived. It allows testing and evaluating\nhypotheses and schemes. Secondly, as a representative case, the LoRaWAN\nprotocol is assessed. The findings indicate how a cross-layer approach can\noptimize LPWANs in terms of energy efficiency and throughput. For instance, it\nis shown that the use of larger payloads can reduce up to three times the\nenergy consumption on quasi-static channels yet may bring an energy penalty\nunder adverse dynamic conditions.","url_abs":"http://arxiv.org/abs/1806.08624v2","url_pdf":"http://arxiv.org/pdf/1806.08624v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"cross-layer-framework-and-optimization-for","repo_url":"https://github.com/GillesC/LoRaEnergySim","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}