{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T21:28:57Z","timestamp":1780349337141,"version":"3.54.1"},"reference-count":33,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T00:00:00Z","timestamp":1683849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Nebraska\u2013Lincoln"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device\u2019s energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network\u2019s performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In wireless communications, the channel plays a major role in determining energy requirements. Therefore, a mixed-integer nonlinear programming problem is formulated to jointly optimize power allocation, sub-channel allocation, user selection, and the activated remote radio units (RRUs) in a combinatorial approach according to the channel conditions. Although it is an NP-hard problem, the optimization problem is solved through fractional programming properties, converting it into an equivalent tractable and parametric form. The resulting problem is then solved optimally by using the Lagrangian decomposition method and an improved Kuhn\u2013Munkres algorithm. The results show that the proposed technique significantly improves the energy efficiency of IoT systems as compared to the state-of-the-art work.<\/jats:p>","DOI":"10.3390\/s23104711","type":"journal-article","created":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T09:56:18Z","timestamp":1683885378000},"page":"4711","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Dynamic Resource Optimization for Energy-Efficient 6G-IoT Ecosystems"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6070-9316","authenticated-orcid":false,"given":"James Adu","family":"Ansere","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Sunyani Technical University, Sunyani P.O. Box 206, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3893-4330","authenticated-orcid":false,"given":"Mohsin","family":"Kamal","sequence":"additional","affiliation":[{"name":"Electrical Engineering Department, National University of Computer and Emerging Sciences, Lahore 54770, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8172-354X","authenticated-orcid":false,"given":"Izaz Ahmad","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Bacha Khan University, Charsadda 24420, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4629-7589","authenticated-orcid":false,"given":"Muhammad Naveed","family":"Aman","sequence":"additional","affiliation":[{"name":"School of Computing, University of Nebraska-Lincoln, Lincoln, NE 68588, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Gyamfi, E., Ansere, J.A., and Xu, L. 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