{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T15:45:25Z","timestamp":1781279125640,"version":"3.54.1"},"reference-count":0,"publisher":"River Publishers","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JICTS"],"abstract":"<jats:p>The increasing demand for real-time video services characterizes next-generation wireless networks. This demand exacerbates the conflict between bandwidth-intensive applications and resource-constrained edge infrastructure. This study proposes an ML-driven co-optimization framework that integrates lightweight compression with adaptive bitrate allocation using distributed edge intelligence. The methodology employs a depthwise separable CNN encoder enhanced by channel pruning and quantization-aware training to minimize computational requirements, achieving model sizes of \u2264500 KB and computational complexity of 0.8 GFLOPs per frame on resource-limited nodes. Concurrently, a proximal policy optimization controller is adopted to dynamically adjust bitrate based on real-time channel state information and motion complexity features. A federated alternating optimization mechanism jointly reduces latency, energy consumption, and distortion while preserving data privacy. Experimental validation on edge IoT testbeds demonstrated substantial improvements over state-of-the-art baselines, achieving 42.7% lower encoding latency, 3.2 dB higher PSNR, and 38.5% reduced energy consumption with sub-100 ms processing times. By addressing the fundamental disconnect between compression and transmission optimization, this framework provides a scalable solution for 6G-enabled massive IoT video systems. It effectively bridges theoretical machine learning advances with practical deployment constraints in ultra-reliable low-latency communication environments.<\/jats:p>","DOI":"10.13052\/jicts2245-800x.1326","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T02:16:13Z","timestamp":1764123373000},"source":"Crossref","is-referenced-by-count":1,"title":["ML-driven Co-optimization of Lightweight Compression and Adaptive Bitrate Allocation for Edge IoT Distributed Video Coding"],"prefix":"10.13052","author":[{"given":"Qu","family":"Wenyue","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wang","family":"Jinglong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhang","family":"Yiming","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Xinyan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang","family":"Zhuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"5195","published-online":{"date-parts":[[2025,11,25]]},"container-title":["Journal of ICT Standardization"],"original-title":[],"link":[{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JICTS\/article\/download\/30549\/22767","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JICTS\/article\/download\/30549\/22769","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JICTS\/article\/download\/30549\/22767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T02:16:23Z","timestamp":1764209783000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.riverpublishers.com\/index.php\/JICTS\/article\/view\/30549"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.13052\/jicts2245-800x.1326","relation":{},"ISSN":["2246-0853","2245-800X"],"issn-type":[{"value":"2246-0853","type":"electronic"},{"value":"2245-800X","type":"print"}],"subject":[],"published":{"date-parts":[[2025,11,25]]}}}