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However, conventional single\u2010MCU nodes and gateway\u2010centric edge solutions are often unable to balance low\u2010power operation with computation\u2010intensive workloads. To address this problem, this paper proposes a hardware\u2013software co\u2010designed heterogeneous multi\u2010MCU edge computing platform for resource\u2010constrained IoT sensing applications. The proposed architecture organizes heterogeneous processing resources into a scheduling node, high\u2010performance MCU nodes, and low\u2010power MCU nodes, thereby enabling task execution to be matched with different computational and energy characteristics. A lightweight runtime mechanism is developed to support task dispatching, dynamic program loading, node activation, state maintenance, and result collection without relying on a heavy operating system. Furthermore, a practical node capability profiling procedure is introduced to measure execution capability, active\u2010power increment, and loading overhead under real operating conditions. Based on these profiled parameters, a latency\u2013energy scheduling model and a discrete particle swarm optimization\u2010based task allocation method are developed. Experimental results on representative monitoring workloads show that the proposed scheduler achieves a better latency\u2013energy trade\u2010off than static and extreme mapping strategies while satisfying hardware feasibility constraints.<\/jats:p>","DOI":"10.1002\/cpe.70861","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T08:15:01Z","timestamp":1784016901000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Heterogeneous Hardware\u2013Software Co\u2010Design for Multi\u2010MCU IoT Edge Computing: Architecture, Runtime Support, and Task Scheduling"],"prefix":"10.1002","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7207-7574","authenticated-orcid":false,"given":"Yuliang","family":"Lu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Public Big Data Guizhou University  Guiyang Guizhou 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