A MILP‐Based Optimization Framework for Joint Transmission Scheduling and Dynamic Channel Allocation in QoS‐Constrained IoT Networks

ABSTRACT The growing scale of Internet of Things (IoT) networks poses critical challenges for delay‐sensitive communication under strict Quality of Service (QoS) requirements. This paper presents MOCHA, a Mixed‐Integer Linear Programming (MILP)‐based optimization framework that jointly addresses transmission scheduling and dynamic channel allocation. A tailored Branch‐and‐Bound algorithm is developed to efficiently explore feasible solutions while ensuring capacity, exclusivity, and deadline constraints. Simulation results demonstrate that MOCHA achieves up to 30% lower transmission delay than leading approaches (MPSORP, MO‐DRL, PQTBA). These results highlight the practicality of exact optimization in enabling reliable and delay‐aware IoT services such as smart healthcare and autonomous systems.