Probabilistic Time Slot Leasing in TDMA-Based IoT Networks for Enhanced Channel Utilization

2025-10-27

International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

AI Summary

This work addresses the inefficiency of conventional TDMA protocols in large-scale, resource-constrained IoT networks, where static slot allocation fails to adapt to dynamic node activity, resulting in low channel utilization and wasted time slots. To overcome this limitation, the paper proposes a fully distributed TDMA scheduling protocol that innovatively integrates dynamic slot reallocation with a lightweight probabilistic leasing mechanism, enabling temporary reassignment of idle slots from inactive nodes to those with high traffic demands. Operating without centralized control, the protocol ensures fairness and stability while significantly improving throughput, reducing latency, and minimizing packet loss. Extensive simulations demonstrate that the proposed scheme efficiently utilizes channel resources across diverse network scenarios, making it well-suited for energy-efficient and scalable next-generation IoT communications.

Technology Category

• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Application Domains: Internet of Things, Sensor Networks & Smart Cities
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

In large-scale resource-constrained wireless networks, such as those prevalent in the Internet of Things (IoT), efficient communication scheduling remains a critical challenge. Among the various approaches, Time Division Multiple Access (TDMA) protocols have been widely adopted for their structured and collision-free communication capabilities. Nevertheless, despite extensive research in this area, current solutions often exhibit suboptimal performance, particularly in dynamic environments where node activity levels fluctuate over time.This paper introduces a novel fully distributed TDMA-based scheduling protocol that intelligently maximizes the utilization of communication resources. The proposed approach adaptively reallocates underutilized time slots, originally assigned to temporarily inactive nodes, to those experiencing higher communication demands. This dynamic reallocation not only improves channel utilization but also reduces idle periods, thereby enhancing overall network efficiency. To further enhance performance, we incorporate a lightweight probabilistic mechanism that governs the temporal leasing of unused slots. This mechanism balances the trade-off between slot availability and transmission reliability, minimizing packet loss while preserving fairness and stability within the network.Simulations across a range of network scenarios demonstrate that our protocol significantly improves throughput, latency, and reliability in resource-constrained environments. These results highlight the protocol’s potential as a robust and scalable solution for adaptive and energy-efficient scheduling in next-generation IoT networks.

Problem

• TDMA
• IoT networks
• channel utilization
• dynamic scheduling
• resource-constrained networks

Innovation

• probabilistic time slot leasing
• adaptive TDMA scheduling
• channel utilization
• distributed IoT protocol
• dynamic resource reallocation