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September 10, 2025Applied Sciences20 citationsOpen Access

Empirical Evaluation of TLS-Enhanced MQTT on IoT Devices for V2X Use Cases

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NGNikolaos Orestis GavriilidisSHSpyros T. HalkidisSPSophia Petridou

Key Points

  • TLS 1.3-enhanced MQTT is feasible on Raspberry Pi 4B, though it introduces non-negligible resource overheads.
  • Batching messages into fewer, larger packets reduces transmission cost and latency, improving efficiency.
  • ChaCha20_Poly1305 outperforms AES_256_GCM in wireless scenarios, making it ideal for resource-sensitive V2X applications.
  • This evaluation quantifies resource consumption including CPU utilization, memory footprint, and energy usage.

Abstract

The rapid growth of Internet of Things (IoT) deployment has led to an unprecedented volume of interconnected, resource-constrained devices. Securing their communication is essential, especially in vehicular environments, where sensitive data exchange requires robust authentication, integrity, and confidentiality guarantees. In this paper, we present an empirical evaluation of TLS (Transport Layer Security) -enhanced MQTT (Message Queuing Telemetry Transport) on low-cost, quad-core Cortex-A72 ARMv8 boards, specifically the Raspberry Pi 4B, commonly used as prototyping platforms for On-Board Units (OBUs) and Road-Side Units (RSUs). Three MQTT entities, namely, the broker, the publisher, and the subscriber, are deployed, utilizing Elliptic Curve Cryptography (ECC) for key exchange and authentication and employing the AES₂56GCM and ChaCha20Poly1305 ciphers for confidentiality via appropriately selected libraries. We quantify resource consumption in terms of CPU utilization, execution time, energy usage, memory footprint, and goodput across TLS phases, cipher suites, message packaging strategies, and both Ethernet and WiFi interfaces. Our results show that (i) TLS 1. 3-enhanced MQTT is feasible on Raspberry Pi 4B devices, though it introduces non-negligible resource overheads; (ii) batching messages into fewer, larger packets reduces transmission cost and latency; and (iii) ChaCha20Poly1305 outperforms AES₂56GCM, particularly in wireless scenarios, making it the preferred choice for resource- and latency-sensitive V2X applications. These findings provide actionable recommendations for deploying secure MQTT communication on an IoT platform.

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Cite This Study

Gavriilidis et al. (2025) studied this question.

synapsesocial.com/papers/68c1ad6a54b1d3bfb60e5ce0https://doi.org/10.3390/app15158398
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