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 AES_256_GCM and ChaCha20_Poly1305 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) ChaCha20_Poly1305 outperforms AES_256_GCM, 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.

IoT has evolved from an experimental to a backbone technology able to connect myriads of people, things, and services for a large range of businesses. At the same time, the emergence of SDN can ideally handle IoT challenges for elasticity, heterogeneity, and mobility, offering an architecture that abstracts decision making away from the data plane and providing a programmable network facility. Along these lines, we propose MINOS, a multi-protocol SDN platform for IoT that implements service awareness utilizing appropriate SDN abstractions and interfaces for logically centralized network control of diverse and resource-constrained IoT environments, two network protocols that are deployable and configurable on demand, and a GUI that provides a bespoke dashboard and a real-time visualization tool. Due to its components, MINOS enables experimentation with novel network control features and protocols that realize optimized routing over heterogeneous IoT nodes, application of real-time strategies as a response to dynamic network conditions, support of individual protocol configurations per node, and flexibility to accommodate new protocols and control algorithms. Our results demonstrate MINOS as an enabling platform for two protocols, CORAL-SDN and Adaptable-RPL, which, in comparison with the state-of-the-art IoT routing protocol RPL, improve the packet delivery ratio with relatively small control overhead.

Energy-efficient Passive Optical Networks (PONs) have gained significant interest since they are estimated to be the largest energy consumers among the wired access networks for the next ten years. In Ethernet PONs (EPONs), the equipment placed at the customer premises, i.e., the Optical Network Units (ONUs), has been shown to be responsible for almost 65% of the total EPON power consumption. Sleep mechanisms, implemented at ONUs’ side, can contribute to the EPONs’ energy-efficiency. However, the trade-off between energy saving and Quality of Service (QoS) requirements should be carefully tuned, especially when the downstream transmission is considered, to achieve the desirable results. In this paper, we propose a general framework that exploits formal methods as an approach for EPONs’ energy-efficiency. The idea is to build a holistic model representing both the state machine of the ONU in its details as well as the ONU’s communication with the Optical Line Terminal (OLT) under EPONs’ specifications. Verification results reveal that, guided by the QoS constraints and considering the transitions’ cost, an “aggressive” policy defining long sleep periods of the 100 ms order can be up to 24,9% beneficial for energy-efficiency compared to a “conservative” policy with sleep periods of the 10 ms order.