Voice-based Speaker Identification (SI) can be framed as the problem of Closed-Set Speaker Identification (CSSI), recognizing a speaker from a known set, or OSSI, additionally recognizing unknown speakers. Precise and accurate Open-Set Speaker Identification (SI) can enable a variety of applications, ranging from human presence detection to authentication. Existing SI solutions are typically driven by deep learning approaches, which involve computationally demanding models often running in cloud back-ends. Enabling local SI models running directly on resource-constrained embedded devices can enable new use cases while preserving speaker privacy. In this work, we fill this gap and present SPIDER, a lightweight, on-device CSSI and OSSI solution capable of running on the off-the-shelf Nordic nRF52840 and nRF5340 system-on-chip microcontrollers, which feature as little as 256 and 512 kB of RAM, respectively, and 1 MB of flash memory. SPIDER is 16x-67x smaller than currently-available SI models, and yet, the 16x smaller version achieves a comparable accuracy of 94.33 % for CSSI and 91.8% for OSSI. Our evaluation across multiple datasets confirms the viability of performing accurate SI directly on resource-constrained embedded devices using only low-cost microphones. To foster further research and development, we open source our implementation of SPIDER, empowering the community to explore new SI use cases where cloud connectivity or backhaul infrastructure is impractical or undesirable.

LoRaWAN has emerged as a leading LPWAN technology for emergency response systems due to its energy efficiency and wide coverage. However, its limited bandwidth poses significant challenges for transmitting time-sensitive images, which are crucial for first responders. A major constraint in such scenarios is that the sender - typically a resource-constrained edge device - cannot perform complex Machine Learning (ML) operations for image compression or enhancement prior to transmission. Conversely, the receiver, often a more capable gateway, has sufficient computational resources to handle ML-based image reconstruction. To address this asymmetry, we propose ZML-ChunkLoRa, an adaptive image transmission framework that segments images into optimally sized chunks based on real-time network conditions. Reduce sender-side processing while enabling high-quality ML-based reconstruction at the receiver. By offloading computation to the gateway, ZML-ChunkLoRa improves transmission efficiency without violating the strict energy and bandwidth restrictions of LoRaWAN. Experimental results demonstrate that our approach significantly improves image transfer speed and visual quality in time-critical, resource-limited first-responder environments.

Industrial Internet of Things (IIoT) networks must meet strict reliability, latency, and low energy consumption requirements. However, traditional low-power wireless protocols are ineffective in finding a sweet spot for balancing these performance metrics. Recently, network flooding protocols based on Synchronous Transmissions (STX) have been proposed for better performance in reliability-critical IIoT, where simultaneous transmissions are possible without packet collisions. STX-based protocols can offer a competitive edge over routing-based protocols, particularly dependability. However, they notably suffer from the beating effect, a physical layer phenomenon that results in sinusoidal interference across a packet and, consequently, packet loss. Thus, we introduce STX-Vote, an error correction scheme that can handle errors caused by beating effects. Importantly, we utilize transmission redundancy already inherent within STX protocols so do not incur additional on-air overhead. Through simulation, we demonstrate STX-Vote can substantially increase reliability. We subsequently implement STX-Vote on nRF52840-DK devices and perform extensive experiments. The results confirm that STX-Vote improves reliability by 25-28% for BLE 5 PHYs and 8% for IEEE 802.15.4; thus, it can complement existing error correction schemes.

Mesh networks enables quick on-demand infrastructure creation and help achieve vital last-mile connectivity. Wi-Fi integration can further enhance the potential and compatibility for the pervasive connectivity requirements in next-generation applications. Despite advancements, Wi-Fi standards still need efforts to meet long-range requirements. Accordingly, this paper proposes a customized handheld platform named WiLong for constructing long-range Wi-Fi Mesh networks in the unlicensed higher bands, 2.4 and 5 GHz. The proposed platform can offer versatile radio profiles by leveraging commercially available hardware and open-source software components, augmented with the addition of IEEE 802.11s mesh link and the B.A.T.M.A.N. advanced routing protocol. Experimental evaluations of the said platform have been conducted across various practical environments, including indoor/outdoor spaces, urban & open bay areas, multi-floor basement car parking, and dense mesh deployments. The experimental results underscore the effectiveness of the WiLong platform in improving long-range Wi-Fi performance while emphasizing the significance of multi-hop networking in demanding ground-to-ground scenarios. These findings highlight the platform’s robustness and versatility. In a selected urban route scenario, the WiLong platform achieved 80% voice and 63% video call bandwidth. Additionally, when configured with 2.4 GHz, the platform reached two floors below in a multi-floor basement car parking.

Ultra-wideband (UWB) devices operate only on a few frequency channels and commonly lack clear channel assessment capabilities: this makes it difficult to support several devices operating concurrently within a single network or to avoid coexistence issues with other UWB-based systems operating in close proximity. To address this issue, the IEEE 802.15.4 standard proposes the use of complex channels (i.e., diverse combinations of frequency channels and preamble codes) to enable multiple orthogonal transmissions. However, existing studies have shown that concurrent UWB transmissions on different complex channels are unreliable and incur high packet loss. In this paper, we investigate and shed light on the reason for this packet loss. We then present concrete methods to boost the reliability of concurrent UWB communications over different complex channels and demonstrate their effectiveness experimentally. In detail, we show that the synchronization and clock frequency offset among concurrent transmitters as well as the employed physical layer settings can be used to increase communication performance over different complex channels. Our study shows the feasibility of more than eight concurrent UWB transmissions on the same frequencies, sustaining a packet reception rate above 99% while retaining the ability to carry out centimetre-accurate ranging.

The popularity of concurrent transmissions (CT) has soared after recent studies have shown their feasibility on the four physical layers specified by BLE 5, hence providing an alternative to the use of IEEE 802.15.4 for the design of reliable and efficient low-power wireless protocols. However, to date, the extent to which physical layer properties affect the performance of CT has not yet been investigated in detail. This article fills this gap and provides an extensive study on the impact of the physical layer on CT-based solutions using IEEE 802.15.4 and BLE 5. We first highlight through simulation how the impact of errors induced by relative carrier frequency offsets on the performance of CT highly depends on the choice of the underlying physical layer. We then confirm these observations experimentally on real hardware and with varying environmental conditions through an analysis of the bit error distribution across received packets, unveiling possible techniques to effectively handle these errors. We further study the performance of CT-based data collection and dissemination protocols in the presence of RF interference on a large-scale testbed, deriving insights on how the employed physical layer affects their dependability.

This paper tackles the problem of frequent disconnections in the Quality-of-Service Optimized Link State Routing (QoS-OLSR) protocol due to mobility in mesh networks. Different routing protocols are proposed for mesh networks, such as Better Approach to Mobile Ad-hoc Networking (BATMAN), Optimized Link State Routing (OLSR), and QoS-OLSR 1.0. QoS-OLSR 1.0 improves the performance compared to the other protocols by incorporating cluster head formation and a Quality-of-Service metric used in cluster head selection. However, it still does not mitigate the impact of mobility in the formulated QoS metric. In this work, we propose and implement a cluster-based QoS-OLSR protocol for mesh networks that accounts for mobility. The work proposes a global QoS metric for nodes, calculated as the average quality of all neighbors’ links. Also, a relative QoS metric is proposed and calculated based on the direct link with the neighbor and its global QoS. Based on the relative QoS, nodes in the network select cluster heads. In case of disconnection from the selected cluster head, the nodes join an existing cluster head to recover from disconnection. Cluster heads in the proposed protocol are responsible for determining Multi-point relays (MPRs) to 2-hop and 3-hop away cluster heads to enhance connectivity. The proposed protocol is implemented as a Linux-compatible protocol for emulations using Mininet-WiFi and compared to BATMAN and QoS-OLSR 1.0. The proposed protocol outperforms the benchmark protocols in terms of throughput, Packet Delivery Ratio, and Round Trip Time with low and high mobility nodes part of the network.

Voice is a convenient and popular way to interact with our digital world. Besides translating speech to text, it is also possible to identify speakers based on their voice profile. To date, speaker identification has predominantly been limited to high-performance computational platforms owing to the intricate nature of the underlying algorithms. In this work, we demonstrate that it is possible to reduce model complexity by the required factor of ~10, such that speaker identification can be made feasible for embedded devices with limited resources. We further describe and discuss novel use cases, such as voice-based presence detection and authentication, that become feasible on these class of devices.

Jamming attacks, as a form of a denial-of-service attack, significantly degrade the performance of wireless communication systems and can lead to significant overhead in terms of re-transmissions and increased power consumption. In this work, we demonstrate the optimal jamming waveform in internet-of-things (IoT) networks. In particular, we present the analytical bit error rate (BER) of the system under attack by employing two common jamming waveforms: Gaussian noise, and digitally modulated. Then, we validate this analysis with the aid of simulations using the MATLAB WLAN toolbox. Obtained analytical and simulation results, demonstrated system performance degradation under jamming attacks. The simulation results agree with the analytical results in terms of determining the effective jamming waveform. Furthermore, the simulation results depict a 100% PER when the jamming to signal ratio (JSR) is OdB for both QPSK modulated and Gaussian noise waveforms which corroborates with the findings in the literature.

Low-power wireless IoT networks have traditionally operated over a single physical layer (PHY) - many based on the IEEE 802.15.4 standard. However, recent low-power wireless chipsets offer both the IEEE 802.15.4 and all four PHYs of the Bluetooth 5 (BT 5) standard. This introduces the intriguing possibility that IoT solutions might not necessarily be bound by the limits of a single PHY, and could actively or proactively adapt their PHY depending on RF or networking conditions (e.g., to offer a higher throughput or a longer radio range). Several recent studies have explored such use-cases. However, these studies lack comprehensive evaluation over various metrics (such as reliability, latency, and energy) with regards to scalability and the Radio Frequency (RF) environment. In this work we evaluate the performance of IEEE 802.15.4 and the four BT 5 2.4GHz PHY options for the recently completed IETF 6TiSCH low-power wireless standard. To the best of our knowledge, this is the first work to directly compare these PHYs in identical settings. Specifically, we use a recently released 6TiSCH simulator, TSCH-Sim, to compare these PHY options in networks of up to 250 nodes over different RF environments (home, industrial, and outdoor), and highlight from these results how different PHY options might be better suited to particular application use-cases.

UAVs are increasingly appearing in swarms or formations to leverage cooperative behavior, forming flying ad hoc networks. These UAV-enabled networks can meet several complex mission requirements and are seen as a potential enabler for many of the emerging use-cases in future communication networks. Such networks, however, are characterized by a highly dynamic and mobile environment with no guarantee of a central network infrastructure which can cause both connectivity and security issues. While wireless mesh networks are envisioned as a solution for such scenarios, these networks come with their own challenges and security vulnerabilities. In this paper, we analyze the key security and resilience issues resulting from the application of wireless mesh networks within UAV swarms. Specifically, we highlight the main challenges of applying current mesh technologies within the domain of UAV swarms and expose existing vulnerabilities across the communication stack. Based on this analysis, we present a security-focused architecture for UAV mesh communications. Finally, from the identification of these vulnerabilities, we discuss research opportunities posed by the unique challenges of UAV swarm connectivity.

The flexible and programmable architectural model offered by Software-Defined Networking (SDN) has re-imagined modern networks. Supported by powerful hardware and high-speed communications between devices and the controller, SDN provides a means to virtualize control functionality and enable rapid network reconfiguration in response to dynamic application requirements. However, recent efforts to apply SDN’s centralized control model to the Internet of Things (IoT) have identified significant challenges due to the constraints faced by embedded low-power devices and networks that reside at the IoT edge. In particular, reliance on external SDN controllers on the backbone network introduces a performance bottleneck (e.g., latency). To this end, we advocate a case for supporting Software-Defined IoT networks through the introduction of lightweight SDN controllers directly on the embedded hardware. We firstly explore the performance of two popular SDN implementations for IoT mesh networks, $\mu$ SDN and SDN-WISE, showing the former demonstrates considerable gains over the latter. We consequently employ $\mu$ SDN to conduct a study of embedded vs. external SDN controller performance. We highlight how the advantage of an embedded controller is reduced as the network scales, and quantify a point at which an external controller should be used for larger networks.

Recent applications in large-scale wireless mesh networks (WSN), e.g., Advanced Metering Infrastructure (AMI) scenarios, expect to support an extended number of nodes with higher throughput, which cannot be sufficiently supported by the current WSN protocols. Two prior protocols, Wi-SUN Field Area Network (Wi-SUN FAN) and IETF 6TiSCH standards, are popularly used that are respectively based on asynchronous Carrier Sense Multiple Access / Collision Avoidance (CSMA/CA) and IEEE 802.15.4 Time Scheduled Channel Hopping (TSCH). However, the former one with CSMA/CA can be prone to the Hidden Node Problem (HNP) that leads to a degradation of reliability, while the latter one with TSCH avoids HNP by using synchronously scheduling but requires massive control signalling that degrades the upper-bound of throughput. Accordingly, this paper tackles the challenge of how to improve the upper-bound of throughput without loss of reliability. To do so, we first present an in-depth evaluation of reliability and throughput between the two existing standards via system-level simulation. We then propose a self-configurable grouping (SCG) method to cluster nodes without using location information of each node. This SCG method eliminates around 99% HNP in CSMA/CA, thus greatly improves its reliability with maintaining the relatively high upper-bound of throughput. Our results show that the SCG method almost doubles the network throughput compared with both 6TiSCH and Wi-SUN FAN in heavy traffic scenarios, while providing extremely high reliability of more than 99.999%.

The popularity of concurrent transmissions (CT) has soared after recent studies have shown their feasibility on the four physical layers specified by BLE 5, hence providing an alternative to the use of IEEE 802.15.4 for the design of reliable and efficient low-power wireless protocols. However, to date, the extent to which physical layer properties affect the performance of CT has not yet been investigated in detail. This paper fills this gap and provides the first extensive study on the impact of the physical layer on CT-based solutions using IEEE 802.15.4 and BLE 5. We first highlight through simulation how the impact of errors induced by de-synchronization and beating on the performance of CT highly depends on the choice of the underlying physical layer. We then confirm these observations experimentally on real hardware through an analysis of the bit error distribution across received packets, unveiling possible techniques to effectively handle these errors. We further study the performance of CT-based flooding protocols in the presence of radio interference on a large-scale, and derive important insights on how the used physical layer affects their dependability.

RPL, the de-facto standard for low power and lossy networks, forms multi-hop routing structures between network nodes and a single root. It intrinsically minimises the number of hops across the mesh, however this can result in large distances between adjacent forwarding nodes. Consequently, during forwarding operations, the received signal strength can be close to the receiver sensitivity threshold and result in frequent packet losses due to link fluctuations. RECLAIM, our proposed approach, overcomes this challenge by transmitting routebuilding messages at a reduced power level at first while switching back to the normal transmission power level during the actual data communication phase. This results in more reliable links per hop and ensures link budget above the receiver sensitivity threshold. This however creates more hops and a longer routing path in order to reach destination. Hence, RECLAIM further applies efficient and non-conflicting 6TiSCH scheduling method to coordinate those communication events in a non conflicting manner which do not collide or cause interference to each other, resolving the issue that has traditionally prevented this approach. Our detailed simulation shows that RECLAIM drops 60 times less packets than standard RPL, and achieves 99.9999% packet delivery ratio.