Careful parametrization of networking protocols is crucial to maximize the performance of low-power wireless systems and ensure that stringent application requirements can be met. This is a non-trivial task involving thorough characterization on testbeds and requiring expert knowledge. Unfortunately, the community still lacks a tool to facilitate parameter exploration while minimizing the necessary experimentation time on testbeds. Such a tool would be invaluable, as exhaustive parameter searches can be time-prohibitive or unfeasible given limited testbed availability, whereas non-exhaustive unguided searches rarely deliver satisfactory results. In this article, we present APEX, a framework enabling an automated and informed parameter exploration for low-power wireless protocols and allowing convergence to the best parameter set within a limited number of testbed trials. We design APEX using Gaussian processes to effectively handle noisy experimental data and estimate the optimality of a parameter combination. After developing a prototype of APEX, we demonstrate its effectiveness by parametrizing two IEEE 802.15.4 protocols across a wide range of application requirements. Our results show that APEX can return the best parameter set with up to 10.6×, 4.5×, 4.3×, and 3.25× less testbed trials than traditional solutions based on exhaustive search, greedy approaches, support vector regression and reinforcement learning, respectively.

The scalability of the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is increasingly attracting the interest of both academia and industry. In light of this, we present experiences from a pilot experimental study conducted over several weeks on the protocol’s state-of-the-art implementation, RPL-Lite, in a large multi-hop IEEE 802.15.4 network of up to 700 nodes dispersed over 3390 m2. Our results show that RPL is capable of reliable and self-managed data collection even in such large-scale deployments, but its performance may drop significantly because of transmission power settings, border router locations, and insufficient load balancing, notably due to a phenomenon that, to the best of our knowledge, has not been reported in literature. We believe that our observations can be of value to designers and administrators of low-power wireless networks as well as to the community developing RPL.

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.

The selection of the spreading factor (SF) has important implications on the radio on-time, energy consumption, achievable data rate, and communication range of LoRa devices. In practical applications, LoRa packets can only be exchanged when the SF between transmitter and receiver matches. To ensure that this is the case, current approaches either statically hard-code the SF used to communicate between two devices, or negotiate which SF to use through handshaking mechanisms. Unfortunately, statically assigning the SF may lead to sub-optimal performance, and changing the assignment at runtime through a negotiation process incurs a significant overhead in terms of both latency and energy consumption. In this paper, we propose RSSF, a scheme that allows an off-the-shelf LoRa device to receive and decode a packet without prior knowledge of the SF used by the transmitter. RSSF leverages the observation that the SF with which a packet was sent can be inferred by analyzing the received signal strength (RSS) samples captured while receiving the first preamble symbols, and by characterizing their periodicity. In real-world systems, however, the waveform obtained by sampling the RSS during the reception of the first preamble symbols contains several spikes due to the receiver's DC offset cancellation, which makes it difficult to accurately identify periods. We show that this problem can be solved by letting an off-the-shelf LoRa receiver sample the RSS on a frequency that is shifted by half of the bandwidth from the original frequency at which the packet was transmitted. We then implement a lightweight algorithm that determines the SF by partitioning the RSS samples into sliding windows of different size (corresponding to each possible SF) and by measuring the zero-crossing intervals for each window size. We evaluate RSSF's performance experimentally using both software-defined radios and off-the-shelf LoRa nodes, showing that RSSF can accurately determine the SF within the first 5 preamble symbols.

The introduction of the Wi-Fi 6E standard operating in the 6 GHz frequency band is a serious threat for IoT systems based on ultra-wideband technology, as they share portions of the same spectrum. Wi-Fi 6E devices can in fact support channel bandwidths up to 160 MHz and operate at a much higher transmission power compared to ultra-wideband devices, which may lead to severe coexitence issues and degraded performance. However, whether and to which extent the performance of ultra-wide band systems worsens due to Wi-Fi 6E interference has not been investigated in detail yet. In this paper, we fill this gap and study how Wi-Fi 6E traffic affects ultra-wideband performance. Our experiments on a large-scale testbed demonstrate that Wi-Fi 6E transmissions may largely disrupt ultra-wideband communications and decrease the accuracy as well as the precision of ranging measurements, with significant consequences on the efficiency of localization systems. We investigate in detail the root causes for the degraded performance and derive empirical observations that can be used to design countermeasures mitigating the impact of Wi-Fi 6E interference. These include, among others, an optimal selection of physical layer settings, as well as the use of a tight synchronization to prevent a false detection of Wi-Fi 6E traffic as ultra-wide band frames and an overshooting of the radio's automatic gain control. We further devise a technique to detect the presence of Wi-Fi 6E traffic and postpone ultra-wideband transmissions accordingly. Our experiments demonstrate that these countermeasures effectively mitigate the impact of Wi-Fi 6E interference on the performance of ultra-wide band systems.

Despite the growing interest in cross-technology communication, its application to real-world systems is still limited, as existing schemes are mostly unidirectional and technology-specific. The lack of generic solutions as well as the complexity of their integration reduces the applicability in a broader scope. In this paper, we propose a solution to augment Wi-Fi, BLE, and ZigBee devices with the ability to transmit and receive cross-technology broadcast frames alongside their existing functionality. After experimentally evaluating the performance of our solution on a variety of hardware platforms, we leverage it to build a gateway-free smart home, where a smartphone can simultaneously control heterogeneous smart objects. The smart objects, which include an off-the-shelf ZigBee light bulb and a BLE-enabled door lock from different vendors, perform cross-technology communication while retaining their original functionality and can maintain duty-cycled operations.

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.

Updating the software running on constrained IoT devices such as low-power sensors and actuators in a secure and efficient way is an open problem. The limited computational, memory, and storage capabilities of these devices, together with their small energy budget, indeed, restrict the number of features that can be embedded into an update system and make it also difficult to build a generic and compact solution. As a result, existing update systems for constrained IoT devices are often not portable, do not perform a proper verification of the downloaded firmware, or focus only on a single phase of the update process, which exposes them to security threats and calls for new solutions. In this paper we present UpKit, a portable and lightweight software update framework for constrained IoT devices encompassing all phases of the update process: from the generation and signature of a new firmware, to the transmission of the latter to an IoT device, its verification and installation. UpKit employs a novel update architecture that is agnostic to how new firmware images are distributed and that introduces a double-signature process to guarantee the freshness of a new firmware. This, together with an additional verification step, allows also to reject invalid software at an early stage and to prevent an unnecessary reboot of the device. We keep UpKit's design modular and provide an open-source implementation for several operating systems, hardware platforms, as well as cryptographic libraries. We further include support for differential updates and flexible memory slots, which allows to significantly increase the efficiency of the update process. An experimental evaluation shows that UpKit can be used to efficiently update highly-constrained IoT devices, and that it has a comparable memory footprint to state-of-the-art solutions, despite the introduction of several features.