The rise of IoT in the past few years has led to the massive deployment of connected devices making IoT networks denser. To optimize transmission arising from congestion in dense networks, adaptive data-rate algorithms have been implemented such as the one used in the LoRaWAN protocol. Utilization of algorithms based on reinforcement learning, especially multi-armed bandit, have been investigated, but the duty-cycle limitation decreases the performance of these algorithms in dense networks up to 15 %. This paper aims at giving a solution to resolve the issue caused by duty-cycle limitation, using the LoRa technology as a study case. An effort was done on energy consumption and the reward is modified in order to save energy according to the quality of service. Performances are evaluated thanks to our new simulator J-LoRaNeS based on the Julia language.

Managing complex distributed applications in the Cloud-Edge continuum, including deployment on diverse resources and runtime operations, presents significant challenges. Orchestrators play a key role by automating resource discovery, optimisation, deployment, and life-cycle management while ensuring system performance. This paper introduces Swarmchestrate, a decentralised, application-centric orchestration framework inspired by self-organising Swarms. Our initial findings, based on the implementation in a Cloud-Edge simulator, demonstrate Swarmchestrate's potential, offering insights into resource coordination and optimised allocation for scalable systems.

Vehicle-to-Everything (V2X) expands the capabilities of vehicles with innovative applications. Localization plays a crucial role in V2X, with measurement accuracy as a fundamental property. Demonstrating this accuracy, however, is not straightforward, especially in indoor environments. Indeed, the inability to use global navigation satellite systems (e.g., GPS) indoor requires exploring alternate technologies. In this work, we present a reliable and accurate validation methodology to demonstrate the performance of V2X localization. An Ultra-Wide Band (UWB) localization technology is at the core of our validation infrastructure. Built around this is a complete system that supports data collection from multiple localization systems, ensures time synchronization across data samples, and provides a comprehensive analysis pipeline. We demonstrate this validation system in both outdoor and indoor environments. Our approach overcomes the challenges of indoor vehicular localization and provides a reliable and accurate way to evaluate the performance of V2X localization systems.

Policy makers have implemented multiple non-pharmaceutical strategies to mitigate the COVID-19 worldwide crisis. Interventions had the aim of reducing close proximity interactions, which drive the spread of the disease. A deeper knowledge of human physical interactions has revealed necessary, especially in all settings involving children, whose education and gathering activities should be preserved. Despite their relevance, almost no data are available on close proximity contacts among children in schools or other educational settings during the pandemic. Contact data are usually gathered via Bluetooth, which nonetheless offers a low temporal and spatial resolution. Recently, ultra-wideband (UWB) radios emerged as a more accurate alternative that nonetheless exhibits a significantly higher energy consumption, limiting in-field studies. In this paper, we leverage a novel approach, embodied by the Janus system that combines these radios by exploiting their complementary benefits. The very accurate proximity data gathered in-field by Janus, once augmented with several metadata, unlocks unprecedented levels of information, enabling the development of novel multi-level risk analyses. By means of this technology, we have collected real contact data of children and educators in three summer camps during summer 2020 in the province of Trento, Italy. The wide variety of performed daily activities induced multiple individual behaviors, allowing a rich investigation of social environments from the contagion risk perspective. We consider risk based on duration and proximity of contacts and classify interactions according to different risk levels. We can then evaluate the summer camps’ organization, observe the effect of partition in small groups, or social bubbles, and identify the organized activities that mitigate the riskier behaviors. Overall, we offer an insight into the educator-child and child-child social interactions during the pandemic, thus providing a valuable tool for schools, summer camps, and policy makers to (re)structure educational activities safely.

Event-triggered control ( ETC ) holds the potential to significantly improve the efficiency of wireless networked control systems. Unfortunately, its real-world impact has hitherto been hampered by the lack of a network stack able to transfer its benefits from theory to practice specifically by supporting the latency and reliability requirements of the aperiodic communication ETC induces. This is precisely the contribution of this article. Our Wireless Control Bus ( WCB ) exploits carefully orchestrated network-wide floods of concurrent transmissions to minimize overhead during quiescent, steady-state periods, and ensures timely and reliable collection of sensor readings and dissemination of actuation commands when an ETC triggering condition is violated. Using a cyber-physical testbed emulating a water distribution system controlled over a real-world multi-hop wireless network, we show that ETC over WCB achieves the same quality of periodic control at a fraction of the energy costs, therefore unleashing and concretely demonstrating its full potential for the first time.

We explore the potential of an RFID gate for a just walk out Smart Micro Market, offering valuable data for sensor fusion with additional system technologies.

Proximity detection is at the core of several mobile and ubiquitous computing applications. These include reactive use cases, e.g., alerting individuals of hazards or interaction opportunities, and others concerned only with logging proximity data, e.g., for offline analysis and modeling. Common approaches rely on Bluetooth Low Energy (BLE) or ultra-wideband (UWB) radios. Nevertheless, these strike opposite tradeoffs between the accuracy of distance estimates quantifying proximity and the energy effciency affecting system lifetime, effectively forcing a choice between the two and ultimately constraining applicability. Janus reconciles these dimensions in a dual-radio protocol enabling accurate and energy-effcient proximity detection, where the energy-savvy BLE is exploited to discover devices and coordinate their distance measurements, acquired via the energy-hungry UWB. A model supports domain experts in con.guring Janus for their use cases with predictable performance. The latency, reliability, and accuracy of Janus are evaluated experimentally, including realistic scenarios endowed with the mm-level ground truth provided by a motion capture system. Energy measurements show that Janus achieves weeks to months of autonomous operation, depending on the use case con.guration. Finally, several large-scale campaigns exemplify its practical usefulness in real-world contexts.

Determining when two individuals are within close distance is key to contain a pandemic, e.g., to alert individuals in real-time and trace their social contacts. Common approaches rely on either Bluetooth Low Energy (BLE) or ultra-wideband (UWB) radios, that nonetheless strike opposite tradeoffs for energy efficiency vs. accuracy of distance estimates. Janus reconciles these dimensions with a dual-radio protocol enabling efficient and accurate social contact detection. Measurements show that Janus achieves weeks to months of autonomous operation, depending on the configuration. Several large-scale campaigns in real-world contexts confirm its reliability and practical usefulness in enabling insightful analysis of contact data.

Devices to support social distancing must be energy-efficient and accurate. Bluetooth Low Energy (BLE) meets the first criteria but falls short on the latter. Ultra-wideband (UWB) measures distances with <10 cm error but with relatively high consumption. Therefore, we built Janus, a dual-radio protocol that uses the strengths of each.

Child independent mobility (CIM) refers to the freedom and capability of children to move about their local neighborhoods without constant direct adult supervision. Our climb project combats an observed decline in CIM, offering a pervasive gameful platform for home–school mobility composed of three primary components: the first two using technology to support different levels of child independence and the third providing an element of continuous motivation for positive behavior change. This paper describes these three novel technologies: PedibusSmart, SafePath, and KidsGoGreen, and reports on four years of success with more than 1800 elementary age children, their teachers, and families. We further show how (i), disappearing, pervasive technology contributes to successful adoption, (ii), properly balancing trust and tracking leads to useful, noninvasive technological support, and (iii), in-classroom, gameful technology engages and motivates participation, with behavior changes persisting over time.

Technology increasingly offers parents more and more opportunities to monitor children, reshaping the way control and autonomy are negotiated within families. This paper investigates the views of parents and primary school children on mobile technology designed to support child independent mobility in the context of the local walking school buses. Based on a school-year long field study, we report findings on children's and parents' experience with proximity detection devices. The results provide insights into how the parents and children accepted and socially appropriated the technology into the walking school bus activity, shedding light on the way they understand and conceptualize a technology that collects data on children's proximity to the volunteers' smartphone. We discuss parents' needs and concerns toward monitoring technologies and the related challenges in terms of trust-control balance. These insights are elaborated to inform the future design of technology for child independent mobility.

Low-power and long-range communication technologies such as LoRa are becoming popular in IoT applications due to their ability to cover kilometers range with milliwatt of power consumption. One of the major drawbacks of LoRa is the data latency and the traffic congestion when the number of devices in the network increases. Especially, the latency arises due to the extreme duty cycling of LoRa end-nodes for reducing the overall energy consumption. To overcome this drawback, we propose a heterogeneous network architecture and an energy-efficient On-demand TDMA communication scheme improving both the device lifetime and the data latency of standard LoRa networks. We combine the capabilities of micro-watt wake-up receivers to achieve ultra-low power states and pure asynchronous communication together with the long-range connectivity of LoRa. Experimental results show a data reliability of 100 % and a round-trip latency on the order of milliseconds with end devices dissipating less than 46 mJ when active and 1.83 μW during periods of inactivity, lasting up to 3 years on a 1200 mA h Lithium battery.

Long-range (LoRa) radio technologies have recently gained momentum in the IoT landscape, allowing low-power communications over distances up to several kilometers. As a result, more and more LoRa networks are being deployed. However, commercially available LoRa devices are expensive and propriety, creating a barrier to entry and possibly slowing down developments and deployments of novel applications. Using open-source hardware and software platforms would allow more developers to test and build intelligent devices resulting in a better overall development ecosystem, lower barriers to entry, and rapid growth in the number of IoT applications. Toward this goal, this paper presents the design, implementation, and evaluation of KRATOS, a low-cost LoRa platform running ContikiOS. Both, our hardware and software designs are released as an open- source to the research community.

The performance of wake-up radios must be clearly measured and understood while designing and developing robust, dependable, and affordable systems, considering both benefits and shortcomings. State-of-the-art WURs display significant diversity in their architecture, processing capability, energy consumption, and receiver sensitivity. Standard methodologies for benchmarking are crucial for quantitatively evaluating the performance of this emerging technology, however, currently, no accepted standard for such quantitative measurement exists. Further, there is no consensus on what objective evaluation procedures and metrics should be used to understand the performance of whole systems exploiting this technology. This lack of standardization has prevented researchers from comparing results and leveraging previous work that could otherwise avoid duplication and speed up the validation process. This paper leads toward an evaluation framework, a benchmark, to enable accurate and repeatable profiling of WUR-based systems, leading to more consistent and therefore comparable evaluations for current and future systems.

Aperiodic data collection received little attention in wireless sensor networks, compared to its periodic counterpart. The recent Crystal system uses synchronous transmissions to support aperiodic traffic with near-perfect reliability, low latency, and ultra-low power consumption. However, its performance is known under mild interference---a concern, as Crystal relies heavily on the (noise-sensitive) capture effect and targets aperiodic traffic where "every packet counts". We exploit a 49-node indoor testbed where, in contrast to existing evaluations using only naturally present interference to evaluate synchronous systems, we rely on JamLab to generate noise patterns that are not only more disruptive and extensive, but also reproducible . We show that a properly configured, unmodified Crystal yields perfect reliability (unlike Glossy) in several noise scenarios, but cannot sustain extreme ones (e.g., an emulated microwave oven near the sink) that instead are handled by routing-based approaches. We extend Crystal with techniques known to mitigate interference---channel hopping and noise detection---and demonstrate that these allow Crystal to achieve performance akin to the original even under multiple sources of strong interference.

Today's "smart'" domains are driven by lightweight battery operated devices carried by people and embedded in environments. Many applications rely on continuous neighbor discovery, i.e., the ability to detect other nearby devices. Application uses for neighbor discovery are widely varying, but they all rely on a protocol in which devices exchange periodic beacons containing device identifiers. Many applications also ultimately involve assessing and adapting to context information sensed about the physical world and the device's situation in that world (e.g., its location or speed, the ambient temperature or sound, etc.). In this paper, we define Proactive Implicit Neighborhood Context Heuristics (PINCH), which leverages unused payload in periodic neighbor discovery beacons to opportunistically distribute context information in a local area. PINCH's self-organizing algorithms use limited local views of the state of a one-hop network neighborhood to determine the most useful type of context information for a device to sense and share. In this paper, we develop the algorithms, integrate an implementation of PINCHwith a smart city simulator, and benchmark the tradeoffs of self-organized local context sharing with 2.4GHz neighbor discovery beacons.

To address the challenges of the EWSN dependability competition we extended our synchronous transmission protocol, CRYSTAL, with techniques to mitigate interference -- channel hopping and noise detection -- and with the capability to deliver aperiodic events to multiple actuators.

Pervasive sensing and actuation applications are increasingly being built using distributed devices connected with low-power wireless links. Most of these applications exploit anarchic protocols in which devices independently attempt to seize communication resources, supporting only best-effort applications as the communication they rely on cannot be guaranteed. For strict quality of service requirements, a few, non-anarchic, disciplined approaches exist in which nodes coordinate and resources are guaranteed to individual devices. Unfortunately, these solutions come at a considerable cost to form and conform to rigid communication schedules while considering the inherent volatility of the wireless environment. This work proposes REINS-MAC, a fully distributed solution that adapts to changes in the wireless environment and forms a flexible communication schedule able to support quality of service requirements. Inspired by pulse-coupled oscillators, the mathematical formulation of firefly flash synchronization, our approach forms and reserves communication slots of variable size in an online and adaptive manner. REINS-MAC tailors communication resources to network conditions that vary in time and space as well as to the explicit communication needs of devices by enabling distributed, dynamic changes to established schedules. Ultimately, REINS-MAC allows higher level abstractions to rein in the protocol anarchy, laying the foundation for reliable wireless applications.