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 paper. 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.

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.

Concurrent transmissions (CTX) enable low latency, high reliability, and energy efficiency. Nevertheless, existing protocols typically exploit CTX via the Glossy system, whose fixed-length network-wide floods are entirely dedicated to disseminating a single packet.

Modern protocols for wireless sensor networks efficiently support multi-hop upward traffic from many sensors to a collection point, a key functionality enabling monitoring applications. However, the ever-evolving scenarios involving low-power wireless devices increasingly require support also for downward traffic, e.g., enabling a controller to issue actuation commands based on the monitored data. The IETF Routing Protocol for Low-power and Lossy Networks (RPL) is among the few tackling both traffic patterns. Unfortunately, its support for downward traffic is significantly unreliable and inefficient compared to its upward counterpart. We tackle this problem by extending RPL with mechanisms inspired by opposed, yet complementary, principles. At one extreme, we retain the route-based operation of RPL and devise techniques allowed by the standard but commonly neglected by popular implementations. At the other extreme, we rely on flooding as the main networking primitive. Inspired by these principles, we define three base mechanisms, integrate them in a popular RPL implementation, analyze their individual and combined performance, and elicit the resulting tradeoffs in scalability, reliability, and energy consumption. The evaluation relies on simulation, using both real-world topologies from a smart city scenario and synthetic grid ones, as well as on testbed experiments validating our findings from simulation. Results show that the combination of all three mechanisms into a novel protocol, T-RPL (i) yields high reliability, close to the one of flooding, (ii) with a low energy consumption, similar to route-based approaches, and (iii) improves remarkably the scalability of RPL with respect to downward traffic.

Time difference of arrival (TDoA) localization with ultra-wideband (UWB) radios is rapidly gaining interest. Nevertheless, TDoA requires tightly time-synchronized anchors, either via wireless synchronization in small-scale setups with all anchors in range or via expensive wired backbones, both ultimately hampering the use of TDoA in large-scale areas. In this paper we present TALLA, a novel wireless-only TDoA approach able to scale over large operational areas without sacrificing positioning accuracy. TALLA relies on a TDMA schedule enabling continuous, multi-hop operation of the anchor infrastructure. We evaluate TALLA in our 12-node UWB testbed and in much larger (>100 anchors) simulated areas, empowered by a technique that generates synthetic timing information faithfully reproducing the trends of the real one. Our real and simulated results show that TALLA achieves decimeter-level accuracy while tracking a moving target across several hops.

Concurrent transmissions can be used to enhance network reliability and scalability and to reduce energy consumption and latency. This paper studies their applicability for communication and ranging in UWB networks, where they are hitherto largely unexplored. To this end, we follow an experiment-driven approach and show that i) different pulse repetition frequencies virtually double the number of non-interfering channels, ii) concurrent transmissions with different preamble codes are unreliable, unless transmitters are tightly synchronized, and iii) under the same RF configuration, UWB radios are very likely to receive one of the packets transmitted concurrently by multiple senders, unlocking opportunities similar to those exploited in low-power narrowband radios. We argue that our findings can inform the design of novel communication and ranging protocols exploiting the unique advantages of concurrent transmissions, potentially inspiring a new wave of research on UWB radios.

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.

Data prediction in wireless sensor networks replaces the commonly used (periodic) data reporting with a model, updated (infrequently) at the sink to accurately reproduce real data trends. This technique abates up to 99% of application messages; yet, recent work has shown it achieves "only" up to a 7x lifetime improvement when executed atop a mainstream network stack (e.g., CTP + BoX-MAC), as the idle listening and topology maintenance in the latter are ill-suited to the sparse traffic induced by data prediction. This paper presents a novel network stack designed for data prediction, CRYSTAL, that exploits synchronous transmissions to quickly and reliably transmit model updates when these occur (infrequently but often concurrently), and minimizes overhead during the (frequent) periods with no updates. Based on 90-node experiments in the Indriya testbed and with 7 public datasets, we show that CRYSTAL unleashes the full potential of data prediction, achieving per-mille duty cycle with perfect reliability and very small latency.

RPL, the IPv6 Routing Protocol for Low-Power and Lossy Networks, supports both upward and downward traffic. The latter is fundamental for actuation, for queries, and for any bidirectional protocol such as TCP, yet its support is compromised by memory limitation in the nodes. In RPL storing mode, nodes store routing entries for each destination in their sub-graph, limiting the size of the network, and often leading to unreachable nodes and protocol failures. We propose here D-RPL, a mechanism that overcomes the scalability limitation by mending storing mode forwarding with multicast-based dissemination. Our modification has minimal impact on code size and memory usage. D-RPL is activated only when memory limits are reached, and affects only the portion of the traffic and the segments of the network that have exceeded memory limits. We evaluate our solution using Cooja emulation over different synthetic topologies, showing a six-fold improvement in scalability.