Highly reliable, low-latency communication in low-power wireless networks

Low-power wireless networks consist of spatially distributed, resource-constrained devices – also referred to as nodes – that are typically equipped with integrated or external sensors and actuators. Nodes communicate with each other using wireless transceivers, and thus, relay data – e. g., collected sensor values or commands for actuators – cooperatively through the network. This way, low-power wireless networks can support a plethora of different applications, including, e. g., monitoring the air quality in urban areas or controlling the heating, ventilation and cooling of large buildings. The use of wireless communication in such monitoring and actuating applications allows for a higher flexibility and ease of deployment – and thus, overall lower costs – compared to wired solutions. However, wireless communication is notoriously error-prone. Message losses happen often and unpredictably, making it challenging to support applications requiring both high reliability and low latency. Highly reliable, low-latency communication – along with high energy-efficiency – are, however, key requirements to support several important application scenarios and most notably the open-/closed-loop control functions found in e. g., industry and factory automation applications. Communication protocols that rely on synchronous transmissions have been shown to be able to overcome this limitation. These protocols depart from traditional single-link transmissions and do not attempt to avoid concurrent transmissions from different nodes to prevent collisions. On the contrary, they make nodes send the same message at the same time over several paths. Phenomena like constructive interference and capture then ensure that messages are received correctly with high probability. While many approaches relying on synchronous transmissions have been presented in the literature, two important aspects received only little consideration: (i) reliable operation in harsh environments and (ii) support for event-based data traffic. This thesis addresses these two open challenges and proposes novel communication protocols to overcome them

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Infective flooding in low-duty-cycle networks, properties and bounds

Flooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network

A Case for Time Slotted Channel Hopping for ICN in the IoT

Recent proposals to simplify the operation of the IoT include the use of Information Centric Networking (ICN) paradigms. While this is promising, several challenges remain. In this paper, our core contributions (a) leverage ICN communication patterns to dynamically optimize the use of TSCH (Time Slotted Channel Hopping), a wireless link layer technology increasingly popular in the IoT, and (b) make IoT-style routing adaptive to names, resources, and traffic patterns throughout the network--both without cross-layering. Through a series of experiments on the FIT IoT-LAB interconnecting typical IoT hardware, we find that our approach is fully robust against wireless interference, and almost halves the energy consumed for transmission when compared to CSMA. Most importantly, our adaptive scheduling prevents the time-slotted MAC layer from sacrificing throughput and delay

Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks

Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals of tens of milliseconds. Low-power wireless technology is preferred for its low cost, small form factor, and flexibility, especially if the devices support multi-hop communication. So far, however, feedback control over wireless multi-hop networks has only been shown for update intervals on the order of seconds. This paper presents a wireless embedded system that tames imperfections impairing control performance (e.g., jitter and message loss), and a control design that exploits the essential properties of this system to provably guarantee closed-loop stability for physical processes with linear time-invariant dynamics. Using experiments on a cyber-physical testbed with 20 wireless nodes and multiple cart-pole systems, we are the first to demonstrate and evaluate feedback control and coordination over wireless multi-hop networks for update intervals of 20 to 50 milliseconds.Comment: Accepted final version to appear in: 10th ACM/IEEE International Conference on Cyber-Physical Systems (with CPS-IoT Week 2019) (ICCPS '19), April 16--18, 2019, Montreal, QC, Canad

Opportunistic Routing and Synchronous Transmissions Meet TSCH

Low-power wireless networking commonly uses either Time-Slotted Channel Hopping (TSCH), synchronous transmissions, or opportunistic routing. All three of these different, orthogonal approaches strive for efficient and reliable communication but follow different trajectories. With this paper, we combine these concepts into one protocol: AUTOBAHN.AUTOBAHN merges TSCH scheduling with opportunistically routed, synchronous transmissions. This opens the possibility to create long-term stable schedules overcoming local interference. We prove the stability of schedules over several days in our experimental evaluation. Moreover, AUTOBAHN outperforms the autonomous scheduler Orchestra under interference in terms of reliability by 13.9 percentage points and in terms of latency by a factor of 9 under a minor duty cycle increase of 2.1 percentage points

Energy-Efficient Communication in Wireless Networks

This chapter describes the evolution of, and state of the art in, energy‐efficient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Specifically, emphasis is placed on energy efficiency as critical to ensuring the feasibility of long lifetime, low‐maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traffic patterns is discussed, in addition to their combination and evaluation as full protocol stacks