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Abstract

In wireless environments, transmission and 1 reception costs dominate system power consumption, motivating 2 research effort on new technologies capable of reducing the 3 footprint of the radio, paving the way for the Internet of 4 Things. The most important challenge is to reduce power 5 consumption when receivers are idle, the so called idle-listening 6 cost. One approach proposes switching off the main receiver, 7 then introduces new wake-up circuitry capable of detecting 8 an incoming transmission, optionally discriminating the packet 9 destination using addressing, then switching on the main radio 10 only when required. This wake-up receiver technology represents 11 the ultimate frontier in low power radio communication. In 12 this paper, we present a comprehensive literature review of 13 the research progress in wake-up radio (WuR) hardware and 14 relevant networking software. First, we present an overview of 15 the WuR system architecture, including challenges to hardware 16 design and a comparison of solutions presented throughout the 17 last decade. Next, we present various medium access control and 18 routing protocols as well as diverse ways to exploit WuRs, both 19 as an extension of pre-existing systems and as a new concept to 20 manage low-power networking.

Abstract-Data prediction is proposed in wireless sensor networks (WSNs) to extend the system lifetime by enabling the sink to determine the data sampled, within some accuracy bounds, with only minimal communication from source nodes. Several theoretical studies clearly demonstrate the tremendous potential of this approach, able to suppress the vast majority of data reports at the source nodes. Nevertheless, the techniques employed are relatively complex, and their feasibility on resource-scarce WSN devices is often not ascertained. More generally, the literature lacks reports from real-world deployments, quantifying the overall system-wide lifetime improvements determined by the interplay of data prediction with the underlying network. These two aspects, feasibility and system-wide gains, are key in determining the practical usefulness of data prediction in real-world WSN applications. In this paper, we describe Derivative-Based Prediction (DBP), a novel data prediction technique much simpler than those found in the literature. Evaluation with real data sets from diverse WSN deployments shows that DBP often performs better than the competition, with data suppression rates up to 99% and good prediction accuracy. However, experiments with a real WSN in a road tunnel show that, when the network stack is taken into consideration, DBP only triples lifetime-a remarkable result per se, but a far cry from the data suppression rates above. To fully achieve the energy savings enabled by data prediction, the data and network layers must be jointly optimized. In our testbed experiments, a simple tuning of the MAC and routing stack, taking into account the operation of DBP, yields a remarkable seven-fold lifetime improvement w.r.t. the mainstream periodic reporting.

Wireless sensor networks (WSNs) are envisioned for a number of application scenarios. Never- theless, the few in-the-field experiences typically focus on the features of a specific system, and rarely report about the characteristics of the target environment, especially with respect to the behavior and performance of low-power wireless communication. The TRITon project, funded by our local administration, aims to improve safety and reduce maintenance costs of road tunnels, using a WSN-based control infrastructure. The access to real tunnels within TRITon gives us the opportunity to experimentally assess the peculiarities of this environment, hitherto not in- vestigated in the WSN field. We report about three deployments: (i) an operational road tunnel, enabling us to assess the impact of vehicular traffic; (ii) a nonoperational tunnel, providing insights into analogous scenarios (e.g., underground mines) without vehicles; (iii) a vineyard, serving as a baseline representative of the existing literature. Our setup, replicated in each deployment, uses mainstream WSN hardware, and popular MAC and routing protocols. We analyze and compare the deployments with respect to reliability, stability, and asymmetry of links, the accuracy of link quality estimators, and the impact of these aspects on MAC and routing layers. Our analysis shows that a number of criteria commonly used in the design of WSN protocols do not hold in tunnels. Therefore, our results are useful for designing networking solutions operating efficiently in similar environments

Energy efficiency is crucial in the design of battery-powered end devices, such as smart sensors for the Internet of Things applications. Wireless communication between these distributed smart devices consumes significant energy, and even more when data need to reach several kilometers in distance. Low-power and long-range communication technologies such as LoRaWAN are becoming popular in IoT applications. However, LoRaWAN has drawbacks in terms of (i) data latency; (ii) limited control over the end devices by the gateway; and (iii) high rate of packet collisions in a dense network. To overcome these drawbacks, we present an energy-efficient network architecture and a high-efficiency on-demand time-division multiple access (TDMA) communication protocol for IoT improving both the energy efficiency and the latency of standard LoRa networks. We combine the capabilities of short-range wake-up radios to achieve ultra-low power states and asynchronous communication together with the long-range connectivity of LoRa. The proposed approach still works with the standard LoRa protocol, but improves performance with an on-demand TDMA. Thanks to the proposed network and protocol, we achieve a packet delivery ratio of 100% by eliminating the possibility of packet collisions. The network also achieves a round-trip latency on the order of milliseconds with sensing devices dissipating less than 46 mJ when active and 1.83 μW during periods of inactivity and can last up to three years on a 1200-mAh lithium polymer battery.

Distributed content-based publish-subscribe middleware provides the decoupling, flexibility, expressiveness, and scalability required by highly dynamic distributed applications, e.g., mobile ones. Nevertheless, the available systems exploiting a distributed event dispatcher are unable to rearrange dynamically their behavior to adapt to changes in the topology of the dispatching infrastructure.In this work, we first define a strawman solution based on ideas proposed (but never precisely characterized) in existing work. We then analyze this solution and achieve a deeper understanding of how the event dispatching information is reconfigured. Based on this analysis, we modify the strawman approach to reduce its overhead. Simulations show that the reduction is significant (up to 50%), and yet the algorithm is resilient to concurrent reconfigurations.

Mobility challenges old assumptions and demands novel software engineering solutions including new models, algorithms, and middleware. Coordination mechanisms must be developed to bridge effectively a clean abstract model of mobility and the technical opportunities and complexities of wireless technology, device miniaturization, and code mobility. Logical mobility opens up a broad range of new design opportunities, physical mobility forces consideration of an entirely new set of technical constraints, and the integration of the two is an important juncture in the evolution of software engineering as a field.