skip to main content


Title: A Novel Time-Interval Based Modulation for Large-Scale, Low-Power, Wide-Area-Networks
Wireless communication over long distances has become the bottleneck for battery-powered, large-scale deployments. Low-power protocols like Zigbee and Bluetooth Low Energy have limited communication range, whereas long-range communication strategies like cellular and satellite networks are power-hungry. Technologies that use narrow-band communication like LoRa, SigFox, and NB-IoT have low spectral efficiency, leading to scalability issues. The goal of this work is to develop a communication framework that is energy efficient, long-range, and scalable. We propose, design, and prototype WiChronos, a communication paradigm that encodes information in the time interval between two narrowband symbols to drastically reduce the energy consumption in a wide area network with large number of senders. We leverage the low data-rate and relaxed latency requirements of such applications to achieve the desired features identified above. We design and implement chirp spread spectrum transmitter and receiver using off-the-shelf components to send the narrowband symbols. Based on our prototype, WiChronos achieves an impressive 60% improvement in battery life compared to state-of-the-art LPWAN technologies in transmission of payloads less than 10 bytes at experimentally verified distances of over 4 km. We also show that more than 1,000 WiChronos senders can co-exist with less than 5% collision probability under low traffic conditions.  more » « less
Award ID(s):
2034415 2142978
NSF-PAR ID:
10398498
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
ACM Transactions on Sensor Networks
Volume:
18
Issue:
4
ISSN:
1550-4859
Page Range / eLocation ID:
1 to 30
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The food and drug industry is facing the need to monitor the quality and safety of their products. This has made them turn to low-cost solutions that can enable smart sensing and tracking without adding much overhead. One such popular low-power solution is backscatter-based sensing and communication system. While it offers the promise of battery-less tags, it does so at the cost of a reduced communication range. In this work, we propose PACT - a scalable communication system that leverages the knowledge asymmetry in the network to improve the communication range of the tags. Borrowing from the backscatter principles, we design custom PACT Tags that are battery-less but use an active radio to extend the communication range beyond standard passive tags. They operate using the energy harvested from the PACT Source. A wide-band Reader is used to receive multiple Tag responses concurrently and upload them to a cloud server, enabling real-time monitoring and tracking at a longer range. We identify and address the challenges in the practical design of battery-less PACT Tags using an active radio and prototype them using off-the-shelf components. We show experimentally that our Tag consumes only 23μJ energy, which is harvested from an excitation Source that is up to 24 meters away from the Tag. We show that in outdoor deployments, the responses from an estimated 520 Tags can be received by a Reader concurrently while being 400 meters away from the Tags.

     
    more » « less
  2. Applications like Connected Healthcare through physiological signal monitoring and Secure Authentication using wearable keys can benefit greatly from battery-less operation. Low power communication along with energy harvesting is critical to sustain such perpetual battery-less operation. Previous studies have used techniques such as Tribo-Electric, Piezo-Electric, RF energy harvesting for Body Area Network devices, but they are restricted to on-body node placements. Human body channel is known to be a promising alternative to wireless radio wave communication for low power operation [1-4], through Human Body Communication, as well as very recently as a medium for power transfer through body coupled power transfer [5]. However, channel length (L) dependency of the received power makes it inefficient for L>40cm. There have also been a few studies for low power communication through the human body, but none of them could provide sustainable battery-less operation. In this paper, we utilize Resonant Electro Quasi-Static Human Body Communication (Res-EQS HBC) with Maximum Resonance Power Tracking (MRPT) to enable channel length independent whole-body communication and powering (Fig.1). We design the first system to simultaneously transfer Power and Data between a HUB device and a wearable through the human body to enable battery-less operation. Measurement results show 240uW, 28uW and 5uW power transfer through the body in a MachineMachine (large devices with strong ground connection) Tabletop (small devices kept on a table, as in [5]) and Wearable-Wearable (small form factor battery operated devices) scenario respectively, independent of body channel length, while enabling communication with a power consumption of only 2.19uW. This enables >25x more power transfer with >100x more efficiency compared to [5] for Tabletop and 100cm Body distance by utilizing the benefits of EQS. The MRPT loop automatically tracks device and posture dependent resonance point changes to maximize power transfer in all cases. 
    more » « less
  3. More than 150 cellular networks worldwide have rolled out LTE-M (LTE-Machine Type Communication) and/or NB-IoT (Narrow Band Internet of Things) technologies to support massive IoT services such as smart metering and environmental monitoring. Such cellular IoT services share the existing cellular network architecture with non-IoT (e.g., smartphone) ones. When they are newly integrated into the cellular network, new security vulnerabilities may happen from imprudent integration. In this work, we explore the security vulnerabilities of the cellular IoT from both system-integrated and service-integrated aspects. We discover several vulnerabilities spanning cellular standard design defects, network operation slips, and IoT device implementation flaws. Threateningly, they allow an adversary to remotely identify IP addresses and phone numbers assigned to cellular IoT devices, interrupt their power saving services, and launch various attacks, including data/text spamming, battery draining, device hibernation against them. We validate these vulnerabilities over five major cellular IoT carriers in the U.S. and Taiwan using their certified cellular IoT devices. The attack evaluation result shows that the adversary can raise an IoT data bill by up to $226 with less than 120 MB spam traffic, increase an IoT text bill at a rate of $5 per second, and prevent an IoT device from entering/leaving power saving mode; moreover, cellular IoT devices may suffer from denial of IoT services. We finally propose, prototype, and evaluate recommended solutions. 
    more » « less
  4. Green wireless networks Wake-up radio Energy harvesting Routing Markov decision process Reinforcement learning 1. Introduction With 14.2 billions of connected things in 2019, over 41.6 billions expected by 2025, and a total spending on endpoints and services that will reach well over $1.1 trillion by the end of 2026, the Internet of Things (IoT) is poised to have a transformative impact on the way we live and on the way we work [1–3]. The vision of this ‘‘connected continuum’’ of objects and people, however, comes with a wide variety of challenges, especially for those IoT networks whose devices rely on some forms of depletable energy support. This has prompted research on hardware and software solutions aimed at decreasing the depen- dence of devices from ‘‘pre-packaged’’ energy provision (e.g., batteries), leading to devices capable of harvesting energy from the environment, and to networks – often called green wireless networks – whose lifetime is virtually infinite. Despite the promising advances of energy harvesting technologies, IoT devices are still doomed to run out of energy due to their inherent constraints on resources such as storage, processing and communica- tion, whose energy requirements often exceed what harvesting can provide. The communication circuitry of prevailing radio technology, especially, consumes relevant amount of energy even when in idle state, i.e., even when no transmissions or receptions occur. Even duty cycling, namely, operating with the radio in low energy consumption ∗ Corresponding author. E-mail address: koutsandria@di.uniroma1.it (G. Koutsandria). https://doi.org/10.1016/j.comcom.2020.05.046 (sleep) mode for pre-set amounts of time, has been shown to only mildly alleviate the problem of making IoT devices durable [4]. An effective answer to eliminate all possible forms of energy consumption that are not directly related to communication (e.g., idle listening) is provided by ultra low power radio triggering techniques, also known as wake-up radios [5,6]. Wake-up radio-based networks allow devices to remain in sleep mode by turning off their main radio when no communication is taking place. Devices continuously listen for a trigger on their wake-up radio, namely, for a wake-up sequence, to activate their main radio and participate to communication tasks. Therefore, devices wake up and turn their main radio on only when data communication is requested by a neighboring device. Further energy savings can be obtained by restricting the number of neighboring devices that wake up when triggered. This is obtained by allowing devices to wake up only when they receive specific wake-up sequences, which correspond to particular protocol requirements, including distance from the destina- tion, current energy status, residual energy, etc. This form of selective awakenings is called semantic addressing [7]. Use of low-power wake-up radio with semantic addressing has been shown to remarkably reduce the dominating energy costs of communication and idle listening of traditional radio networking [7–12]. This paper contributes to the research on enabling green wireless networks for long lasting IoT applications. Specifically, we introduce a ABSTRACT This paper presents G-WHARP, for Green Wake-up and HARvesting-based energy-Predictive forwarding, a wake-up radio-based forwarding strategy for wireless networks equipped with energy harvesting capabilities (green wireless networks). Following a learning-based approach, G-WHARP blends energy harvesting and wake-up radio technology to maximize energy efficiency and obtain superior network performance. Nodes autonomously decide on their forwarding availability based on a Markov Decision Process (MDP) that takes into account a variety of energy-related aspects, including the currently available energy and that harvestable in the foreseeable future. Solution of the MDP is provided by a computationally light heuristic based on a simple threshold policy, thus obtaining further computational energy savings. The performance of G-WHARP is evaluated via GreenCastalia simulations, where we accurately model wake-up radios, harvestable energy, and the computational power needed to solve the MDP. Key network and system parameters are varied, including the source of harvestable energy, the network density, wake-up radio data rate and data traffic. We also compare the performance of G-WHARP to that of two state-of-the-art data forwarding strategies, namely GreenRoutes and CTP-WUR. Results show that G-WHARP limits energy expenditures while achieving low end-to-end latency and high packet delivery ratio. Particularly, it consumes up to 34% and 59% less energy than CTP-WUR and GreenRoutes, respectively. 
    more » « less
  5. We present the first system that can airdrop wireless sensors from small drones and live insects. In addition to the challenges of achieving low-power consumption and long-range communication, airdropping wireless sensors is difficult because it requires the sensor to survive the impact when dropped in mid-air. Our design takes inspiration from nature: small insects like ants can fall from tall buildings and survive because of their tiny mass and size. Inspired by this, we design insect-scale wireless sensors that come fully integrated with an onboard power supply and a lightweight mechanical actuator to detach from the aerial platform. Our system introduces a first-of-its-kind 37 mg mechanical release mechanism to drop the sensor during flight, using only 450 μJ of energy as well as a wireless communication link that can transmit sensor data at 33 kbps up to 1 km. Once deployed, our 98 mg wireless sensor can run for 1.3-2.5 years when transmitting 10-50 packets per hour on a 68 mg battery. We demonstrate attachment to a small 28 mm wide drone and a moth (Manduca sexta) and show that our insect-scale sensors flutter as they fall, suffering no damage on impact onto a tile floor from heights of 22 m. 
    more » « less