Building a green connected future: smart (Internet of) Things for smart networks

The vision of Internet of Things (IoT) promises to reshape society by creating a future where we will be surrounded by a smart environment that is constantly aware of the users and has the ability to adapt to any changes. In the IoT, a huge variety of smart devices is interconnected to form a network of distributed agents that continuously share and process information. This communication paradigm has been recognized as one of the key enablers of the rapidly emerging applications that make up the fabric of the IoT. These networks, often called wireless sensor networks (WSNs), are characterized by the low cost of their components, their pervasive connectivity, and their self-organization features, which allow them to cooperate with other IoT elements to create large-scale heterogeneous information systems. However, a number of considerable challenges is arising when considering the design of large-scale WSNs. In particular, these networks are made up by embedded devices that suffer from severe power constraints and limited resources. The advent of low-power sensor nodes coupled with intelligent software and hardware technologies has led to the era of green wireless networks. From the hardware perspective, green sensor nodes are endowed with energy scavenging capabilities to overcome energy-related limitations. They are also endowed with low-power triggering techniques, i.e., wake-up radios, to eliminate idle listening-induced communication costs. Green wireless networks are considered a fundamental vehicle for enabling all those critical IoT applications where devices, for different reasons, do not carry batteries, and that therefore only harvest energy and store it for future use. These networks are considered to have the potential of infinite lifetime since they do not depend on batteries, or on any other limited power sources. Wake-up radios, coupled with energy provisioning techniques, further assist on overcoming the physical constraints of traditional WSNs. In addition, they are particularly important in green WSNs scenarios in which it is difficult to achieve energy neutrality due to limited harvesting rates. In this PhD thesis we set to investigate how different data forwarding mechanisms can make the most of these green wireless networks-enabling technologies, namely, energy harvesting and wake-up radios. Specifically, we present a number of cross-layer routing approaches with different forwarding design choices and study their consequences on network performance. Among the most promising protocol design techniques, the past decade has shown the increasingly intensive adoption of techniques based on various forms of machine learning to increase and optimize the performance of WSNs. However, learning techniques can suffer from high computational costs as nodes drain a considerable percentage of their energy budget to run sophisticated software procedures, predict accurate information and determine optimal decision. This thesis addresses also the problem of local computational requirements of learning-based data forwarding strategies by investigating their impact on the performance of the network. Results indicate that local computation can be a major source of energy consumption; it’s impact on network performance should not be neglected

KRATOS: An Open Source Hardware-Software Platform for Rapid Research in LPWANs

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.Comment: Accepted at WiMob 201

Real-time and long lasting Internet of Things through semantic wake-up radios

The world is going towards the Internet of Things (IoT) where trillions of objects that are common in our lives will be enhanced and revolutionized by adding them computational and networking capabilities. Examples are cars, street lamps, industrial machinery, electrical appliances. The corner- stone of Internet of Things research is Wireless Sensor Networks (WSNs). These networks are made of hundreds of low-cost, low-complexity devices endowed with sensors to monitor the surrounding environment or objects. Typically these devices (also called sensors, nodes or motes) are battery-powered, therefore they can operate for a limited amount of time (i.e., days) before running out of energy. This is the main challenge that applications of Wireless Sensor Networks have to face. Since one of the major power consumers in a node is the radio transceiver, a lot of research effort has been put into finding solutions that keep the radio in a low-power state as much as possible, while not harming the communication capability. While this approach brings the network lifetime, i.e. the time before battery-operated nodes die having depleted their energy, to years or more, it introduces significant latency, as the energy reduction comes at the cost of not being able to reach nodes in deep sleep for long period of times. The most promising solution to this problem is the wake-up radio, an additional ultra-low power transceiver used for the sole purpose of triggering the activation of the high power, high bandwidth radio. Wake-up radio enabled IoT systems maintain always on their wake up radio, which has a negligible energy consumption, in this way optimizing both energy and latency performance metrics. Most of the research so far focused on the design of wake-up receivers, while a limited amount of communication protocols that take advantage of this radio has been proposed. Moreover, almost all of these protocols have been evaluated only through simulations. In this thesis we set to start filling this gap. We first evaluate the range performance of an ultra-low power wake-up receiver integrated into a state- of-the-art Wireless Sensor Network mote, the MagoNode++. Based on the results of this evaluation we deploy an outdoor testbed made of MagoNode++ motes. The testbed allows to validate in a real-world scenario our implementation of CTP-WUR, an extension of the widely used Collection Tree Protocol (CTP) for wake-up radio-enabled Wireless Sensor Networks. The comparison between CTP-WUR and CTP demonstrates that wake-up radios can effectively reduce the power consumption and obtain, at the same time, end-to-end latencies in the order of milliseconds, enabling new time critical applications. Based on the results and on the insights gained dur- ing the testbed evaluation a new version of CTP-WUR is presented that improves its performance across all the metrics taken into consideration: end-to-end packet latency, energy consumption and Packet Delivery Ratio

Pragmatic Low-Power Interoperability: ContikiMAC vs TinyOS LPL

Standardization has driven interoperability at multiple layers of the stack, such as the routing and application layers, standardization of radio duty cycling mechanisms have not yet reached the same maturity. In this work, we pitch the two de facto standard flavors of sender-initiated radio duty cycling mechanisms against each other: ContikiMAC and TinyOS LPL. Our aim is to explore pragmatic interoperability mechanisms at the radio duty cycling layer. This will lead to better understanding of interoperability problems moving forward, as radio duty cycling mechanisms get standardized. Our results show that the two flavors can be configured to operate together but that parameter configuration may severely hurt performance

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application

Energy-Efficient Wireless Circuits and Systems for Internet of Things

As the demand of ultra-low power (ULP) systems for internet of thing (IoT) applications has been increasing, large efforts on evolving a new computing class is actively ongoing. The evolution of the new computing class, however, faced challenges due to hard constraints on the RF systems. Significant efforts on reducing power of power-hungry wireless radios have been done. The ULP radios, however, are mostly not standard compliant which poses a challenge to wide spread adoption. Being compliant with the WiFi network protocol can maximize an ULP radio’s potential of utilization, however, this standard demands excessive power consumption of over 10mW, that is hardly compatible with in ULP systems even with heavy duty-cycling. Also, lots of efforts to minimize off-chip components in ULP IoT device have been done, however, still not enough for practical usage without a clean external reference, therefore, this limits scaling on cost and form-factor of the new computer class of IoT applications. This research is motivated by those challenges on the RF systems, and each work focuses on radio designs for IoT applications in various aspects. First, the research covers several endeavors for relieving energy constraints on RF systems by utilizing existing network protocols that eventually meets both low-active power, and widespread adoption. This includes novel approaches on 802.11 communication with articulate iterations on low-power RF systems. The research presents three prototypes as power-efficient WiFi wake-up receivers, which bridges the gap between industry standard radios and ULP IoT radios. The proposed WiFi wake-up receivers operate with low power consumption and remain compatible with the WiFi protocol by using back-channel communication. Back-channel communication embeds a signal into a WiFi compliant transmission changing the firmware in the access point, or more specifically just the data in the payload of the WiFi packet. With a specific sequence of data in the packet, the transmitter can output a signal that mimics a modulation that is more conducive for ULP receivers, such as OOK and FSK. In this work, low power mixer-first receivers, and the first fully integrated ultra-low voltage receiver are presented, that are compatible with WiFi through back-channel communication. Another main contribution of this work is in relieving the integration challenge of IoT devices by removing the need for external, or off-chip crystals and antennas. This enables a small form-factor on the order of mm3-scale, useful for medical research and ubiquitous sensing applications. A crystal-less small form factor fully integrated 60GHz transceiver with on-chip 12-channel frequency reference, and good peak gain dual-mode on-chip antenna is presented.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162975/1/jaeim_1.pd

Design Considerations of a Sub-50 {\mu}W Receiver Front-end for Implantable Devices in MedRadio Band

Emerging health-monitor applications, such as information transmission through multi-channel neural implants, image and video communication from inside the body etc., calls for ultra-low active power (<50${\mu}$W) high data-rate, energy-scalable, highly energy-efficient (pJ/bit) radios. Previous literature has strongly focused on low average power duty-cycled radios or low power but low-date radios. In this paper, we investigate power performance trade-off of each front-end component in a conventional radio including active matching, down-conversion and RF/IF amplification and prioritize them based on highest performance/energy metric. The analysis reveals 50${\Omega}$ active matching and RF gain is prohibitive for 50${\mu}$W power-budget. A mixer-first architecture with an N-path mixer and a self-biased inverter based baseband LNA, designed in TSMC 65nm technology show that sub 50${\mu}$W performance can be achieved up to 10Mbps (< 5pJ/b) with OOK modulation.Comment: Accepted to appear on International Conference on VLSI Design 2018 (VLSID