Bradford Campbell

The Internet of Things Has a Gateway Problem

The vision of an Internet of Things (IoT) has captured the imagination of the world and raised billions of dollars, all before we stopped to deeply consider how all these Things should connect to the Internet. The current state-of-the-art requires application-layer gateways both in software and hardware that provide application-specific connectivity to IoT devices. In much the same way that it would be difficult to imagine requiring a new web browser for each website, it is hard to imagine our current approach to IoT connectivity scaling to support the IoT vision. The IoT gateway problem exists in part because todays gateways conflate network connectivity, in-network processing, and user interface functions. We believe that disentangling these functions would improve the connectivity potential for IoT devices. To realize the broader vision, we propose an architecture that leverages the increasingly ubiquitous presence of Bluetooth Low Energy radios to connect IoT peripherals to the Internet. In much the same way that WiFi access points revolutionized laptop utility, we envision that a worldwide deployment of IoT gateways could revolutionize application-agnostic connectivity, thus breaking free from the stove-piped architectures now taking hold. In this paper, we present our proposed architecture, show example applications enabled by it, and explore research challenges in its implementation and deployment.

Grafting energy-harvesting leaves onto the sensornet tree

We study the problem of augmenting battery-powered sensornet trees with energy-harvesting leaf nodes. Our results show that leaf nodes that are smaller in size than todays typical battery-powered sensors can harvest enough energy from ambient sources to acquire and transmit sensor readings every minute, even under poor lighting conditions. However, achieving this functionality, especially as leaf nodes scale in size, requires new platforms, protocols, and programming. Platforms must be designed around low-leakage operation, offer a richer power supply control interface for system software, and employ an unconventional energy storage hierarchy. Protocols must not only be low-power, but they must also become low-energy, which affects initial and ongoing synchronization, and periodic communications. Systems programming, and especially bootup and communications, must become low-latency, by eliminating conservative timeouts and startup dependencies, and embracing high-concurrency. Applying these principles, we show that robust, indoor, perpetual sensing is viable using off-the-shelf technology.

Monjolo: an energy-harvesting energy meter architecture

Conventional AC power meters perform at least two distinct functions: power conversion, to supply the meter itself, and energy metering, to measure the load consumption. This paper presents Monjolo, a new energy-metering architecture that combines these two functions to yield a new design point in the metering space. The key insight underlying this work is that the output of a current transformer -- nominally used to measure a load current -- can be harvested and used to intermittently power a wireless sensor node. The hypothesis is that the nodes activation frequency increases monotonically with the primary loads draw, making it possible to estimate load power from the interval between activations, assuming the node consumes a fixed energy quanta during each activation. This paper explores this thesis by designing, implementing, and evaluating the Monjolo metering architecture. The results demonstrate that it is possible to build a meter that draws zero-power under zero-load conditions, offers high accuracy for near-unity power factor loads, works with non-unity power factor loads in combination with a whole-house meter, wirelessly reports readings to a data aggregator, is resilient to communication failures, and is parsimonious with the radio channel, even under heavy loads. Monjolo eliminates the high-voltage AC-DC power supply and AC metering circuitry present in earlier designs, enabling a smaller, simpler, safer, and lower-cost design point that supports novel deployment scenarios like non-intrusive circuit-level metering.

An energy-harvesting sensor architecture and toolkit for building monitoring and event detection

Understanding building usage patterns and resource consumption, particularly for existing buildings, requires a sensing infrastructure for the building. Often, deploying these sensors and obtaining real-time information is hindered by installation and maintenance difficulties resulting from scaling down and powering these devices. Devices that rely on batteries are limited by the scale of the batteries and the maintenance cost of replacing them while AC mains powered sensors incur high upfront installation costs. To mitigate these burdens, we present a new architecture for designing building-monitoring focused energy-harvesting sensors. The key to this architecture is masking the inevitable inter-mittency provided by energy-harvesting with a trigger abstraction that activates the device only when there is useful work to be done. In this paper, we describe our architecture and demonstrate how it supports existing energy-harvesting sensor designs. Further, we realize three additional design points within the architecture and demonstrate how the sensors are effective at building monitoring and event detection. The sensors, however, are classically disruptive: they improve ease of installation and maintenance, but to do so, they sacrifice some fidelity and reliability. Whether this trade-off is acceptable remains to be explored, but the technology needed to do so is now here.

Ownership is theft: experiences building an embedded OS in rust

Rust, a new systems programming language, provides compile-time memory safety checks to help eliminate runtime bugs that manifest from improper memory management. This feature is advantageous for operating system development, and especially for embedded OS development, where recovery and debugging are particularly challenging. However, embedded platforms are highly event-based, and Rusts memory safety mechanisms largely presume threads. In our experience developing an operating system for embedded systems in Rust, we have found that Rusts ownership model prevents otherwise safe resource sharing common in the embedded domain, conflicts with the reality of hardware resources, and hinders using closures for programming asynchronously. We describe these experiences and how they relate to memory safety as well as illustrate our workarounds that preserve the safety guarantees to the largest extent possible. In addition, we draw from our experience to propose a new language extension to Rust that would enable it to provide better memory safety tools for event-driven platforms.

Gemini: A Non-invasive, Energy-Harvesting True Power Meter

Power meters are critical for sub metering loads in residential and commercial settings, but high installation cost and complexity hamper their broader adoption. Recent approaches address installation burdens by proposing non-invasive meters that easily clip onto a wire, or stick onto a circuit breaker, to perform contact less metering. Unfortunately, these designs require regular maintenance (e.g. Battery replacement) or reduce measurement accuracy (e.g. Work poorly with non-unity power factors). This paper presents Gemini, a new design point in the power metering space. Gemini addresses the drawbacks of prior approaches by decoupling and distributing the AC voltage and current measurement acquisitions, and recombining them wirelessly using a low-bandwidth approach, to offer non-invasive real, reactive, and apparent power metering. Battery maintenance is eliminated by using an energy-harvesting design that enables the meter to power itself using a current transformer. Accuracy is substantially improved over other non-invasive meters by virtualizing the voltage channel -- effectively allowing the meter to calculate power as if it could directly measure voltage (since true power requires sample-by-sample multiplication of current and voltage measurements acquired with tight timing constraints). Collectively, these improvements result in a new design point that meters resistive loads with 0.6 W average error and a range of reactive and switching loads with 2.2 W average error -- matching commercial, mains-powered solutions.

Deltaflow: submetering by synthesizing uncalibrated pulse sensor streams

Current submetering systems suffer from prohibitive device costs, invasive installations, and burdensome maintenance. In this paper we present Deltaflow, a submetering system that can estimate the power draw of individual loads by augmenting aggregate measurements with very simple sensors. The key insight is that we can drastically reduce sensor complexity by encoding information in the mere existence of a radio transmission, rather than the contents of that transmission. A sensor consisting simply of a radio and an energy-harvesting power supply tuned to harvest a side-channel emission of energy consumption (e.g. light, heat, magnetic field, vibration) will exhibit an activation frequency that is correlated with the power draw of the load to which it is affixed. These sensors report their activations to the data-processing backend, which can determine the actual power draw by incorporating ground truth aggregate measurements such as those provided by utility meters. The server maps sensor activations to energy consumption by observing when the aggregate measurement and the sensor activation frequency change simultaneously. The server iteratively partitions the system history into discrete states which are used to construct and solve instances of a linear optimization problem. Solutions to the problem reveal the mapping from pulse frequencies to individual load power draw. This systems approach to submetering results in deployments that are easy to install and maintain, while contributing zero additional load, enabling building owners and occupants to simply affix tags to energy consumers and automatically begin receiving real-time power draw readings.

A networked embedded system platform for the post-mote era

For the last fifteen years, research explored the hardware, software, sensing, communication abstractions, languages, and protocols that could make networks of small, embedded devices---motes---sample and report data for long periods of time unattended. Today, the application and technological landscapes have shifted, introducing new requirements and new capabilities. Hardware has evolved past 8 and 16 bit microcontrollers: there are now 32 bit processors with lower energy budgets and greater computing capability. New wireless link layers have emerged, creating protocols that support rapid and efficient setup and teardown but introduce novel limitations that systems must consider. The time has come to look beyond optimizing networks of motes. We look towards new technologies such as Bluetooth Low Energy, Cortex M processors, and capable energy harvesting, with new application spaces such as personal area networks, and new capabilities and requirements in security and privacy to inform contemporary hardware and software platforms. It is time for a new, open experimental platform in this post-mote era.

Towards a perpetual wireless sensor node

We report our experimental findings on a perpetual wireless sensor node. Our perpetual node is based on the integration of a wireless sensor node that runs IEEE 802.15.4e technology on TIs MSP430 with a solar energy harvesting module that is based on TIs bq25504 modules. We show that by default running the time synchronized channel hopping (TSCH) MAC layer draws more power than the harvester is able to provide. To close that gap, enhancements that improve the power efficiency of TSCH protocol are described and results are presented. The enhancements proposed consist of shared slot suppression, slotframe skipping, and connection setup time reduction. It is shown that even with these enhancements consumed power is still greater than harvested power. We provide future directions on how to further reduce consumed power at the node.

Demo: An IEEE 802.15.4-compatible, battery-free, energy-harvesting sensor node

We present a battery-free sensornet edge node design that operates on ambient indoor lighting, drawing just microwatts, but still delivers readings several times per minute.