Jay Taneja

Trio: enabling sustainable and scalable outdoor wireless sensor network deployments

We present the philosophy, design, and initial evaluation of the Trio testbed, a new outdoor sensor network deployment that consists of 557 solar-powered motes, seven gateway nodes, and a root server. The testbed covers an area of approximately 50,000 square meters and was in continuous operation during the last four months of 2005. This new testbed in one of the largest solar-powered outdoor sensor networks ever constructed and it offers a unique platform on which both systems and application software can be tested safely at scale. The testbed is based on Trio, a new mote platform that provides sustainable operation, enables efficient in situ interaction, and supports fail-safe programming. The motivation behind this testbed was to evaluate robust multi-target tracking algorithms at scale. However, using the testbed has stressed the system software, networking protocols, and management tools in ways that have exposed subtle but serious weaknesses that were never discovered using indoor testbeds or smaller deployments. We have been iteratively improving our support software, with the eventual aim of creating a stable hardware-software platform for sustainable, scalable, and flexible testbed deployments

Design, Modeling, and Capacity Planning for Micro-solar Power Sensor Networks

This paper describes a systematic approach to building micro-solar power subsystems for wireless sensor network nodes. Our approach composes models of the basic pieces - solar panels, regulators, energy storage elements, and application loads - to appropriately select and size the components. We demonstrate our approach in the context of a microclimate monitoring project through the design of the node, micro-solar subsystem, and network, which is deployed in a challenging, deep forest setting. We evaluate our deployment by analyzing the effects of the range of solar profiles experienced across the network.

Reducing Transient and Steady State Electricity Consumption in HVAC Using Learning-Based Model-Predictive Control

Heating, ventilation, and air conditioning (HVAC) systems are an important target for efficiency improvements through new equipment and retrofitting because of their large energy footprint. One type of equipment that is common in homes and some offices is an electrical, single-stage heat pump air conditioner (AC). To study this setup, we have built the Berkeley Retrofitted and Inexpensive HVAC Testbed for Energy Efficiency (BRITE) platform. This platform allows us to actuate an AC unit that controls the room temperature of a computer laboratory on the Berkeley campus that is actively used by students, while sensors record room temperature and AC energy consumption. We build a mathematical model of the temperature dynamics of the room, and combining this model with statistical methods allows us to compute the heating load due to occupants and equipment using only a single temperature sensor. Next, we implement a control strategy that uses learning-based model-predictive control (MPC) to learn and compensate for the amount of heating due to occupancy as it varies throughout the day and year. Experiments on BRITE show that our techniques result in a 30%-70% reduction in energy consumption as compared to two-position control, while still maintaining a comfortable room temperature. The energy savings are due to our control scheme compensating for varying occupancy, while considering the transient and steady state electrical consumption of the AC. Our techniques can likely be generalized to other HVAC systems while still maintaining these energy saving features.

Marionette: using RPC for interactive development and debugging of wireless embedded networks

A main challenge with developing applications for wireless embedded systems is the lack of visibility and control during execution of an application. In this paper, we present a tool suite called Marionette that provides the ability to call functions and to read or write variables on pre-compiled, embedded programs at run-time, without requiring the programmer to add any special code to the application. This rich interface facilitates interactive development and debugging at minimal cost to the node

Experiences with a high-fidelity wireless building energy auditing network

We describe the design, deployment, and experience with a wireless sensor network for high-fidelity monitoring of electrical usage in buildings. A network of 38 mote-class AC meters, 6 light sensors, and 1 vibration sensor is used to determine and audit the energy envelope of an active laboratory. Classic WSN issues of coverage, aggregation, sampling, and inference are shown to appear in a novel form in this context. The fundamental structuring principle is the underlying load tree, and a variety of techniques are described to disambiguate loads within this structure. Utilizing contextual metadata, this information is recomposed in terms of its spatial, functional, and individual projections. This suggests a path to broad use of WSN technology in energy and environmental domains.

A building block approach to sensornet systems

We present a building block approach to hardware platform design based on a decade of collective experience in this area, arriving at an architecture in which general-purpose modules that require expertise to de sign and incorporate commonly-used functionality are integrated with application-specific carriers that satisfy the unique sensing, power supply, and mechanical constraints of an application. Of course, modules are widespread, but our focus is far less on the performance of any individual module and far more on an overall architecture that supports the prototype, pilot, and production stages of design, and preserves the artifacts and learnings accumulated along the way. We present heuristics for partitioning functionality between modules and carriers, and identify guidelines for their interconnection. Our approach advocates exporting a wide electrical interface, eliminating the system bus, and supporting many physical interconnect options for modules and carriers. We evaluate this approach by constructing a family of general-purpose modules and application-specific carriers that achieve a high degree of reuse despite very different application requirements. We show that this approach shortens platform development time-to-result for novice graduate students, making custom platforms broadly accessible.

An architecture for energy management in wireless sensor networks

Sensornets are becoming more widely adopted for commercial and scientific use and, in settings where battery replacement or recharging is difficult, it is important that sensornets have long and predictable lifetimes. We thus expect energy management to play an increasingly important role in meeting user requirements. Today, system developers seek a balance between network lifetime and performance, but recent history shows that unexpected and dynamic environmental conditions often scuttle expected energy budgets. For example, many nodes in the Great Duck Island deployment were conjectured to have died prematurely because unexpected overhearing of traffic caused radios to become operational for longer than originally predicted [22]. This pattern was repeated in the Redwoods deployment, but for a supposedly different reason: some nodes seemingly died prematurely because they became disconnected from the wireless network and depleted their batteries trying to reconnect [24]. Even systems augmented with energy harvesting are still susceptible to this type of problem. In the Trio Testbed, seasonal and daily variations in solar power, the angle of inclination of the solar cell, the effect of dirt and bird droppings on the cells, and the inefficiencies in power storage and transfer resulted in node duty cycles ranging from 20% to 100% [5]. The issues with these deployments arise from mistaken assumptions, unforeseen difficulties, and unpredictable environmental dynamics. Solutions to these issues take two extreme approaches. At one extreme, some have proposed runtime adaptation to meet lifetime requirements [16] or energy availability [11, 10]. While promising, these efforts have addressed rather coarse-grained, high-level adaptation – for example, by adjusting sampling rates or varying the system-wide duty cycle – but they remain silent on prioritizing energy usage in a fine-grained and flexible manner. At the other extreme, low-level energy management mechanisms that give direct control over the hardware to multiple entities (e.g. network protocols) can be tedious to implement and difficult to debug because of the lack of any isolation. Arbitration can address the isolation problem, but it does not enable runtime adaptation to varying workloads [12]. We believe that using an energy management architecture would alleviate or even prevent these types of problems. SecEnforcement

Towards Cooperative Grids: Sensor/Actuator Networks for Renewables Integration

Faced with an uncertain path forward to renewables portfolio standard (RPS) goals and the high cost of energy storage, we believe that deep demand side management must be a central strategy to achieve widespread penetration of renewable energy sources. We examine the variability of wind as a source of renewable, non-dispatchable energy and the loads that can be dispatched to match sources of this type. We identify two classes of dispatchable energy loads, and create models for these loads to match their consumption to the generation of energy sources, while introducing {\em slack}, a generalized measure of dispatchability of energy. From these load models, we examine a number of techniques and considerations for source-following loads, including the sensitivity of thermostat constraints and the effects of aggregating appliance populations. Our results show a home heater that is able to reduce energy consumption by over 50% while increasing the proportion of renewable energy consumed versus grid energy.

@scale: insights from a large, long-lived appliance energy WSN

We present insights obtained from conducting a year-long, 455 meter deployment of wireless plug-load electric meters in a large commercial building. We develop a stratified sampling methodology for surveying the energy use of Miscellaneous Electric Loads (MELs) in commercial buildings, and apply it to our study building. Over the deployment period, we collected over nine hundred million individual readings. Among our findings, we document the need for a dynamic, scalable IPv6 routing protocol which supports point-to-point routing and multiple points of egress. Although the meters are static physically, we find that the set of links they use is dynamic; not using such a dynamic set results in paths that are twice as long. Finally, we conduct a detailed survey of the accuracy possible with inexpensive AC metering hardware. Based on a 21-point automated calibration of a population of 500 devices, we find that it is possible to produce nearly utility-grade metering data.

Making sanitation count: developing and testing a device for assessing latrine use in low-income settings

While efforts are underway to expand latrine coverage to an estimated 2.6 billion people who lack access to improved sanitation, there is evidence that actual use of latrines is suboptimal, limiting the potential health and environmental gains from containment of human excreta. We developed a passive latrine use monitor (PLUM) and compared its ability to measure latrine activity with structured observation. Each PLUM consisted of a passive infrared motion detector, microcontroller, data storage card, and batteries mounted in a small plastic housing that was positioned inside the latrine. During a field trial in Orissa, India, with ∼115 households, the number of latrine events measured by the PLUMs was in good agreement with that measured by trained observers during 5 h of structured observation per device per week. A significant finding was that the presence of a human observer was associated with a statistically significant increase in the number of latrine events, i.e., the users modified their behavior in response to the observer. Another advantage of the PLUM was the ability to measure activity continuously for an entire week. A shortcoming of the PLUM was the inability to separate latrine events that occurred in immediate succession, leading to possible undercounting during high-traffic periods. The PLUM is a promising technology that can provide detailed measures of latrine use to improve the understanding of sanitation behaviors and how to modify them and for assessing the intended health, livelihood, and environmental benefits of improved sanitation.