Jaein Jeong

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

Incremental network programming for wireless sensors

We present an incremental network programming mechanism which re programs wireless sensors quickly by transmitting the incremental changes for the new program version. Using the Rsync algorithm we generate the difference of the two program images, which allows us to distribute just the key changes of the program. Unlike previous approaches, our design does not assume any prior knowledge of the program code structure and can be applied to any hardware platform. To meet the resource constraints of wireless sensors we tuned the Rsync algorithm which was originally made for updating binary files among computationally powerful machines. In our design, the sensor node processes the delivery and the decoding of the difference script in separate steps. This makes it easy to extend for multi-hop network programming. We are able to achieve the speedup of 9.1 for changing a constant and 2.1 to 2.5 for changing a few lines in the source code over the non-incremental delivery.

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.

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

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.

Empirical Analysis of Transmission Power Control Algorithms for Wireless Sensor Networks

Previously, many researchers sought to optimize the throughput and power consumption by radio transmission power control, but the experimental platforms and the workloads did not reflect the reality of WSNs. We present a dynamic transmission-power-control algorithm based on previous studies and evaluate the algorithm using realistic multi-hop WSN workloads and a large Mica2dot-based testbed. We have found that potential gains of dynamic transmission-power control are much smaller than what is indicated by prior research. Compared to the fixed transmission-power control, the dynamic transmission-power control improves the power consumption up to 16% for convergence traffic, but no noticeable performance improvements for aggregation traffic. The effect of dynamic transmission-power control becomes larger as we reduce the radio duty cycle, with 37% power savings at a 10% duty cycle. This result suggests that dynamic transmission-power control is most useful in combination of low-power MAC protocols which implement radio low duty cycling.

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

Design and analysis of micro-solar power systems for Wireless Sensor Networks

Wireless sensor networks are fundamentally limited by their energy storage resources and the power they obtain from their environment. Several micro-solar powered designs have been developed to address this important problem but little analysis is available on key design trade-offs. We develop a taxonomy of the micro-solar design space identifying key components, design choices, interactions, challenges, and trade-offs. Based on this taxonomy, we provide an empirical and mathematical analysis of two prominent designs of micro-solar power systems (Heliomote and Trio), and interpret the results to propose design guidelines for micro-solar power systems.

A practical theory of micro-solar power sensor networks

Building a micro-solar power system is challenging because it must address long-term system behavior under highly variable solar energy and consider a large design space. We develop a practical theory of micro-solar power systems that is materialized in a simulation suite that models component and system behavior over a long time scale and in an external environment that depends on time, location, weather, and local variations. This simulation provides sufficient accuracy to guide specific design choices in a large design space. Unlike the many macro-solar calculators, this design tool models detailed behavior of milliwatt systems in the worst conditions, rather than typical behavior of kilowatt systems in the best conditions. Our simulation suite is validated with a concrete design of micro-solar power systems, the HydroWatch node. With our simulation suite, micro-solar power systems can be designed in a systematic fashion. Putting the model and empirical vehicle together, the design choices in each component of a micro-solar power system are studied to reach a deployable candidate. The deployment is evaluated by analyzing the effects of different solar profiles across the network. The analysis from the deployment can be used to refine the next system-design iteration.

A modular sensornet architecture: past, present, and future directions

ion that supports existing implementations, more so than building a narrow waist that exports a set of services that new implementations are expected to adhere to. While future applications may use such features, the disregard for these interfaces by current protocols, coupled with the desire to maintain a lean narrow waist, leads to a top-down focus. In designing the unifying link layer abstraction for T2 [20], our approach has been quite different. We began with a foundation similar to the previous version, pruning unneeded services and functionality. More importantly we synthesized a list of requirements for a diverse set of protocols and applications in order to ensure support in the upcoming version. We also focused on integrating cross-layer services, such as security and power management, working closely with developers of these stand-alone components and focused architectures. The result is a new link abstraction which we feel is lean, yet provides the essential set of services needed to support the majority of higher-level services.