Waylon Brunette

Data MULEs: modeling a three-tier architecture for sparse sensor networks

This paper presents and analyzes an architecture to collect sensor data in sparse sensor networks. Our approach exploits the presence of mobile entities (called MULEs) present in the environment. MULEs pick up data from the sensors when in close range, buffer it, and drop off the data to wired access points. This can lead to substantial power savings at the sensors as they only have to transmit over a short range. This paper focuses on a simple analytical model for understanding performance as system parameters are scaled. Our model assumes two-dimensional random walk for mobility and incorporates key system variables such as number of MULEs, sensors and access points. The performance metrics observed are the data success rate (the fraction of generated data that reaches the access points) and the required buffer capacities on the sensors and the MULEs. The modeling along with simulation results can be used for further analysis and provide certain guidelines for deployment of such systems.

Data MULEs: modeling and analysis of a three-tier architecture for sparse sensor networks

Abstract This paper presents and analyzes a three-tier architecture for collecting sensor data in sparse sensor networks. Our approach exploits the presence of mobile entities (called MULEs) present in the environment. When in close range, MULEs pick up data from the sensors, buffer it, and deliver it to wired access points. This can lead to substantial power savings at the sensors as they only have to transmit over a short-range. This paper focuses on a simple analytical model for understanding performance as system parameters are scaled. Our model assumes a two-dimensional random walk for mobility and incorporates key system variables such as number of MULEs, sensors and access points. The performance metrics observed are the data success rate (the fraction of generated data that reaches the access points), latency and the required buffer capacities on the sensors and the MULEs. The modeling and simulation results can be used for further analysis and provide certain guidelines for deployment of such systems.

Exploiting mobility for energy efficient data collection in wireless sensor networks

We analyze an architecture based on mobility to address the problem of energy efficient data collection in a sensor network. Our approach exploits mobile nodes present in the sensor field as forwarding agents. As a mobile node moves in close proximity to sensors, data is transferred to the mobile node for later depositing at the destination. We present an analytical model to understand the key performance metrics such as data transfer, latency to the destination, and power. Parameters for our model include: sensor buffer size, data generation rate, radio characteristics, and mobility patterns of mobile nodes. Through simulation we verify our model and show that our approach can provide substantial savings in energy as compared to the traditional ad-hoc network approach.

Making Sensor Networks Practical with Robots

While wireless sensor networks offer new capabilities, there are a number of issues that hinder their deployment in practice. We argue that robotics can solve or greatly reduce the impact of many of these issues. Our hypothesis has been tested in the context of an autonomous system to care for houseplants that we have deployed in our office environment. This paper describes what we believe is needed to make sensor networks practical, the role robots can play in accomplishing this, and the results we have obtained in developing our application.

Reminding About Tagged Objects Using Passive RFIDs

People often misplace objects they care about. We present a system that generates reminders about objects left behind by tagging those objects with passive RFID tags. Readers positioned in the environment frequented by users read tags and broadcast the tags’ IDs over a short-range wireless medium. A user’s personal server collects the read events in real-time and processes them to determine if a reminder is warranted or not. The reminders are delivered to a wristwatch-sized device through a combination of text messages and audible beeps. We believe this leads to a practical and scalable approach in terms of system architecture and user experience as well as being more amenable to maintaining user privacy than previous approaches. We present results that demonstrate that current RFID tag technology is appropriate for this application when integrated with calendar information.

PlantCare: An Investigation in Practical Ubiquitous Systems

Ubiquitous computing is finally becoming a reality. However, there are many practical issues that stand in the way of mass acceptance. We have been investigating these practical concerns within the context of an autonomous application that takes care of houseplants using a sensor network and a mobile robot. We believe that emphasizing autonomy and thereby minimizing demands on users will help us address the many practical concerns that will arise not only in PlantCare but also in many other ubiquitous applications. In this paper, we discuss the technical challenges that we have encountered while trying to make PlantCare a reality and report on our experience in addressing these challenges.

Open data kit 2.0: expanding and refining information services for developing regions

Open Data Kit (ODK) is an open-source, modular toolkit that enables organizations to build application-specific information services for use in resource-constrained environments. ODK is one of the leading data collection solutions available and has been deployed by a wide variety of organizations in dozens of countries around the world. This paper discusses how recent feedback from users and developers led us to redesign the ODK system architecture. Specifically, the design principles for ODK 2.0 focus on: 1) favoring runtime languages over compile time languages to make customizations easier for individuals with limited programming experience; 2) implementing basic data structures as single rows within a table of data; 3) storing that data in a database that is accessible across applications and client devices; and 4) increasing the diversity of input types by enabling new data input methods from sensors. We discuss how these principles have led to the refinement of the existing ODK tools, and the creation of several new tools that aim to improve the toolkit, expand its range of applications, and make it more customizable by users.

Open data kit sensors: a sensor integration framework for android at the application-level

Smartphones can now connect to a variety of external sensors over wired and wireless channels. However, ensuring proper device interaction can be burdensome, especially when a single application needs to integrate with a number of sensors using different communication channels and data formats. This paper presents a framework to simplify the interface between a variety of external sensors and consumer Android devices. The framework simplifies both application and driver development with abstractions that separate responsibilities between the user application, sensor framework, and device driver. These abstractions facilitate a componentized framework that allows developers to focus on writing minimal pieces of sensor-specific code enabling an ecosystem of reusable sensor drivers. The paper explores three alternative architectures for application-level drivers to understand trade-offs in performance, device portability, simplicity, and deployment ease. We explore these tradeoffs in the context of four sensing applications designed to support our work in the developing world. They highlight a range of sensor usage models for our application-level driver framework that vary data types, configuration methods, communication channels, and sampling rates to demonstrate the frameworks effectiveness.

Challenges for Pervasive RFID-Based Infrastructures

The success of RFID in supply chain management is leading many to consider more personal and pervasive deployments of this technology. Unlike industrial settings, however, deployments that involve humans raise new and critical problems related to privacy, security, uncertainty, and a more diverse and evolving set of applications. At the University of Washington, we are deploying a building-wide RFID-based infrastructure with hundreds of antennas and thousands of tags. Our goal is to uncover the issues of pervasive RFID deployments and devise techniques for addressing these issues before such deployments become common place. In this paper, we present the challenges encountered and lessons learned during a smaller-scale pilot deployment of the system. We show some preliminary results and, for each challenge, discuss how we addressed it or how we are planning on addressing it

Building a transportation information system using only GPS and basic SMS infrastructure

This work consists of two main components: (a) a longitudinal ethnographic study in Kyrgyzstan that demonstrates the importance of transportation resources in the developing world and how to plan for an appropriate ICT solution, and (b) the results of a proof-of-concept system engineered to create a bottom-up, transportation information infrastructure using only GPS and SMS. Transportation is a very important shared resource; enabling efficient and effective use of such resources aids overall development goals.