Algis Rudys

Practical robust localization over large-scale 802.11 wireless networks

We demonstrate a system built using probabilistic techniques that allows for remarkably accurate localization across our entire office building using nothing more than the built-in signal intensity meter supplied by standard 802.11 cards. While prior systems have required significant investments of human labor to build a detailed signal map, we can train our system by spending less than one minute per office or region, walking around with a laptop and recording the observed signal intensities of our buildings unmodified base stations. We actually collected over two minutes of data per office or region, about 28 man-hours of effort. Using less than half of this data to train the localizer, we can localize a user to the precise, correct location in over 95% of our attempts, across the entire building. Even in the most pathological cases, we almost never localize a user any more distant than to the neighboring office. A user can obtain this level of accuracy with only two or three signal intensity measurements, allowing for a high frame rate of localization results. Furthermore, with a brief calibration period, our system can be adapted to work with previously unknown user hardware. We present results demonstrating the robustness of our system against a variety of untrained time-varying phenomena, including the presence or absence of people in the building across the day. Our system is sufficiently robust to enable a variety of location-aware applications without requiring special-purpose hardware or complicated training and calibration procedures.

Robotics-based location sensing using wireless ethernet

A key subproblem in the construction of location-aware systems is the determination of the position of a mobile device. This paper describes the design, implementation and analysis of a system for determining position inside a building from measured RF signal strengths of packets on an IEEE 802.11b wireless Ethernet network. Previous approaches to location awareness with RF signals have been severely hampered by non-linearity, noise and complex correlations due to multi-path effects, interference and absorption. The design of our system begins with the observation that determining position from complex, noisy and non-linear signals is a well-studied problem in the field of robotics. Using only off-the-shelf hardware, we achieve robust position estimation to within a meter in our experimental context and after adequate training of our system. We can also coarsely determine our orientation and can track our position as we move. By applying recent advances in probabilistic inference of position and sensor fusion from noisy signals, we show that the RF emissions from base stations as measured by off-the-shelf wireless Ethernet cards are sufficiently rich in information to permit a mobile device to reliably track its location.

On the feasibility of using wireless ethernet for indoor localization

IEEE 802.11b wireless Ethernet is becoming the standard for indoor wireless communication. This paper proposes the use of measured signal strength of Ethernet packets as a sensor for a localization system. We demonstrate that off-the-shelf hardware can accurately be used for location sensing and real-time tracking by applying a Bayesian localization framework.

Wireless LAN location-sensing for security applications

This paper considers the problem of using wireless LAN location-sensing for security applications. Recently, Bayesian methods have been successfully used to determine location from wireless LAN signals, but such methods have the drawback that a model must first be built from training data. The introduction of model error can drastically reduce the robustness of the location estimates and such errors can be actively induced by malicious users intent on hiding their location. This paper provides a technique for increasing robustness in the face of model error and experimentally validates this technique by testing against unmodeled hardware, modulation of power levels, and the placement of devices outside the trained workspace. Our results have interesting ramifications for location privacy in wireless networks.

Robotics-based location sensing using wireless Ethernet

Abstract A key subproblem in the construction of location-aware systems is the determination of the position of a mobile device. This article describes the design, implementation and analysis of a system for determining position inside a building from measured RF signal strengths of packets on an IEEE 802.11b wireless Ethernet network. Previous approaches to location-awareness with RF signals have been severely hampered by non-Gaussian signals, noise, and complex correlations due to multi-path effects, interference and absorption. The design of our system begins with the observation that determining position from complex, noisy and non-Gaussian signals is a well-studied problem in the field of robotics. Using only off-the-shelf hardware, we achieve robust position estimation to within a meter in our experimental context and after adequate training of our system. We can also coarsely determine our orientation and can track our position as we move. Our results show that we can localize a stationary device to within 1.5 meters over 80% of the time and track a moving device to within 1 meter over 50% of the time. Both localization and tracking run in real-time. By applying recent advances in probabilistic inference of position and sensor fusion from noisy signals, we show that the RF emissions from base stations as measured by off-the-shelf wireless Ethernet cards are sufficiently rich in information to permit a mobile device to reliably track its location.

Using wireless Ethernet for localization

IEEE 802.11b wireless Ethernet is rapidly becoming the standard for in-building and short-range wireless communication. Many mobile devices such as mobile robots, laptops and PDAs already use this protocol for wireless communication. Many wireless Ethernet cards measure the signal strength of incoming packets. This paper investigates the feasibility of implementing a localization system using this sensor. Using a Bayesian localization framework, we show experiments demonstrating that off-the-shelf wireless hardware can accurately be used for location sensing and tracking with about one meter precision in a wireless-enabled office building.

Hack-a-vote: Security issues with electronic voting systems

In a quest for election legitimacy, officials are increasingly deploying direct recording electronic (DRE) voting systems. A project to assess their trustworthiness revealed both the ease of introducing bugs into such systems and the difficulty of detecting them during audits.

Transactional rollback for language-based systems

Language run-time systems are routinely used to host potentially buggy or malicious codelets-software modules, agents, applets, etc.-in a secure environment. A number of techniques exist for managing access control to system services and even for terminating codelets once they have been determined to be misbehaving. However because codelets can be terminated anywhere in their execution, a codelets internal state might become inconsistent; restarting the codelet could result in unexpected behavior. Any state the codelet shares with other codelets may likewise become inconsistent, destabilizing those codelets as well. To address these problems, we have designed a mechanism, strictly using code-to-code transformations, which provides transactional rollback support for codelets. Each instance of a codelet is run in its own transaction, and standard (ACID) transactional semantics apply. All changes made by the codelet are automatically rolled back when the corresponding transaction aborts. We discuss a transactional rollback implementation for Java, and present its performance.