James Horey


Curriculum Vitae


Research Statement [HTML] [PDF]

SenseReduce: A Distributed Programming Model for Streaming, Geospatial Data

Geospatial data is increasing both in volume and complexity. Much of this volume stems from new technologies, including sensor networks, that are able to stream back geo-located data at very high temporal resolutions. In addition, remote sensing technologies (i.e. satellites, high-aerial imagery) provide high spatial resolution data. In this project, we are developing a novel distributed programming tool inspired by MapReduce for geospatial data. Our project will be able to handle geospatial data in a transparent fashion and take advantage of the unique features of geospatial data for improved execution.


Sensorpedia is a program initiated by Oak Ridge National Laboratory (ORNL) to utilize Web 2.0 social networking principles to organize and provide access to online sensor network data and related data sets. Sensorpedia is based on the same underlying social networking and collaboration principles used by popular web sites such as Wikipedia, Squidoo, Google Maps, and Facebook. Instead of networking users based on mutual personal interests, Sensorpedia networks users based on mutual information interests. It provides near-real-time collaboration among communities with requirements to share sensor information. An open API and flexible access controls ensure Sensorpedia will work for everyone, regardless of application requirements.

Negative Survey Methods for Anonymous Data Collection

Sensor networks involving human participants will require privacy protection before wide deployment is feasible. Providing this privacy has typically involved the use of crytographic approaches that must maintain complicated infrastructures and protocols for key maintainence. The negative survey is an alternative, lower overhead method for privacy protection that can be used in applications that only require aggregate data. In the negative survey, sensor nodes, transmit a sample of the data complement to a basestation. The basestation then uses the samples to reconstruct a histogram of the original values.

Tables: A Table-based Language Environment for Sensor Networks

Programming for wireless sensor networks can be a difficult and frustrating task. Tables is a graphical programming environment that addresses this problem by utilizing a spreadsheet-inspired programming interface that interacts with a local runtime executing on sensor nodes. Tables emphasizes ease-of-use by reusing spreadsheet abstractions, such as pivot tables and functions, to interactively program the sensor network. By using these familiar tools, users are able to construct complex applications that include local data filtering and collective processing.