EECS 598: Wireless Sensor Networks

Technologies, Systems, and Applications

Course Summary

Motivation. Some of the most daunting challenges facing society today deal with healthcare, energy, and the environment. This course is predicated on a simple hypothesis: that real-time, high-fidelity data about physical processes can dramatically improve their operation, thereby reducing healthcare costs while improving service, reducing energy usage while providing equivalent useful work, and helping save the planet through better visibility and control of our environmental explosure and impact. The challenge lies in affordably and scalably instumenting the physical world to gather, analyze, and act on this data.

Overview. EECS 598 is a graduate-level introduction to wireless, embedded, internetworked sensor/actuator ("sensornet") systems, an emerging technology that can provide visibility into and control over complex physical processes. Sensornet systems have applications to many societal-scale problems including health, safety, energy, and the environment. However, their design raises challenges across all areas of computer systems research, including platform architecture, power systems, operating systems, embedded databases, networking, data management, and machine learning. Many of these challenges stem from severe energy-constraints, deep physical embedding, volatile network connectivity, and small physical form factor, all of which present different design issues than traditional computing systems, and require a different design approach.

Focus. This course will focus on fundamental technology trends, system software design and implementation, and emerging applications areas. The course will expose students to the platforms, tools, and software used for modern sensornet research. Students will read and present research papers, participate in discussion and debate, program and deploy wireless sensor nodes, and complete an independent or group research project. The programming assignments will be both fun (students can monitor their own sleeping patterns, measure their personal energy consumption, or visualize their real-world social network interactions) and instructive (students will learn how to use the TinyOS toolchain, program sensor nodes in C/nesC, and deploy an IPv6 low-power wireless network). Projects may focus on new platform technology, a novel software system, or a new application area. In particular, applications to personal health, energy, and the environment will be emphasized.

Enrollment and Grading. The course is being offered as a special topics course and is open to graduate students in CSE or ECE, or a related discipline, as well as advanced undergraduate students with a strong interest in research (with permission of the instructor). Grading will be based on: individual or group project (50%), homework/programming assignments (25%), and paper summaries/class participation (25%).

Syllabus