Networking with Low Duty-Cycled Wireless Sensors
Assistant Professor -EECS Dept.
University of Michigan
Rapid advances in MEMS technology and integrated sensing, processing, and wireless communications have enabled many emerging wireless sensor network applications. They are expected to be deployed in large quantities for a variety of purposes, including enviornmental monitoring, surveillance, and left to self-organize and operate on battery power, which is not always renewable, it is critical to operate these sensors in a highly energy efficient manner. It has long been observed that these low power, low range sensors consume significant amount of energy while idling compared to that consumed during transmission and reception. Consequently one of the most effective way of conserving energy is to simply turn the sensors off for a large portion of the time. However, operating sensors on a low duty cycle — the fraction of time the sensor stays on — inevitably disrupts the communication and sensing capabilities of the network. Thus in order to provide the same level of performance not only do we need redundancy in the network, but also good networking mechanisms that work well with low duty-cycled sensors. In this talk we will discuss the challenges and research issues involved in low duty-cycled sensor networks and present recent results on using these
sensors to provide sensing coverage and network connectivity. In particular
we will examine two broad classes of methods used to duty cycle the sensors,
the random and the coordinated algorithms. We will also discuss the performance
implications of duty-cycling sensors and various design trade-offs.
Mingyan Liu received her Ph.D. Degree in electrical engineering from the
University of Maryland, College Park, in August 2000. She joined the
Department of Electrical Engineering and Computer Science at the University
of Michigan, Ann Arbor, in September 2000, where she is currently an Assistant
Professor. Her research interests are in performance modeling, analysis,
energy-efficiency and resource allocation issues in wireless mobile ad hoc
networks, wireless sensor networks, and terrestrial satellite hybrid networks.