IBM Research – Distributed and Fault Tolerant Computing – Current Seminars at Watson
Matt Welsh, Harvard University Title: Market-Based Programming Paradigms for Sensor Networks Date: 10/20/2004 Time: 2:00 -3:30 PM Location: Hawthorne 1S-F40 Host: Fred Douglis
Sensor networks present a novel programming challenge: that of achieving robust global behavior despite limited resources, varying node locations and capabilities, and changing network conditions. Current programming models typically require that global behavior be specified in terms of the low-level actions of individual nodes. This approach makes it extremely difficult to tune the operation of the sensor network as a whole.Ideally, sensor nodes should self-schedule to determine the set of operations that maximizes that node’s contribution to the network-wide task. In this talk, we present market-based macroprogramming (MBM), a new approach for achieving efficient resource allocation in sensor networks. Rather than programming individual sensor nodes, MBM defines a virtual market in which nodes sell goods (such as sensor readings or data aggregates) in response to prices that are established by the programmer. Nodes take actions to maximize their profit, subject to energy budget constraints. The behavior of the network is determined by adjusting the price vectors for each good, rather than by directly specifying local node programs. Nodes individually specialize their operation in response to feedback from payments. Market-based macroprogramming provides a useful set of primitives for controlling the aggregate behavior of sensor networks despite variance of individual nodes. We present the MBM paradigm and a sensor network vehicle tracking application based on this design, as well as a number of experiments demonstrating that MBM allows nodes to operate efficiently under limited energy budgets, while adapting to changing network conditions. This project is in collaboration with Geoff Mainland and David Parkes.
Matt Welsh is an assistant professor of Computer Science at Harvard University. Prior to joining Harvard, he received his Ph.D. from UC Berkeley, and spent one year as a visiting researcher at Intel Research Berkeley. His research interests span many aspects of complex systems, including Internet services, distributed systems, and sensor networks.