ITR Collaborative Research: Energy-efficiency and Reliability in Dense Sensor Networks: A Distributed Signal Processing Perspective

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

Kannan Ramchandran U of Cal Berkeley This proposal addresses some important components in the theoretical and algorithmic signal processing machinery needed to make low-power, ubiquitous sensor networks a reality. The physical and hardware attributes as well as the computing and communication capabilities of these low-power, low-cost sensors, particularly those based on high-density MEMS devices, have the potential to revolutionize next-generation information technology. Indeed, next-generation MEMs sensors are expected to be very cheap and very small (of the order of one millimeter cube) with a communication range of several hundred meters and a bandwidth of tens to hundreds of kilobits per second. The challenge is to build a pervasive, reliable, mas-sively distributed, dynamically self-conguring dense sensor network system out of these low-cost, ubiquitous devices. While the hardware and computational infrastructure are following Moore's law, the system-level expertise in terms of both theoretical and algorithmic knowledge-base needed to fully harness the potential of this infrastructure is sadly lagging behind. The challenges presented by these networks are far beyond existing theories and algorithms, and in many cases require a fundamental paradigm shift from centralized to distributed architectures. This proposal is accordingly motivated at developing some important components of the signal processing and communication system machinery needed to make this dream a reality.