Research in embedded networked sensing has thus far focused primarily on the design of hardware architectures for sensor nodes and application protocols to realize desired functionality for operation of such ad hoc, untethered, and resource constrained networks. This talk will examine networked sensing from algorithm design and application development perspective and develop an alternate view of application synthesis for such systems. The tradeoffs in using different program flow mechanisms will be explored from the perspective of system level designers, application developers, and end users of networked sensor systems.  We present a data driven programming model for sensor networks called the Abstract Task Graph (ATaG).  ATaG separates the application functionality from non-functional aspects of control and coordination, thereby enabling an end-to-end methodology for architecture-independent programming and automatic compilation for a class of networked sensor systems. Compile time optimizations will be illustrated using task placement problems. We will also discuss a tool chain for application synthesis.

Biography：

Viktor K. Prasanna (V. K. Prasanna Kumar) received his BS in Electronics Engineering from the Bangalore University, MS from the School of Automation, Indian Institute of Science and Ph.D. in Computer Science from the Pennsylvania State University. Prasanna has published extensively and consulted for industries. He is the Steering Committee Co-Chair of the International Parallel & Distributed Processing Symposium (IPDPS) [merged IEEE International Parallel Processing Symposium (IPPS) and Symposium on Parallel and Distributed Processing (SPDP)]. He is the Steering Committee Chair of the International Conference on High Performance Computing (HiPC). He serves on the editorial boards of the Journal of Parallel and Distributed Computing, IEEE Transactions on Parallel and Distributed Systems and the IEEE Transactions on Computers. He was the founding chair of the IEEE Computer Society's Technical Committee on Parallel Processing. He is a Fellow of the IEEE.