1. Exploiting Partially Reconfigurable FPGAs for Situation-Based Reconfiguration in Wireless Sensor Networks Rafael Garcia, Dr. Ann Gordon-Ross, Dr. Alan George Target Tracking Overview & Potential of Kalman Filter  Estimate state of dynamic system (moving target in this case) in a noisy environment  Commonly used in target tracking, extendable for multiple targets, models, and dimensions  Assume white Gaussian sensor noise Working w/ frames from USB Camera CPU-FPGA Transfer image array (1) FPGA-CPU Send X, Y, Width, Height to CPU (2) CPU Update frame Remove Background (2) Erosion1 (1) Erosion2 (2) Label (1) Group Properties (2) Sort (1) CPU Capture frame FPGA Process image FPGA-Amenable Features  Low memory/bandwidth requirements  Simple filter with streaming inputs & outputs  Requires only multiplication & addition, can be implemented using only logic & MACs  Filter receives/produces a stream of coordinates, not images VAPRES-based processing nodes Intelligent Sensor Nodes Environment Adaptation  Monitored by a process running inside the controlling agent (Microblaze)  Tracking filters loaded or unloaded dynamically during run-time in response to:  Number of targets inside tracking area  Power available at VAPRES-based node  Priority scheduling for critical targets Computation/Power Migration  Hardware modules can migrate between VAPRES based processing nodes  Offload processing if a node runs out of processing/power resources  Migration supported by Microblaze network interface Top Level Specifications  VAPRES - Virtual Architecture for Partially Reconfigurable Embedded Systems  Microblaze-based reconfigurable embedded system leveraging partial reconfiguration  Highly parametric architecture: e.g. number of partially reconfigurable regions (PRRs), FSL FIFOs depth, network-on-chip (SCORES) parameters  Two streaming communication backbones: o Microblaze-to-coprocessors through asynchronous FSL (fast streaming links) o Intra-coprocessor communication through light-weight custom network-on-chip (SCORES) Reconfigurable module features  Partial reconfigurable coprocessors can span multiple regions (PRRs)  Each PRR is independently clocked o Each coprocessor can run at an independent clock frequency o Clock frequency is managed by a controlling agent (Microblaze) Reconfiguration Drivers  Target behavior  Target criticality  Quality of sensor readings  Available resources/power Situation-Based Reconfiguration Policies Characteristics Sensor type Target Type High Power High Bandwidth PrecisionSizeKernel Type Low powerSlow targetsFixed PointSmallKalman Filter Fast samplingFast targetsFixed PointSmallKalman Filter Multi-scaleAirborne targets Floating Point Large Multiscale Kalman Smoother High-Noise Filtering Noisy or generic targets Floating Point MediumKalman Filter Feature selectiveMultiple targetsFloating Point LargeFeature Extraction/Selection Kalman Filter Taxonomy Working w/ JPEG image Testbed Implementation  CPU simulates the the sensor and the display