1. Research Topics Embedded, Real-time, Sensor Systems Frank Mueller moss
Research Topics Embedded, Real-time, Sensor Systems Frank Mueller moss.csc.ncsu.edu/~mueller
Center for Embedded Systems Research/
Dept. of Computer Science
North Carolina State University

2. Power-Aware RT Scheduling
voltage
current 1 2 3
EDF-DVS schemes on IBM PowerPC 405LP
Split task based on feedback of avg. exec. time
yield up to 54% reduction in energy
1-5% energy reduction for async. DVS modulation Ca Cb

3. Timing Analysis for Real-Time
Objective: meet deadline
Problem: need to know worst-case execution time (WCET)
Experimentally: inconclusive
We promote static analysis
Analyze your execution path
Additional benefit: energy savings
Dynamic voltage scaling through scheduling

4. Adaptive Encryption for Sensor Systems
requirements for cryptographic algo / embedded architectures
Experiments
mostly uniform cycle overhead for each word size (8/16/32 bits)
but differences among classes
Parameters that matter: text length, block size, architectural (few)
Uniformity  Approximate Model
Derive minimum requirements
predict performance on new hardware
Timing analysis for Sensor Nodes
Can be integrated with STI for feedback on integration benefits
Tool support for sensor networks w/ real-time constraints
Framework (API) for adaptive, low energy security in sensor networks

5. VISA: A Virtual Simple Architecture
hypothetical simple processor
static timing analysis applicable
WCET derived assuming the VISA
Exploiting performance gain
Complex processor typically much faster
Exploit newly-created slack
Dynamic voltage scaling
complex lower frequency
2 for 1: simple+complex mode in one architecture
Energy savings with DVS: 12-47%
Speculatively run on complex processor
gauge progress (on subtasks) to confirm timeliness
if not as timely, switch to simple mode
speculative frequency
(based on PETs)
recovery frequency
(based on WCETs)
frequency requirement
frequency (MHz)

6. Overview
Timing analysis framework (ToC’99, JRTS’99/00/01, RTSS’03, RTSS’04)
Toolset predicts max. execution time  scheduling
FAST: Frequency-Aware Timing Analysis (RTSS’03)
VISA: Architecture for Real-Time (ISCA’03,RTSS’04)
Real-time scheduling with dynamic voltage scheduling (LCTES’02, COLP’02, RTAS’04)
Adaptive Encryption for Sensor Systems (CASES’03)