Design suite for deeply embedded cyber physical systems
ACM SIGBED Review - Special issue on the RTSS forum on deeply embedded real-time computing
Performance of Bulk Data Dissemination in Wireless Sensor Networks
DCOSS '09 Proceedings of the 5th IEEE International Conference on Distributed Computing in Sensor Systems
Heuristics for scheduling periodic real-time streams in wireless sensor networks
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Pervasive and Mobile Computing
Bulk data dissemination in wireless sensor networks: Modeling and analysis
Computer Networks: The International Journal of Computer and Telecommunications Networking
BAND-AiDe: A Tool for Cyber-Physical Oriented Analysis and Design of Body Area Networks and Devices
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on CAPA'09, Special Section on WHS'09, and Special Section VCPSS' 09
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ANDES, for modeling a wireless sensor network system and analyzing its performance before deployment. ANDES enables designers to systematically develop a model for the system, refine it iteratively by tuning the system parameters based on existing analysis techniques, and resolve key design decisions according to the required system performance. We also present a real- time communication schedulability analysis for sensor networks based on exact characterization which utilizes information regarding network topology and workload characteristics to analyze the schedulability of a set of periodic streams with real- time constraints. We further demonstrate the use of ANDES for the designers through detailed case studies where we design wireless sensor network applications (for target detection and environmental monitoring) using ANDES and validate the results through simulations. Currently, ANDES supports communication schedulability analysis, target tracking analysis and real-time capacity analysis which work on system models with differing levels of detail. ANDES has been developed by extending the AADL/OSATE framework which has been used extensively for real-time and embedded systems. Based on key insights gained from the development of this analysis tool, we address issues in AADL for its use in the field of wireless sensor networks. We have developed a plug-in for ANDES, called ModelGeneration, which bridges the gap between the semantics needed for sensor networks and the syntax supported by AADL. This makes it easy for sensor network designers to build system models that are intuitive to them. Furthermore, ANDES is extensible and new analysis techniques can be easily incorporated into the toolset.