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Real-Time Systems and Sensor Networks

Sang H. Son Department of Computer Science University of Virginia Charlottesville, Virginia 22904. Real-Time Systems and Sensor Networks. Input. Real-Time (Embedded) System. Real World. Output. Input current state (view) update tasks to be performed by real-time systems Output

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Real-Time Systems and Sensor Networks

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  1. Sang H. Son Department of Computer Science University of Virginia Charlottesville, Virginia 22904 Real-Time Systems and Sensor Networks

  2. Input Real-Time (Embedded) System Real World Output • Input • current state (view) update • tasks to be performed by real-time systems • Output • actions to change real world situation • information to be used to support decision-making

  3. Real-Time Systems • Real-time systems • typically embedded in a large complex system • timeliness and dependability (reliability) are crucial • explicit/implicit timing constraints (soft, firm, hard) • A large number of applications • aerospace and defense systems, nuclear systems, robotics, process control, agile manufacturing, stock trading, network and traffic monitoring and control, multimedia computing, databases,medical systems, wireless sensor networks • Rapid growth in research and development • workshops, symposia, journals • standards (RT-Linux, RT-Java, RT-COBRA, …)

  4. Time Constraints v(t) v0 d t v(t) v0 d1 d2 t

  5. Trends in Real-Time Systems Applications • Soft real-time requirements rather than hard ones • much wider applications • relates well with the notion of QoS • soft is harder to deal with than hard ones • Operate in unpredictable environments • WCET too pessimistic or high variance • unbounded arrival rate; overload unavoidable • Need to support multi-dimensional requirements • real-time, power, size, security, and fault-tolerance • conflicting resource requirements and system architecture • Embedded and interacting with physical world

  6. Real-time services in embedded networked systems flexible and adaptable (self-configurable) interaction with physical/distributed environment - sensors/actuators in mobile nodes using WSN group-based aggregation and confidence management scalability Multi-dimensional constraints real-time, location-dependence, power, mobility, wireless, size, cost, fault-tolerance, security and privacy Timely management of real-time data (QoD/QoS) large volume with temporal properties robust real-time data and event services Key Issues (Part of a Long List)

  7. Motivation increasing demands for real-time data/event services web-based information services and e-business sensor networks interactive rendering location-aware services in mobile networks temporary overload and service degradation inevitable Service quality: QoS parameters timeliness data freshness degree of imprecision behavior in transient state: overshoot and settling time QoS Management in Real-Time Data

  8. Feedback Control control input Controller Actuator Process Sensor feedback controlled variable reference (set point)

  9. Timeliness Specification Miss ratio Overshoot Steady state error % Reference Transient State Steady State Time Settling time

  10. Data Freshness Database Database Freshness: Set of continuous data Perceived Freshness: Set of continuous data accessed by timely transactions

  11. WSN Application Spectrum

  12. Recent advances in low-cost low-power devices large scale sensor networks (ad hoc mobile networks) each node consists of sensors/actuators/processors Issues in wireless sensor networks how to collect and disseminate real-time data QoS management under resource constraints how to conserve energy while satisfying application requirements efficient real-time localization consensus, aggregation, in-network processing, confidence, security Data/Event Services in Sensor Networks

  13. Event Services for Emergency Response Technology and ResearchMultidisciplinaryImpact • Sensor design • Application to emergency response services • Save lives • Minimize damage • Improve response to natural disasters or terrorist attacks • Confidence levels in data • Multi-level events • Real-Time • Minimize false alarms • Actual implementation Dynamic Deployment of Wireless Sensor Network (self-organizing) Evacuate people ahead of leak Explosion Detect compound event & dispatch emergency rescue team Gas Leak Simple event reports

  14. Automated real-time undersea surveillance project by Navy Acoustic communication in undersea Experiments performed in 2003 in Florida Three sensor nodes in a cluster Each had 3-dimensional magnetic sensor One submarine at a time moved through the network Data was gathered during experiments and analyzed later (not real-time) Undersea Surveillance

  15. Feature extraction from magnetic/acoustic sensors to mitigate false alarms Confidence to reduce false positives/negatives System architecture and trade-off analysis Identify system objectives and key performance parameters System configuration (# and type of sensor nodes, surveillance coverage, deployment, …) System parameters (sensing/communication ranges, duty cycles, data aggregation ratio, …) Adaptation under uncertainty Issues in Undersea Surveillance

  16. NSF REU (Research Experience for Undergrads) What is promised challenging problems rewarding research experience Offers will not last long call toll-free number 1-800-982-2205 e-mail to son@cs.virginia.edu Undergrad Research Assistant

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