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Adam - Adaptive Monitoring in 5min

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Adam - Adaptive Monitoring in 5min

  1. 1. Low-Cost Adaptive Monitoring Techniques for the Internet of Things The AdaM Framework
  2. 2. The Challenges… Challenge 1 - Taming data volume and data velocity with limited processing and network capabilities Challenge 2 - IoT devices are usually battery-powered which means intense processing leads to less battery-life Data Volume Network Bandwidth Battery Life The Problems…
  3. 3. Research Question Can we reduce the volume of IoT generated data while at the same time reduce on device processing to preserve battery life?What if: • A framework could predict metric stream evolution and dynamically adapt the rate at which metrics are collected… • Filter out metric values when consecutive values do not differ and adapt to ensure accuracy defined by users is always met… 𝑠𝑖 𝑠𝑖+1 𝑇𝑖+1 Metric Stream 𝑀′ dynamically sampledMetric Stream 𝑀 with 𝑇 = 1𝑠
  4. 4. The AdaM Framework Raspberry Pi Arduino Beacons Processing Unit Dissemination Unit Adaptive Sampling Knowledge Base AdaM IoT Device metrics adjust filter range Adaptive Filtering A P I Activity Trackers Sensing Unit adjust sampling rate filtered metrics • Reduces on device processing, energy consumption and allocated bandwidth • Reduces volume and velocity of data generated in streaming networks • Achieves a balance between efficiency and accuracy • AdaM dynamically adapts the monitoring intensity of IoT devices based on metric stream evolution and variability AdaM: an Adaptive Monitoring Framework for Sampling and Filtering on IoT Devices. Trihinas, D.; Pallis, G.; and Dikaiakos, M. D. In 2015 IEEE International Conference on Big Data, (IEEE BigData 2015), pages 717--726, 2015.
  5. 5. AdaM in action! Steps Heartrate Calories 94% accuracy! 96% accuracy! 91% accuracy!
  6. 6. AdaM in action! 6x less processing! 4x less network traffic! 4x less energy usage! + AdaM 3 - 5 days 7 - 8 days

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