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Energy Conservation in wireless sensor networks

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  1. Energy Conservation in wireless sensor networks Kshitij Desai, MayureshRandive, AnimeshNandanwar

  2. Basic Design • Sensor Network Architecture Sink Sensor Network Internet

  3. Architecture of a Sensor Node • Ref: Energy Conservation in Wireless Sensor Networks – a Survey

  4. Observations • Communication Sub-system consumes more energy than computation sub-system • Energy to transmit one bit = Energy for execution 1000 . instructions • Radio component requires same order of energy for reception, transmission and idle states • Sensing sub-system might also require significant amount of energy based on the type of sensor node.

  5. Three Main enabling Techniques • Duty-cycling • Data-Driven approaches • Mobility

  6. Duty-cycling • Topology Control • Power Management • Sleep/Wake Protocols • On-demand, scheduled rendezvous and Async • MAC Protocols with low Duty-cycle • TDMA, Contention-based and hybrid

  7. Data-driven approaches • Data reduction • In-Network Processing • Data-Compression • Data-prediction • Stochastic, Time-series Forecasting and algorithmic approaches • Energy-efficient data acquisition • Adaptive Sampling • Hierarchical Sampling • Model-Driven active sampling

  8. Mobility-based approaches • Mobile-sink • Mobile-relay

  9. ATPC: Adaptive Transmission Power Control for WirelessSensor Networks

  10. Main Points • What is this paper about? • Power saving for wireless communication • Paper style? • Empirical study + a little theory work • What is the contribution? • Study of spatial-temporal impact on communication • Mechanism to adaptively achieve an optimal transmission power consumption

  11. Motivation TP1 TP2 TP2

  12. Motivation T2 TP1 T1 TP2 T2 TP1 The minimum transmission power level to save energy and maintain specified link quality

  13. Design Goals • Achieve energy efficiency • The minimum transmission power • Maintain Link Quality • Reliable links • In runtime systems, dynamic environments • Spatial impact • Temporal impact

  14. Roadmap Data Analysis Empirical Observation PART 1 Algorithm Design PART 2 Algorithm Evaluation

  15. Part 1-Transmission Power vs. Link Quality • Link Quality Metrics • RSSI (Received Signal Strength Indication), LQI (Link Quality Indication), and PRR (Packet Reception Ratio) • Transmission Power Level Index (3~31) • Experiments on Spatial Impact • 5 pairs of motes, 3 environments • 100 packets at each transmission power level • RSSI/LQI/PRR measured at different distances

  16. Part 1- Investigation of Spatial Impact (a) RSSI measured on a grass field (b) RSSI measured in a corridor • Different shapes at the same distance in different environments • Different degree of variation in different environments • Approximately linear (c) RSSI measured in a parking lot

  17. Investigation of Temporal Impact • Experiment on Temporal Impact • In brushwood where human activity is rare, over 72 hours • 9 MicaZ motes in a line, 3 feet apart • A group of 20 packets at each power level every hour (a) RSSI measured every 8-hour (b) RSSI measured every hour • 1. Vary gradually but noticeably over time • 2. Approximately parallel

  18. Part 1- Link Quality Threshold (a) RSSI Threshold on a grass field (b) LQI Threshold on a grass field Binary link quality thresholds Slight different in different environments

  19. Part 2- Model Design of ATPC • Use a linear model to approximate a non-linear correlation • rssi(tp) = a · tp +b • Least-square approximation • Dynamic model • a and b vary from time to time

  20. Part 2- ATPC Overview 25 8 Initialization Phase: build models from linear approximation Runtime Tuning Phase: pairwise closed loop control

  21. Part 2 – Closed Loop Control Start here RSSI, LQI and PRR

  22. Part 2- Experiment Setup • Current transmission power control algorithms • A node-level non-uniform solution (Non-uniform) • Network-level uniform solutions • Max transmission power level (Max) • The minimum transmission power level over nodes in a network that allows them to reach their neighbors (Uniform) • A 72-hour continuous experiment with MicaZ • A spanning tree of 43 nodes, 24 leaf nodes • Leaf nodes send 32 packets to the base every hour

  23. Part 2- Experimental Setup (a) Weather Conditions over 72 Hours (b) Spanning Tree Topology (c) Experimental Site

  24. Part 2- Packet Reception Ratio • E2E packet reception ratio • Max ~ 100% • ATPC ~ 98.3% • Uniform ~ 98.3% • Non-Uniform ~ 58.8% (b) PRR at a chosen link ATPC ~ constantly 100% Static transmission power ~ vary from 0% to 100%

  25. Part 2- Transmission Energy Consumption Relative energy consumption Max ~ 100% ATPC ~ 58.3% (1% control overhead) Uniform ~ 68.6% Non-Uniform ~ 43.2%

  26. Conclusions and Future Work • Benefits of ATPC lie in three core aspects: • ATPC maintains above 98% E2E PRR over time • ATPC achieves significant energy savings • 53.6% of the transmission energy of Max • 78.8% of the transmission energy of Uniform • ATPC accurately adjusts the transmission power • Adapting to spatial and temporal factors • Towards reliable and energy-efficient routing • Spatial reuse for concurrent transmissions

  27. Questions? Thank you very much!