Energy Conservation in wireless sensor networks Kshitij Desai, Mayuresh Randive, Animesh Nandanwar

Basic Design Sensor Network Architecture Internet Sensor Network Sink

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

Observations Communication Sub-system consumes more energy than computation sub-system Energy to transmit one bit = Energy for execution 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.

Three Main enabling Techniques Duty-cycling Data-Driven approaches Mobility

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

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

Mobility-basedapproaches Mobile-sink Mobile-relay

ATPC: Adaptive Transmission Power Control for Wireless Sensor Networks

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

Motivation 11 TP1 TP2

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

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

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

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 15

Part 1- Investigation of Spatial Impact 16 (a) RSSI measured on a grass field (c) RSSI measured in a parking lot 1.Different shapes at the same distance in different environments 2.Different degree of variation in different environments 3.Approximately linear (b) RSSI measured in a corridor

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 Vary gradually but noticeably over time 2. Approximately parallel (a) RSSI measured every 8-hour (b) RSSI measured every hour

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

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 19

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

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

Part 2- Experiment Setup 22 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

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

Part 2- Packet Reception Ratio 24 (a)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%

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

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 26

Questions? 27 Thank you very much!