development and evaluation of energy-efficient and adaptive protocolsfor wireless sensor networks

IEEE 3rd Latin-American Conference on Communications – LATINCOM 2011

Development and Evaluation of Energy-Efficient and Adaptive Protocolsfor Wireless Sensor Networks

Torsten Braun, Universität Bern, [email protected], rvs.unibe.ch

joint work with many other persons, see publications

mailto:[email protected]

http://www.iam.unibe.ch/

Torsten Braun: Development and Evaluation of Energy-Efficient and Adaptive Protocols for Wireless Sensor Networks

2

Overview

> Introduction— Wireless Sensor Network Applications and Application Requirements— Design, Implementation, Evaluation of WSN Protocols

> Experimentation Platform for WSN Research— Wireless Sensor Network Testbed — Software-Based Estimation of Energy Consumption

> WSN Research Experiments— Traffic-Adaptive and Energy-Efficient WSN MAC Protocol— Adaptive Forward Error Control in WSNs

> Conclusions> Outlook: Mobility Support

Belém, October 24, 2011


3

Wireless Sensor Network Applications

> REDE (REde de sensores sem fio para Detectar Enchentes) project (USP São Carlos, http://sp-river.blogspot.com)

> Outdoor deployment of wireless sensor network to measure water depth and pollution in creeks of the city of São Carlos SP

> SunSPOT motes and hydrostatic level and conductivity sensors.


Jó Ueyama, Daniel Roy Hughes, Nelson Matthys, Wouter Horré, Wouter Joosen, Christophe Huygens, Sam Michiels: An Event-based Component Model for Wireless Sensor Networks: a Case Study for River Monitoring, XXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos

http://sp-river.blogspot.com/


4


> Environmental monitoring (A4-Mesh, a4-mesh.unibe.ch) Thomas Staub, Benjamin Nyffenegger, Desislava Dimitrova, Torsten Braun: Operational Support of Wireless Mesh Networks Deployed for Extending Network Connectivity, 1st International Workshop on Opportunistic Sensing and Processing in Mobile Wireless Sensor and Cellular networks (MobiSense), Bilbao, May 2011


https://a4-mesh.unibe.ch/


5

A4-Mesh Impressions



6


> Monitoring and control of buildings using sensor nodes and artificial neural networks

Markus Wälchli, Torsten Braun: Building Intrusion Detection with a Wireless Sensor Network, ICST AdHocNets, Niagara Falls, 2009



7

Application Requirements

> Energy-efficient operation> Low delays> Reliability> Adaptivity to varying link characteristics and traffic load



8

Design, Implementation, and Evaluation of Wireless Sensor Network Protocols

> Simulations are only meaningful with accurate calibration of parameters, e.g., energy consumption, transmission characteristics, traffic models.

> Experiments in testbeds give insights about protocol behaviour in more realistic scenarios and system-related issues, but face several problems— Experiment control— Scalability— Reproducability— Energy measurements— Mobility


Wireless Sensor Network Testbed


10

TestbedTestbed

TestbedTestbed

TestbedTestbed

TestbedTestbed

TestbedTestbed

TestbedTestbed

Wireless Sensor Network Testbed (WISEBED)

> Recently finished FP7 Future Internet research project

> wisebed.eu > Pan-European federation of

9 WSN testbeds> approx. 1000 deployed nodes> Each partner runs own testbed

with different hardware.> Use of individual testbed or

interconnected testbeds


http://www.wisebed.eu/


11

General Testbed Infrastructure

> Portal— Gateway between Internet and WSN— Used for WSN management

> Wireless Sensor Network— Sensor nodes communicate with

each other.— Backbone used to communicate

with portal.> Internet

— connects all WISEBED testbeds


Internet

Wireless Sensor Network

(WSN)

Backbone

PortalDB

WSNTestbedpart of WISEBED

WSNTestbedpart of WISEBED


12

Testbed @ Universität Bern

Ethernet

Mesh Node

Portal(running TARWIS management system)

InternetUSBLANwireless

Sensor Node



13

Testbed @ Universität Bern

> Approx. 50 TelosB/MSB430 nodes connected to portal via Ethernet with temperature, humidity, light sensors



14

TARWIS System Architecture



15

Testbed / Sensor Node Reservation

> Reservation system maintains per-site reservation database.> User Interfaces

— Web-based user interface— iPhone application



16

TARWIS Experiment Configuration



17

TARWIS Experiment Monitoring



18

TARIWS-Generated Experiment Trace


Software-Based Estimation of Energy Consumption


20

Software-Based Estimation of Energy Consumption

> Problem: Equipment of sensor nodes with measurement hardware is — very expensive.— difficult in out-door environments / real-world deployments.— not sufficient to support energy awareness.

– Energy awareness: Application / system adapts operation in order to meet energy consumption constraints.

> Solution: Software-based energy measurement (calibration of software-based model using measurement hardware)



21

Hardware-Based Energy Measurements

> Measurement of current draw and voltage using Sensor Network Management Devices (SNMD) from KIT



22

Simple 3-State-Model


A. Dunkels, F. Osterlind, N. Tsiftes, Z. He: Software-based On-line Energy Estimation for Sensor Nodes. IEEE EmNets, 2007


23

Measured vs. Estimated Energy Consumption

Approach: Measurement of current draw in different states and energy estimation by



24

3-State-Model with State Transitions


Revised estimation:


25

Estimation Accuracy


OLS: Ordinary Least Squares Regression Analysis

On the Accuracy of Software-based Energy Estimation Techniques. Philipp Hurni, Torsten Braun, Benjamin Nyffenegger, Anton Hergenroeder: 8th European Conference on Wireless Sensor Networks (EWSN), Bonn, Germany, February 2011.

MaxMAC: Maximally Traffic-Adaptive and Energy-Efficient WSN MAC Protocol


27

MAC Protocols for Wireless Sensor Networks

1. Scheduled Protocols — Multiplexing and Allocation of channels, e.g., time multiplexing,

requires accurate time synchronization

2. Contention-based Protocols— Channel sharing and allocation on-demand, often: periodic wake-ups— Problems: collisions and delays— Sender must ensure that receiver is awake during transmission

– Transmissions of long preambles/beacons (B-MAC, X-MAC, WiseMAC)– Weakly synchronized wakeups (S-MAC, T-MAC)– Receiver signals wakeup (RI-MAC)

— Load adaptation– Adaptation of wakeup time dependent on activation events or load

(T-MAC, X-MAC)

Wake-up intervalBelém, October 24, 2011


28

WiseMAC

> Very energy-efficient MAC protocol, but adaptivity to traffic variation is very limited.

> Unsynchronized nodes wakeup for a short time> Tpreamble = min {4θL,T}

— θ: clock drift, L: time since last update, T: duration of a cycle— Max. clock drift: 2θL, sender must start preamble transmission 2θL

prior to wakeup and transmit it until 2θL after wakeup. > „Piggybacking“ of wakeup times

Enz et al.: WiseNET: An Ultralow-Power Wireless Sensor Network Solution, IEEE Computer, Vol. 37, No. 8; August 2004



29

MaxMAC: a Maximally Traffic-Adaptive and Energy-Efficient WSN MAC Protocol

> is based on sampling of preambles, cf. WiseMAC> integrates destination address into preamble to reduce overhearing> Additional wakeups for higher rates of received packets

(measurement by sliding window)— Periodic reports in acknowledgements from receiver to sender— State transitions if thresholds T1,T2,TCSMA are exceeded.

Base state

S12 *

duty cycle

S24 *

duty cycle

CSMA

RECV

packet rate ≥ T1 packet rate ≥ T2 packet rate ≥ TCSMA

packet rate < T1

Lease expiredpacket rate < T2

Lease expiredpacket rate < TCSMA

Lease expiredBelém, October 24, 2011


30

MaxMAC

CSMA

Philipp Hurni and Torsten Braun. MaxMAC: a maximally traffic-adaptive MAC protocol for wireless sensor networks. 7th European Conference on Wireless Sensor Networks (EWSN), Coimbra, Portugal, February 2010.



31

MaxMAC Implementation on MSB430

> Threshold parameters: T1 = 1, T2 = 2, TCSMA = 3 packets / s> Base duty cycle: 0.6 % (3 ms) for a base interval of 500 ms> Frame size: 40 bytes including header> Lease times: 3 s > Bit rate: 19.2 kbps> Implementation of packet burst mode



32

Implementation Experiences

Implementation of MaxMAC on MSB430 using Scatterweb operating system raised several problems:> Inaccurate execution of timers,

e.g., because of active event processing at timer expiration → somewhat earlier scheduling of timers

> Overhearing avoidance has not been supported by node hardware.



33

Experiments with Intruder Scenario I


WiseMAC

MaxMAC

CSMA


34

Experiments with Intruder Scenario II


Adaptive Forward Error Correction


36

Error Control in Wireless Sensor Networks

> Wireless channels in sensor networks have varying bit error rates, sometimes up to 20 %.

> Options— Automatic Repeat Request (ARQ)

– Retransmission adds delay.– Original transmission was useless, but consumed bandwidth and

energy.

— Forward Error Correction (FEC)– Relatively small delay (due to encoding and decoding) compared to

ARQ for error correction – En-/decoding can be costly (several 100 ms for decoding).– Too strong codes consume computing resources and bandwidth. – Too weak codes might not be able to correct errors.

> Proposed Approach: Adaptive FEC



37

Implementation of FEC Library


> Repetition Code> Hamming Code> Double Error Correction Triple Error Detection (DECTED)> Bose-Chaudhuri-Hocquengham (BCH)


38

Adaptive FEC


> Stateful Adaptive FEC (SA)— Selection of current code dependent on success of previous transmission

(next higher / lower level)— Quick adaptation

> Stateful History Adaptive (SHA)— History of last transmissions (here: 5)— For successful/failed transmissions: storage of next lower/higher level— Selection of level with majority in history— Reacts less quickly than SA-FEC

> Stateful Sender Receiver Adaptive (SSRA)— Consideration of number of corrected bit errors

by receiver (to be reported in acknowledgement)

(63,36)

Philipp Hurni, Sebastian Barhlomé, Torsten Braun: Link-Quality Aware Run-Time Adaptive Forward Error Correction Strategies in Wireless Sensor Networks, submitted


39

Energy Consumption by FEC and ARQ

> Additional power consumption by FEC> In case of no FEC, MSB430 node can enter lower power mode

with Idefault

> Energy for encoding/decoding 32 bytes (30/100 ms): 0.95 mJ> Energy for retransmission



40

Wisebed Experiments

> Different link characteristics → Deployment of a single FEC scheme would not be most efficient.



41

Static vs. Adaptive FEC


> Better error correction performance of adaptive FEC schemes than for static ones.

> Adaptive FEC advantages— Lower processing and energy costs— Lower bandwidth and lower interference

in multi-hop scenarios— Higher packet delivery rate— Adapt automatically to different

link characteristics


42

Conclusions

> Contributions— Design and experimental evaluation of energy-efficient, reliable, and

adaptive protocols > Experiences: Development and use of WSN testbed resulted in

— More efficient use of hardware resources— Testbed experiments as easy as simulations— Repeatability and larger number of experiments

(statistical significance)— Reproducability of experiments and results

> Outlook— Several experiences (testbeds, protocols) to be applied in other

areas, e.g. wireless mesh and ad-hoc networks— Mobility support in wireless sensor / mesh network testbeds



43

Field to be sprayed

chemicals

Sensor-UAV-link

UAV-UAV-link

Wireless Sensor Networks and UAVs in Agriculture

Field not to be sprayed

Fausto Guzzo da Costa, Torsten Braun, Jó Ueyama, Gustavo Pessin, Fernando Santos:Arquitetura baseada em veículos aéreos não tripulados e redes de sensores sem fio para aplicações agrícolas, VIII Congresso Brasileiro de Agroinformatica, SBIAGRO 2011, Bento GonçalvesBelém, October 24, 2011

http://www.innalogics.com.br/sbiagro/


44

VirtualMesh: Wireless and Mobile Network Emulation


Thomas Staub, Reto Gantenbein, Torsten Braun: VirtualMesh: an emulation framework for wireless mesh and ad hoc networks in OMNeT++, SIMULATION: Transaction of the Society for Modelling and Simulation International, Vol. 87, No. 1-2, January 1, 2011

http://www.scs.org/simulation


45

Mobility Support in Wisebed by VirtualMesh


Torsten Braun, Geoff Coulson, Thomas Staub: Towards Virtual Mobility Support in a Federated Testbed for Wireless Sensor Networks, 6th Workshop on Wireless and Mobile Ad-Hoc Networks (WMAN 2011), Kiel, Germany, March 10 - 11, 2011


46

Thanks for your attention !

> Contact: [email protected]> More information: rvs.unibe.ch


mailto:[email protected]

http://www.rvs.unibe.ch/

development and evaluation of energy-efficient and adaptive protocolsfor wireless sensor networks

Technology

evaluation of energy

awireless sensor network

evaluation ofenergyefficient

wirelesssensor networks

mobility support belm

traffic load belm

light sensors belm

db portal