Energy Aware Communication for Wireless Sensor Networks Dirk Pesch - - PowerPoint PPT Presentation

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Energy Aware Communication for Wireless Sensor Networks Dirk Pesch - - PowerPoint PPT Presentation

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Energy Aware Communication for Wireless Sensor Networks Dirk Pesch Head of Centre NIMBUS Centre for Networked Embedded Systems Cork Institute of Technology dirk.pesch@cit.ie http://www.nimbus.cit.ie Wireless Sensor Networks - WSN Next stage

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Energy Aware Communication for Wireless Sensor Networks

Dirk Pesch

Head of Centre NIMBUS Centre for Networked Embedded Systems Cork Institute of Technology dirk.pesch@cit.ie http://www.nimbus.cit.ie

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 2

Wireless Sensor Networks - WSN

Next stage in distributed sensing is combining sensing with actuation and control towards Cyber Physical Systems (CPS) or Networked Embedded Control Systems (NECS)

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 3

Example Application: Building Energy Management

Buildings consume 40% of total U.S. energy

  • 71% of electricity
  • 54% of natural gas

No Single End Use Dominates

Building sector has: Largest Energy Use! Fastest growth rate!

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 4

Sensor-Actuator Networks in Building Management

  • Energy in buildings accounts for

almost half of the total amount of energy consumed in EC

  • Fossil fuels the primary energy

source, building sector produces 22%

  • f total CO2 emissions - more than

produced by the industrial sector

  • Almost 85% of the energy is for low

temperature applications such as space and water heating

  • Retrofit WSAN can contribute to

energy reduction

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 5

What are the challenges in WSAN Design?

  • Cost effective energy management for long term

autonomous operation of large scale WSAN

– Autonomous, computationally efficient power management – Energy harvesting

  • Design and Deployment support for large WSAN

– Tools that support design to achieve joint design of

  • wireless network
  • often heterogeneous sensing/actuation requirements

– Need to estimate lifetime of WSANs prior to deployment

  • Reliable wireless communication

– Co-existence issues in unlicensed radio spectrum – Harsh radio environments in many application domains – Reliability to support control over wireless

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 6

More Challenges

  • Management of QoS and energy expenditure to support

control over wireless

– Current control requires real-time real-time data delivery – Future joint design of wireless networks and control applications

  • Management and operation of large scale WSAN

– Need for WSAN to adapt autonomously to environmental changes to minimise power consumption at all times – But also desire to manage and diagnose WSAN operation in many critical applications

  • Need for WSN design templates to avoid custom design

for every application

– Too often custom designs for each application – Templates are required to reduce costs in WSN design

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 7

Example: Energy Management Framework for IEEE802.15.4

Power Management Network Transport

PER target Reliability Redundancy Delay Duty cycle

Link Adaptation Media Acces s Control

RSS Life-time PRR NMSG

PHY Measurements NWK Requirements

Sensing rate SNR NED

Physical layer

TP DR CW BE Data Rate (DR) Transmit Power (TP) Beacon Order (BO) Superframe Order (SO) Contention Window (CW) Backoff Exponent (BE) PLE PDC SO BO

TFI

PIC

Shared Pool

ETE delay

Link estimation Traffic estimation Frame Transmission

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Duty Cycle Learning (DCLA)

  • The DCLA protocol is based
  • n Q-learning
  • DCLA explores and selects

new actions adaptively according to the rewards received

  • DCLA adapts duty cycle in

event-based scenarios

  • Implemented in OPNET and
  • n telosB motes

START Any frames received? Preliminary exploration phase

No Yes

END Select next action based on round-robin

Yes No

Increase learning rate Select max inactive period max(ai) Select next action based on e-greedy Stable state (e = 0)

Yes No

Update r(ai) Greedily selected a different action? Decrease exploration rate

No

Increase exploration rate

Yes

Has the reward changed?

No

Select next action based

  • n traffic change & last

stable Increase learning rate Increase exploration rate

  • R. de Paz Alberola, D. Pesch, “Duty Cycle Learning Algorithm (DCLA) for

IEEE 802.15.4 Beacon-Enabled Wireless Sensor Networks”, Ad-hoc Networks, Elsevier, (http://dx.doi.org/10.1016/j.adhoc.2011.06.006)

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Average Duty Cycle (DC) selection Average end-to-end delay (D) Probability of Success (PS) Energy Efficiency

Periodic Monitoring Application

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Instantaneous DC selection Probability of Success Energy Efficiency

  • PIR sensors

detect event and report to the sink

  • Other nodes

generate periodic monitoring data

Event-based Monitoring

30m 30m

Event detection

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Distributed Duty Cycle Management (DDCM)

  • Distributed Duty Cycle Management (DDCM) for IEEE 802.15.4

Beacon-Enabled Wireless Mesh Sensor Networks.

– DDCM uses DCLA to adapt a node’s duty cycle to the network traffic and manages the allocation of time slots as well as the prevention and resolution of possible slot conflicts within a mesh network

Beacon Interval (BI) Coordinator 1 (BO= 3)

SD

Transmitted Beacon Tracked Beacons Coordinator 2 (BO= 4) Coordinator 3 (BO= 5)

ESD BSD

SD

SD BSD SD BSD ESD

Multi-superframe duration (MD) Superframe duration (SD)

BSD BSD BSD

Beacon Interval (BI)

SD ESD SD

Broadcast SD Extended SD

  • R. de Paz Alberola, B. Carballido Villaverde, D. Pesch, “Distributed Duty Cycle Management (DDCM) for IEEE

802.15.4 Beacon-Enabled Wireless Mesh Sensor Networks”, in Proc. of 5th IEEE International Workshop on Enabling Technologies and Standards for Wireless Mesh Networking, Valencia, Spain, October 2011

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 12

Evaluation Results

Probability of Success Average Duty Cycle Selected Energy Efficiency

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 13

Wireless Sensor Network Design

Wireless Network Planning Tool Optimally placing wireless devices is a challenge, especially for large network deployments. To save time and money during deployment, Nimbus Design Tool can automatically design and

  • ptimise the position of wireless devices to meet

site specific application needs. User friendly GUI >> Minimal Experience Required From Design to Deployment With Nimbus Design Tool, designers are aided in all phases of the planning process. This approach ensures that the user considers the impact of the deployment environment, application requirements, user density, etc

  • n

network performance. The design tool can also be used to evaluate network expansion or the viability of new wireless applications.

Wireless Network Design Process

Requirements Gathering Automatic Design & Optimisation Deployment PHASE 1 PHASE 2 PHASE 3 PHASE 4 Verification

  • A. Guinard, M. S. Aslam, D. Pusceddu, S. Rea, A. McGibney, D. Pesch, “Design and Deployment Tool for In-Building Wireless Sensor Networks: a Performance

Discussion”, in Proc. 7th IEEE Performance & Management of Wireless and Mobile Networks (P2MNET 2011), Bonn, Germany, Oct. 2011

  • A. Mc Gibney, A. Guinard, D. Pesch, “Wi-Design: A Modelling and Optimization Tool for Wireless Embedded Systems in Buildings”, in Proc. 7th IEEE Performance &

Management of Wireless and Mobile Networks (P2MNET 2011), Bonn, Germany, October 2011

  • A. Guinard, A. McGibney, D. Pesch, “A Wireless Sensor Network Design Tool to Support Building Energy Management”, in Proc. of 1st ACM BuildSys (in conjunction with

ACM SenSys), Berkeley, CA, USA, November 2009

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 14

Wireless Sensor Network Design

2D Representation for design tool IFC model or AutoCAD

WSN Design Tool

Throughput Prediction Channel selection Signal Level Noise Levels

Design Optimisation Output 3D Output Visualisation

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 15

Design Case Study

Experienced Designer Novice Designer WSAN Design Tool

€ € € € € €

53%Sensor Traffic 47%Routing Traffic 78%Sensor Traffic 22%Routing Traffic 71%Sensor Traffic 29%Routing Traffic

Sensing Data Delivery Ratio Data transmission cost (# packets) Design cost Cost Savings Design Time Comments Novice Designer 97.0 % 1.85 € 3300 € 0 4 h No previous WSN design experience, follows EnOcean Range Planning Guide Experienced Designer 97.6 % 1.21 € 2940 € 360 30 min WSN Design Expert, Sun SPOT developer WSAN Design Tool 98.2 % 1.46 € 2620 € 680 40 min WSAN Design Tool 3 Gateways 5 Repeaters 3 hops max 3 Gateways 1 Repeater 3 hops max 2 Gateways 2 Repeaters 2 hops max

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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 16

Road Ahead

  • Need to develop concepts for holistic energy

management concepts across all protocol layers and sensing/control applications for large scale WSANs

  • Design and optimisation methodologies and

tools to support better WSAN design considering network and application requirements

  • More effective management and diagnostics of

WSAN to support long term energy efficient

  • peration
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Dr Dirk Pesch CHIST-ERA Conference, 5th September 2011 17

Acknowledgements

  • Financial Support

– Science Foundation Ireland and Irish Higher Education Authority

  • Colleagues in Nimbus Centre @ CIT
  • ITOBO and NEMBES project Colleagues

Dr Dirk Pesch Nimbus Centre for Embedded Systems Research Cork Institute of Technology dirk.pesch@cit.ie