xenofon“fontas” fafoutis · 2011-04-14 · xenofon“fontas” fafoutis. 2 dtu informatics,...

Wireless Sensor Networks

Xenofon “Fontas” Fafoutis

14/04/2011Wireless Sensor Networks2 DTU Informatics, Technical University of Denmark

Sensors


Wireless Sensor Networks

Sink

Sensor

Sensed Area


Outline

• Wireless Sensor Networks

–Types and Topologies

–Applications

–System Issues and Standards

• Energy Harvesting

• Networking Challenges

• Open Research Problems


Types of Nodes

Sensor

–Low resources

–Inexpensive

–Energy constraints• Main challenge!!

Sink

–High resources

–AC power supply

–Internet connection (typically)

Typically traffic is generated by the sensors and it is directed to the sink


Unstructured vs. Structured

Unstructured

–Dense

–Ad hoc

Structured

–Fewer sensors

–Strategic positions

Forest Railway


Topologies

Multi-sink

–Increased cost

–Increased performance

–Reliability

Mobile sinks

–Move and gather data


Topologies: Single- vs. Multi-Hop

Single-Hop

–Short coverage

–Less challenging

–Higher deployment costs per m2

Multi-Hop

–Large Coverage

–Challenging


Topologies: Wireless Mesh Network

Very large sensed areas

–Wireless links of several hundreds of meters

Sink w/o Internet Connection

Central Station w/ Internet Connection


Outline



–Applications






Application Types

• Monitoring

– Environmental, industrial and health monitoring

– Factory and process automation

– Logistics storage support

• Tracking

– Tracking objects, animals, people and vehicles

– Military, business, public transportation networks


Traffic Classification

• Continuous

– Mainly on monitoring applications

– Predictable and static

• Event-Driven

– Mainly on tracking applications

– Threshold alerts

– Unpredictable triggering

• Request-Reply

– Predictable triggering

• Hybrid


Application Requirements

• End-to-end delay

– Tracking, alerting applications

• Reliability

– Long-term monitoring for off-line analysis

• Main trade-off / challenge of WSNs

– Application requirements vs. Energy constraints

Can you name some applications?


Typical applications

• Environmental monitoring

– Indoor environment control: light, temperature, status of windows and doors, indoor air pollution

– Great Duck Island: Sense the environment that birds live (temperature, pressure, humidity)

• Military applications

– A line in the Sand: Sensors that can detect metallic objects, tracking and classifying moving objects

• Support for logistics

– Storage management of barrels by BP: Detect incompatibilities in storage that may lead to explosions

• Human-centric applications

– Support for senior citizens: Identify behaviors, indicate early stages of disorders, recording if they are taking medication and detect emergencies

• Other

– Six-sensor glove: Movement and gesture recognition


Outline



–Applications






Operating System and Standards

• Standards for Low-Rate Wireless Personal Networks (LR-WPN)

– IEEE 802.15.4

• Defines the PHY and MAC layers

– Zigbee

• Defines the NET and APP layers

• TinyOS

– A tiny operating system designed for sensor networks


Challenges: Localization

Localization

– The problem of determining a node’s position

• Challenging in unstructured topologies

– Important for applications, routing protocols (e.g. geographic routing)

– Straightforward solution: GPS

• But, requires line of sight to satellites, consumes energy, increases cost

– Alternative estimation approaches

• E.g. Received Signal Strength Indicator (RSSI) methods


Challenges: Synchronization

Synchronization

– The problem of assuring that different nodes have a common notion of time

– Important for applications (correlating data) and networking protocols (time scheduling, coordinated duty cycles)

– Known problem of distributed systems

• Typical solutions are unsuitable due to the limited resources


Challenges: Security

Security

– The problem of protecting sensed data and resources from attacks and misbehaviors

– Attacks classification

• On secrecy and authentication

– Confidentiality, authorization, authentication

• On availability

– Denial-of-Service (DoS) attacks

• On service integrity

– False data values from compromised nodes


Outline



–Applications






Energy Harvesting

• Battery-based WSNs

– Sacrifice performance for lower energy consumption

– Eventually will die and need battery replacement

• Often not even possible (e.g. underground sensors)

• Energy-Harvesting WSNs

– Extracting energy from the environment

– Infinite lifetime but energy not always available

• Energy sources have spatiotemporal variations

– Batteries operate as energy buffers


Classification of Energy Availability

• Uncontrollable but predictable

– E.g. Solar energy

• Uncontrollable and unpredictable

– E.g. Vibrations in an indoor environment

• Fully controllable

– E.g. Flush-lights used to generate energy

• Partially controllable

– E.g. A deployed energy source

Can you name some energy harvesting sources?


Energy Sources

• Electromagnetic radiation

– Solar power

– Ambient indoor light

• Thermal energy

– Room radiator

– Machines

– Body temperature

• Mechanical energy

– Wind power, air currents

– Water flows in natural channels (e.g. rivers) or in pipes

– Blood flow and breathing

– Vibrations

• Acoustic noise

– High noise levels (e.g. concerts)


Design Principles

Battery-Based WSNs• Maximize the lifetime while maintaining a minimum performance

• Save as much energy as possible

• Distribute the tasks and computation load as much as possible

Energy-Harvesting WSNs• Maximize performance while maintaining energetic sustainability

• Use the available harvested energy

• Use the nodes that have access to more energy to cover for nodes that they don’t to


Outline



–Applications






Transmission Power

• The power of the signal transmission

•Directly affects the transmission range

– Number of neighbors

•Main energy consumption factor

– The relation of transmission power and range is not linear!

• Transmission Power policies

– Static Approaches

– Adaptation Algorithms


Transmission Power Trade-off

��

��

Power of received signal

Constant Distance

Transmission Power

Path loss exponent typically in [2-4]

In order to maintain the same received signal strength over the half distance we need 2�times less transmission power!

Transmission range

R/2RThe number of neighbors are decreased. Hence, the delay to reach the sink is increased.


Duty Cycles

• Time division into active and sleeping periods

– Energy conservation in battery-based WSNs

– Energy neutral operation in EH-WSNs

• Energy consumption equal to harvested energy

– Introduce additional delay: sleeping delay

• Duty cycle algorithms

– Synchronized duty cycles

• Used in battery-based WSNs

• Same duty cycle for all sensors in an area

– Individual duty cycles


Individual Duty Cycles

• Important for EH-WSNs because of

– Different energy harvesting rates

• Transmitters and receivers need to be awake at the same time

– Straightforward for single-hop topologies

• The receiver (sink) is always awake

– Challenging for multi-hop topologies

• Energy wasted listening for the receiver to wake up


Routing

• The problem of selecting the optimum path from the source to the sink

– Objectives: performance and energy conservation

• Is the shortest path always the best solution?

– No!

Path A

Path B

Path B is the shortest path but is it the best solution when:• The batteries of Path A nodes are fuller?• The nodes of Path A can harvest more energy?• The conditions on Path B are bad (many retransmissions)?• …


Routing Metrics

• Cost functions that evaluate a link or a path

– The lower the better

• Factors that routing metrics shall consider

– Shortest path

– Transmission power requirements

– Energy profile (residual battery, harvesting rate)

– Channel conditions

– Duty cycles

– Traffic load (for load balancing)

The importance of each factor is different for different objectives


Outline



–Applications






Some Open Research Problems

• Transmission Power Assignment for EH-WSNs

• Routing metrics for EH-WSNs

• Load distribution for EH-WSNs

• …


Transmission Power Assignment for EH-WSNs

• Problem: Assign the transmission power of each sensor considering the fact that each node has a unique energy profile (residual battery, harvesting rate)

• Objective: Energetically capable sensors can cover for less capable

• Example scenario:

As the shadow moves, the energy harvesting rate of each node changes. Capable sensors can increase their power consumption to help the incapable sensor regenerate.


Routing metrics for EH-WSNs

• Problem: Design a routing algorithm / cost function that evaluates and select the optimum path for EH-WSNs.

• Approach: Different factors affect differently the performance and the energetic sustainability. The importance of each factor needs to be evaluated.


• Which path minimizes the delays?• Which path contributes more to the

energetic sustainability of the network?

• Path A where shadows and keep the harvesting rate low?

• Or Path B where an obstacle creates a lots of channel errors and, thus, needs many retransmissions?

Path A

Path B


Load distribution for EH-WSNs

• Problem: Distribute the sensing between sensors with different energy profiles.


Assuming that the sink is interesting in only 1 value per period for the red circle area. How shall this energetically consuming task should be distributed among the sensors?


Thanks

• What’s next?

– Questions / Clarifications

– Exercises

xenofon“fontas” fafoutis · 2011-04-14 · xenofon“fontas” fafoutis. 2 dtu informatics,...

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