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Autonomic Wireless Sensor Networks: Intelligent Ubiquitous Sensing. G.M.P. O’Hare, M.J. O’Grady, A. Ruzzelli, R. Tynan. Adaptive Information Cluster (AIC) Group, University College Dublin, Ireland. Summary. Wireless Sensor networks (WSNs) Generality Prototypes Applications Requirements

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autonomic wireless sensor networks intelligent ubiquitous sensing

Autonomic Wireless Sensor Networks: Intelligent Ubiquitous Sensing

G.M.P. O’Hare, M.J. O’Grady, A. Ruzzelli, R. Tynan

Adaptive Information Cluster (AIC) Group, University College Dublin, Ireland.

summary
Summary
  • Wireless Sensor networks (WSNs)
    • Generality
    • Prototypes
    • Applications
    • Requirements
  • Autonomic computing
    • Properties
    • Autonomic WSNs
    • Agent technology in WSNs
    • Autonomic network management
      • Intelligent power management
      • Intelligent communication and routing
      • Intelligent network coverage
  • Conclusion
energy efficient wireless sensor networks wsns
Energy-Efficient Wireless Sensor Networks (WSNs)
  • A large number of tiny wireless devices to sense the environment:
    • Sensor nodes
  • Few more powerful devices to collect the data:
    • Gateways (or sinks)

PDA, laptop, PC etc.

some wsn applications
Some WSN applications

environmental data collection: temperature light, humidity, pressure, solar radiation.

Wind Response

Of Golden Gate Bridge

  • Remote area monitoring
  • Object location
  • Industry machinery monitoring
  • Disaster prevention
  • Wireless medical systems
wireless sensor characteristics
Wireless sensor characteristics

WSN manager

  • Sensors are of :
    • Low cost
    • Low processing capability
  •  System strength based on sensor collaboration
  • Large scale networks
    • Multihop communication
  • Sensors are battery operated for long unattended period:
    •  Saving energy is a primary objective
wsn issues
WSN issues
  • Large number of nodes

Scalability issues

  • High dynamic condition (number and position of nodes might change)

Network Reactivity and Self-organization

  • Power management

The network need to be connected as long as possible

  • System reliability
    • The wireless signal might be subjected to interference
  • Robustness
    • Subject to environmental variability
    • Complex interoperability of network devices
sensor node prototypes
Sensor node prototypes

Mica2 mote

Tyndall sensor

Eyes node prototype

Philips sand nodes

general wireless sensor network architecture
General wireless sensor network architecture:

Sensing

devices

Application

Data interpolation

Sensing coverage

Localization

Cross layer interaction

Routing

MAC

Physical

Antenna

  • Any layer try to achieve the task using the smallest amount of energy possible
autonomic wsns
Autonomic WSNs:
  • Origin of autonomic computing by IBM

Relieve human of the burden of managing large scale computer systems

  • Autonomic WSNs properties:
    • Self healing
    • Self protection
    • Self configuration
    • Self optimization
    • Self managing
agent technology for autonomic wsns
Agent technology for autonomic WSNs
  • Agent properties:
    • Sense-deliberate-act cycle
      • Sensing data is used as input for the decision making process
    • Mobility
      • Useful characteristic of agents that well map onto WSNs
      • Agent can migrate from one node to another processing data as it goes
    • Fault tolerance
      • Agents can still take decision if some data are missing
an example network anomaly intervention
An example: Network anomaly intervention

Possible solution Multiple Notification messages (High energy consuming)

Proposed solution: Migrating agent (Moderate energy consuming)

contribution of autonomic computing to wsns
Contribution of autonomic computing to WSNs
  • Self configuring nodes

(1) can set up a network;

(2) might not be well positioned but still work;

(3) can evaluate network gaps;

(4) can decide communication schedule.

  • Self protection attribute
    • Migrating agents check channel condition and battery level before migrating
  • Self healing
    • Repair network damage due to hash work condition
    • Negotiating new routes;
    • Activating redundant nodes;
    • Ask for replacement of damaged nodes.
  • Self optimization
    • Quality of service
    • Network efficiency
    • Delay control and data prioritization
intelligence aided sensor network
Intelligence-aided sensor network
  • Opportunistic power management
  • Intelligent coverage
  • Intelligent routing
opportunistic power management 1
Opportunistic power management (1)
  • Increase network longevity by deactivating redundant nodes: node hibernation
  • Sensing Coverage:
    • All points within the sensed area need to be covered by at least 1 sensor. Traditionally, a point is covered if it is within the sensing range of a given sensor.

Gateway

Redundant based on sensor coverage

intelligent sensing coverage
Intelligent sensing coverage
  • It deals with the quality of sensory data provided to the application which is using it;
  • Data sampling frequency at the node and surrounding nodes should be enough to have a certain detail of the phenomena of interest;
  • Migrating agents control:
    • Sensor sampling rate by tuning it;
    • Might request an increase of node density in an area
intelligent routing
Intelligent routing
  • By interacting with different layers the agent can check several parameters
  • A look-up table with neighbouring nodes parameters (RSSI, battery level, location) is provided
  • Even with incomplete data an agent can figure out the best neighbours to which to forward the data to

Routing

table

Route managing Agent

MAC

Physical

Antenna

conclusion
Conclusion
  • A methodology for the automation of the sensor network technogy has been presented;
  • WSNs offer significant potential in numerous application domains
  • Given the diverse nature of such domain, robustness and reliability is essential;
  • The method outlined exploits the integration of autonomic principles into design and operation of WSNs
  • Autonomic WSN can effectively both enhance the network reliability and extend the network lifespan.
slide18
Thank you!

www.csi.ucd.ie/research(Prism LAB web site)

www.adaptiveinformation.ie (project)

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