Autonomic Wireless Sensor Networks: Intelligent Ubiquitous Sensing

G.M.P. O’Hare, M.J. O’Grady, A. Ruzzelli, R. TynanAdaptive Information Cluster (AIC) Group, University College Dublin, Ireland.

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)

• A large number of tiny wireless devices to sense the environment: – Sensor nodes Sensing unit

(temp,pressure, vibration, sound, etc.)

Small processing

unit

Short range radio unit

Small power

unit

• Few more powerful devices to collect the data:– Gateways (or sinks)

High processing unit

Wireless comm. unit High power unit

Wired comm. unit

PDA, laptop, PC etc.

Some WSN applications

• Remote area monitoring

• Object location

• Industry machinery monitoring

• Disaster prevention

• Wireless medical systems

Wind ResponseOf Golden Gate Bridge

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

Wireless sensor characteristics

• Sensors are battery operated for long unattended period: Saving energy is a primary objective

• Sensors are of :• Low cost• Low processing capability

System strength based on sensor collaboration

• Large scale networks Multihop communication

WSN manager

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

Philips sand nodes

Mica2 mote

Eyes node prototype

Tyndall sensor

General wireless sensor network architecture:

• Any layer try to achieve the task using the smallest amount of energy possible

Antenna

Sensingdevices

Application

Data interpolation

Routing

MAC

Physical

Sensing coverage

Cross layer interaction

Localization

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 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

Possible solution Multiple Notification messages (High energy consuming)

Proposed solution: Migrating agent (Moderate energy consuming)

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

• Opportunistic power management

• Intelligent coverage

• Intelligent routing

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

• 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

• 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

Antenna

Routing

MAC

Physical

Route m

anaging A

gent

table

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.

Thank you!

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