Localization and Clustering in Scalable WSN

8/3/2019 Localization and Clustering in Scalable WSN

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Localization and

Clustering in scalableWSNEnvironmental Monitoring network with mobile nodes



Federated

Secure SensorNetwork

(currently in

development by

Cambridge

university) [1]

With FRESNEL they aim tobuild a large scale federated

sensor network framework

with multiple applications

sharing the same resources.

They want to guarantee a

reliable intra-applicationcommunication as well as a

scalable and distributed

management infrastructure.

Orthogonally, privacy and

application security should

also be maintained.



A

Survey of Mobile Phone

Sensing

[2]

Presents of a survey done in the

field of using mobile phone as a

monitoring system.

He believes that sensor equipped

mobile phones will revolutionize

many sectors of our economy,

including business, healthcare,

social networks, environmental

monitoring, and transportation.



A Biologically

Inspired

Networking

Model

for Wireless

Sensor

Networks [3]

proposes an energy-efficient topology

management model inspired by

biological intercell signalling schemes,

which allows sensor nodes to form

clusters around imminent targets in a

purely distributed and autonomous

fashion. In particular, nodes in the target

vicinity collaborate to form a cluster

according to their relative observation

quality values, based on a bioinspired

lateral induction process



Federated

Secure Sensor

Network(currently in

development by

Cambridge

university)

A Survey of

Mobile Phone

Sensing[1]

A Biologically

Inspired

Networking

Model

for Wireless

Sensor

Networks [3]

Mobile Sensor

network using

wearable sensor

(we are here)



Mobile Sensor

network using

wearable sensor

?Health care

[5]

Crowd

management

[4]

Possible applications



What will we do?

Suggest (and implement) a protocol that

guarantee localization and clustering asnodes moves.



Clusters are changing as nodes move

depending on the event to be detected

and the available no. of nodes



Where is novelty?

Most paper suggests protocols for

fixed nodes with/without mobile anchors

We will propose the situation with are

mobile nodes with/without fixed anchors.



How do we know that no one

did it before? I have checked libraries, journals, websites ,

Current papers [6,7,8 ]suggest developing their

algorithms to incorporate mobile nodes as future

works.



What will we not do?

We will not address the heterogeneity in

nodes platform (assume all nodes are of

the same type)

We will not address software application

that needed to interface different nodes

(No cloud computing)

However data management (collecting) will

be carried out.



How will we do it?

Through simulation

MATLAB : will be used though it is not the best

for network simulation, but fast result could be

verify the system feasibility

Through implementation

Microcontroller currently available in the

school labs will be adequate platform todevelop



What results are expected?

Ability of a WSN with mobile nodes to collect

data from some environment and deliver it to a

base station as soon as possible.



How do we validate results?

We will Compare results with anotherWSN involve fixed nodes (considered as

the optimum state).



Where to start?

Three recent PhD theses (across British universities)that are deal with localization and clustering areselected.

1. Author [6] develops a protocol for EnergyOptimization Algorithm for mobile Wireless SensorNetworks

2. Author [7] develops An adaptive clustering

protocol.

3. Author [8] explores the deployment of WirelessSensor Networks (WSNs) on localised maritimeevents.



References

1. http://www.cl.cam.ac.uk/research/srg/netos/fresnel

2. N. D. Lane, E. Miluzzo, H. Lu, D. Peebles, T. Choudhury, and A. T. Campbell, "A survey of mobile phone sensing," IEEE CommunicationsMagazine, vol. 48, pp. 140-150, 2010.

3. C. Charalambous and C. Shuguang, "A biologically inspired networking model forwireless sensor networks,"Network, IEEE, vol. 24, pp. 6-13, 2010.

4. E. T.-H. Chu, Y.-L. Chen, J. W. S. Liu and J. K. Zao Strategies for Crowdsourcing forDisaster Situation Information, WIT Transactions on the Built Environment 119, pp.

257-269.5. An agent-based signal processing in-node environment for real-time human activity

monitoring based on wireless body sensor networks

6. M., Al-Obaidi, ENAMS: Energy Optimization Algorithm for Mobile Wireless SensorNetworks using Evolutionary Computation and Swarm Intelligence, PhD thesis DeMontfort University, September 2010

7. F., Bajaber, Performance Analysis of Cluster Based Communication Protocols forEnergy Efficient Wireless Sensor Networks , PhD thesis, School of Computing,

InformaticsandM

edia, University of B

radford, 20108. P., Barbosa, Scalable Wireless Sensor Networks for Dynamic Communication

Environments: Simulation and Modelling, PhD thesis, School of Electronics andComputer Science, UNIVERSITY OF SOUTHAMPTON, 2011.





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Localization and Clustering in Scalable WSN