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Abstract

Wireless Nano Sensor Network (WNSN) consists of nano-scale devices with potential sensing capabilities in advanced applications. The most notable characteristic of these networks is the use of very high operating frequencies (0.1-10 THz) for communication among nano-machines. In addition, the extreme limitations of nano-devices motivate the design of novel and simple protocols for overcoming the restrictions and improving the network performance. This paper introduces a fuzzy logic-based mobility management (FLMM) solution for mobile cluster-based WNSNs founded on TDMA MAC protocol. This method aids mobile nano sensor nodes to optimally handoff among static anchor nodes named nano-controllers, so that, the handoff decision is triggered based on a combination of three important local parameters “distance from nano-controller”, “residual energy of nano-controller” and “traffic load of nano-controller”. The proposed model is evaluated in comparison to a similar non-fuzzy distance-based mobility controller. To this end, several critical metrics such as energy consumption, packet loss ratio, successful handoff rate and average end-to-end delay have been studied using NS-3 simulator and the results of performance evaluation show that proposed fuzzy logic-based mobility controller provides more reliability, less delivery delay and lower energy consumption in a dynamic topology of limited WNSN.

Keywords

Wireless Nano Sensor Network (WNSN)mobility management fuzzy logic handoff control NS-3

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References

Kandel

and Langholz

, Fuzzy Hardware: Architectures and Applications, Chap.7, Edn.3, Springer 2012.

Piro

, Grieco

L.A.

, Boggia

, et al., Nano-sim: Simulating electromagnetic-based nanonetworks in the network simulator 3, Proceedings of the 6th International ICST Conference on Simulation Tools and Techniques, Brussels, Belgium, 2013, 203–210. Doi: 10.4108/simutools.2013.251699

Piro

, Grieco

L.A.

, Boggia

, et al., Simulating wireless nano sensor networks in the ns-3 platform, 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA), Barcelona, Espain 2013, pp. 67–74. Doi: 10.1109/WAINA.2013.20

Fotouhi

, Alves

, Kouba

, et al., On a reliable handoff procedure for supporting mobility in wireless sensor networks, 9th International Workshop on Real-Time Networks (RTN), Brussels, Belgium 2010.

Akyildiz

I.F.

, Brunetti

and Blazquez

, Nanonetworks: A new communication paradigm, Computer Networks (Elsevier) Journal 52(12) (2008), 2260–2279. Doi: 10.1016/j.comnet.2008.04.001

Akyildiz

I.F.

and Jornet

J.M.

, Electromagnetic wireless nanosensor networks, Nano Communication Networks (Elsevier) Journal 1(1) (2010), 3–19. Doi: 10.1016/j.nancom.2010.04.001

Giarratano

J.C.

and Riley

, Expert Systems: Principles and Programming, 4 edn., Course Technology, 2004.

Jornet

J.M.

and Akyildiz

I.F.

, Channel modeling and capacity analysis for electromagnetic wireless nanonetworks in the terahertz band, IEEE Transactions on Wireless Communications 10(10) (2011), 3211–3221. Doi: 10.1109/TWC.2011.081011.100545

Jornet

J.M.

and Akyildiz

I.F.

, Femtosecond-long pulse-based modulation for terahertz band communication in nanonetworks, IEEE Transactions on Communications 62(5) (2014), 1742–1754. Doi: 10.1109/TCOMM.2014.033014.130403

10.

Jornet

J.M.

and Akyildiz

I.F.

, Information capacity of pulsebased wireless nanosensor networks, 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), Salt Lake City, USA 2011, pp. 80–88. Doi: 10.1109/SAHCN.2011.5984951

11.

Jornet

J.M.

and Akyildiz

I.F.

, Joint energy harvesting and communication analysis for perpetual wireless nanosensor networks in the terahertz band, IEEE Transactions on Nanotechnology 11(3) (2012), 570–580. Doi: 10.1109/TNANO.2012.2186313

12.

Jornet

J.M.

, Pujol

J.C.

and Paret

J.S.

, Phlame: A physical layer aware mac protocol for electromagnetic nanonetworks in the terahertz band, Nano Communication Networks (Elsevier) Journal 3(1) (2012), 74–81. Doi: 10.1016/j.nancom.2012.01.006

13.

Kim

J.M.

, Park

S.H.

, Han

Y.J.

, et al., Chef: Cluster head election mechanism using fuzzy logic in wireless sensor networks, 10th International Conference on Advanced Communication Technology (ICACT), Gangwon-Do, South Korea 2008, pp. 654–659. Doi: 10.1109/ICACT.2008.4493846

14.

Tanaka

, An Introduction to Fuzzy Logic for Practical Applications, Springer-Verlag: New York, 1996.

15.

Kasabo

, Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering, MIT Press, Cambridge: London, England, 1996.

16.

Azad

and Sharma

, Cluster head selection in wireless sensor networks under fuzzy environment, International Scholarly Research Notices (2013). doi: 10.1155/2013-909086

17.

Wang

, Jornet

J.M.

, Malik

M.G.A.

, et al., Energy and spectrum-aware MAC protocol for perpetual wireless nanosensor networks in the Terahertz Band, Nano Communication Networks (Elsevier) Journal 11(1) (2013), 2541–2555. Doi: 10.1016/j.adhoc.2013.07.002

18.

Fuller

, Introduction to Neuro-Fuzzy Systems, Springer Science and Business Media, 2013.

19.

Rovatti

and Borgatti

, Maximum-throughput implementation of piecewise-linear fuzzy systems, Proceedings of the Sixth IEEE International Conference on Fuzzy Systems 2 (1997), 767–772. Doi: 10.1109/FUZZY.1997.622807

20.

Cho

and Hayes

J.P.

, Impact of mobility on connection stability in ad hoc networks, IEEE Wireless Communications and Networking Conference (WCNC), New Orleans, USA 2005, 1650–1656. Doi: 10.1109/WCNC.2005.1424761

21.

Gajjar

, Sarkar

and Dasgupta

, Cluster head selection protocol using fuzzy logic for wireless sensor networks, International Journal of Computer Applications 97(7) (2014), 38–43. Doi: 10.5120/17022-7310

22.

Pal

S.K.

and Mandal

, Fuzzy logic and approximate reasoning: An overview, Journal of the Institution of Electronics and Telecommunication Engineers 97(5-6) (1991), 548–560.

23.

Haider

and Yusuf

, A fuzzy approach to energy optimized routing for wireless sensor networks, The International Arab Journal of Information Technology April 6(2) (2009), 179–185.

24.

Srikanth

, Chaluvadi

and Sandeep , et al., Energy efficient, scalable and reliable mac protocol for electromagnetic communication among nano devices, International Journal of Distributed and Parallel Systems (IJDPS) 3(1) (2012), 249–256.

25.

Zhang

, Handover Decision Using Fuzzy MADM in Heterogeneous Networks, IEEE Wireless Communications and Networking (WCNC) Conference, 2, 2004, pp. 653–658. Doi: 10.1109/WCNC.2004.1311263

26.

Kim

Y.H.

, Ahn

S.C.

and Kwon

W.H.

, Computational complexity of general fuzzy logic control and its simplification for a loop controller, Fuzzy Sets and Systems (Elsevier) Journal 111(2) (1997), 215–224. Doi: 10.1016/S0165-0114(97)00409-0

27.

Zinonos

, Chrysostomou

and Vassiliou

, Mobility management in wsns using fuzzy logic: An industrial application scenario, 8th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS), Hangzhou, China, 2012, pp. 284–286. Doi: 10.1109/DCOSS.2012.51

28.

Zinonos

, Chrysostomou

and Vassiliou

, Wireless sensor networks mobility management using fuzzy logic, Ad Hoc Networks (Elsevier) Journal 16 (2014), 70–87. Doi: 10.1016/j.adhoc.2013.12.003

29.

A look at the performance offered by the VIA Nano E-C4650-Based on the 28nm Isaiah architecture from VIA. http://wccftech.com/via-28nm-c4650-x86-quad-coreprocessor-benchmarks. Accessed 28 November, 2015.

Mobility management in wireless nano-sensor networks using fuzzy logic

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