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Abstract

Wireless sensor networks (WSNs), with self-organizing and high fault tolerant characteristics, have great advantages for target tracking. But the sensor nodes are battery powered and in most of the cases, it is impossible to charge or replace batteries. Therefore, energy efficiency to extende the life of the network has become an important design criterion for wireless sensor networks. At the same time, high communication speed is also an important issue in the target tracking application. In order to overcome these problems, we propose a novel fuzzy logic model which provides high communication speed to fulfil the tracking task of wireless sensor networks. The proposed algorithm is evaluated in MATLAB. The results show that the our algorithm performs better than the other algorithms in terms of data transmission rate and system lifetime.

Keywords

Wireless sensor networks fuzzy logic target tracking high speed data transmission

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References

Kulkarni

R.V.

, Forster

and Venayagamoorthy

G.K.

, Computational intelligence in wireless sensor networks: A survey, IEEE Commun Surv Tutor13(1) (2011), 68–96.

and Qin

, A dynamic neural network approach for solving nonlinear inequal-ities defined on a graph and its application to distributed, routing free, range free localization of WSNs, Neurocomputing117 (2013), 72–80.

Attea

B.A.

and Khalil

E.A.

, A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks, Appl Soft Comput12(7) (2012), 1950–1957.

Bagci

and Yazici

, An energy aware fuzzy approach to unequal clustering in wireless sensor networks, Appl Soft Comput13(4) (2013), 1741–1749.

Kuila

, Gupta

S.K.

and Jana

P.K.

, A novel evolutionary approach for load balanced clustering problem for wireless sensor networks, Swarm and Evolutionary Computation12 (2013), 48–56.

Lee

J.-S.

and Cheng

W.-L.

, Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication, IEEE Sensors Journal12(9) (2012), 2891–2897.

Jiang

, Sun

and Xu

, Fuzzy-logic based energy optimized routing for wireless sensor networks, Int J Distrib Sens Netw (2013), 8–17.

Han

, Luo

, Liu

and Vasilakos

A.V.

, Algorithm design for data communications in duty-cycled wireless sensor networks: A survey, IEEE Communications Magazine5(7) (2013), 107–113.

Yao

, Cao

and Vasilakos

A.V.

, EDAL: An energy efficient, delay-aware, and lifetime-balancing data collection protocol for heterogeneous wireless sensor networks, IEEE/ACM Transactions on Networking23(3) (2015), 810–823.

10.

Xiao

and Xu

, Reliable and energy efficient communication algorithm in hierarchical wireless sensor networks, Wireless Personal Communications (2016). doi: 10.1007/s11277-016-3705-y.

11.

Lee

J.S.

, Member

and Cheng

W.L.

, Fuzzy-logic-based clustering approach for energy predication, IEEE Sensors Journal12(9) (2012), 2891–2897.

12.

Caraballo

, Herrera-Cobos

and Marin-Rubio

, An iterative method for non-autonomous nonlocal reaction-diffusion equations, 2(1) (2017), 73–82. doi: 10.21042.

13.

Zhou

, Xu

and Xu

, A sufficient condition for the existence of a k-factor excluding a given r-factor, Applied Mathematics and Nonlinear Sciences2(1) (2017), 13–20. doi: 10.21042.

14.

Troubleyn

, Moerman

and Demeester

, QoS challenges in wireless sensor networked robotics, Wireless Personal Communications70(3) (2013), 1059–1075.

15.

Ferng

H.W.

, Tendean

and Kurniawan

, Energy-efficient routing protocol for wireless sensor networks with static clustering and dynamic structure, Wireless Personal Communications65(2) (2012), 347–367.

Fuzzy logic based high speed data transmission algorithm of sensor networks for target tracking

Abstract

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References