Abstract
This paper presents a fuzzy logic-based adaptive communication management on a wireless network. A combination of both wireless network and handheld device is most widely used in the world today. The wireless network depends on the radio signal to communicate with the device. And the handheld device is the mobile node, which is difficult to determine the certain location. These unstable features have a negative influence on the communication QoS (quality of service). Therefore, we adopt the fuzzy logic to improve the communication efficiency. The access point (AP) may evaluate the communication state with the fuzzy logic. Through this, the relay station utilizes the evaluation result to handle the communication throughput. The simulation demonstrates the efficiency of our proposed model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Raychaudhuri, D., Mandayam, N.B.: Frontiers of wireless and mobile communications. Proceedings of the IEEE 100(4), 824–840 (2012)
Avestimehr, A.S., Diggavi, S.N., Tse, D.N.: Wireless network information flow: A deterministic approach. IEEE Transactions on Information Theory 57(4), 1872–1905 (2011)
Shin, K., Kim, J., Choi, S.B.: Loss recovery scheme for TCP using MAC MIB over wireless access networks. IEEE Communications Letters 15(10), 1059–1061 (2011)
Maisuria, J.V., Patel, R.M.: Overview of Techniques for Improving QoS of TCP over Wireless Links. In: 2012 International Conference on Communication Systems and Network Technologies (CSNT), pp. 366–370. IEEE (2012)
Nguyen, T.H., Park, M., Youn, Y., Jung, S.: An improvement of TCP performance over wireless networks. In: 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 214–219. IEEE (2013)
Tiyyagura, S., Nutangi, R., Reddy, P.C.: An improved snoop for TCP Reno and TCP sack in wired-cum-wireless networks. Ind. J. Comput. Sci. Eng. 2, 455–460 (2011)
Rajasekaran, S., Pai, G.V.: Neural networks, Fuzzy logic and Genetic algorithms. PHI Learning Private Limited (2011)
Lee, C.C.: Fuzzy Logic in Control Systems: Fuzzy Logic Controller. IEEE Trans. Systems, Man and Cybernetics 20, 404–435 (1990)
Zeigler, B., Moon, Y., Kim, D., Ball, G.: The DEVS environment for high performance modeling and simulation, Computational Science and Engineering. IEEE CS&E, 61–71 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Kim, T., Han, Y., Kim, J., Lee, J. (2014). Fuzzy Logic-Based Adaptive Communication Management on Wireless Network. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-11289-3_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11288-6
Online ISBN: 978-3-319-11289-3
eBook Packages: Computer ScienceComputer Science (R0)