Flexible congestion control using fuzzy logic for Wireless Sensor Networks
DOI:
https://doi.org/10.26438/ijcse/v6i5.492499Keywords:
Congestion Control Technique, Delay Ratio, Dropping Rate, Flexible, Fuzzy Logic System, Neighbors, Type-2 Fuzzy logicAbstract
In WSNs, congestion seems to be an unpredictable stage caused by the packets collision and the overloaded network. The main reason of overloading is the neighboring nodes. In large networks, mainly neighbor nodes behave smartly to grasp the large amount of bandwidth in advance for packet transmission. The affect of low bandwidth causes the problem of packet delay and dropping rate. Both network and transport layer share the responsibility to control the congestion. To achieve these objectives, Flexible congestion control scheme (FCCFA) is proposed. FCCFA uses the closed loop congestion control technique to control the traffic rate accordingly by using three parameters. The Type-2 Fuzzy Logic System is used to estimates the adjustment rate to handle the uncertainty of data. Implicit notification system is used to notify the immediate nodes without wasting any energy. The simulated results give the proof of our promises and improvements.
References
Yeduri Sreenivasa Reddy, K. K. Pattanaik, “A Reply Cache Mechanism to Reduce Query Latency of WSNs in IoT Sensory Enviornment” 2016 IEEE International Symposium on Nanoelectronic and Information System, pp 19-21, Dec 2016, Gwalior , India.
Sonmez et al: “Fuzzy Based Congestion Control for Wireless Multimedia Sensor Network” , EURASIP journal on Wireless Communications and Networking , 2014:63 , Istanbul ,Turkey.
Ghaffari A. “Congestion Control Mechanisms in Wireless Sensor Networks: A Survey”, Journal of Network and Computer Applications 2015, Tabriz , Iran.
Dharmendera Singh , Neeraj Singh kushwaha , Sachin Kumar, “ Fast AIMD: A Fairness Based Congestion Control Approach for TCP Networks”, International Conference on Computing Communication and Automation 2015.
Hrvoja Kozacinski, Peter Knezevid, “An Approach using Simulation Techniques to Estimate Quality of Service Parameter in Communication Networks”, MIPRO Opatiya, Croatic, 26-30, May 2014.
K M Archana Patel , Richa Martolia, “Congestion Control Techniquesin Networking”, International Conference on Communication and Signal Processing 2016, India.
Majid Hatamian, Hamid Barati , “Priority based Congestion Control Mechnism for Wireless Sensor Networks using Fuzzy Logic”, IEEE Journal on ICCCNT 2015, July , 13-15, 2015, Denton , U.S.A.
Sara Ghanavati, Jemal Abawajy and Davood Izadi, “A Congestion Control Scheme Based on Fuzzy Logic in Wireless Body Area Networks”, IEEE- International Symposium on Network Computing and Applications 2015.
O. B. Akan, I.F. Akyidiz, “ESRT: Event to Sink Reliable Transport in Wireless Sensor Networks” , IEEE Transactions on Networking 2005.
Saad A. Munir, Yu Wen Bin, Ren Biao, Ma Jian, “Fuzzy Logic Based Congestion Estimation for QoS” , Wireless Communications and Networking conference 2007, Kowloon, China.
Saurabh Jaiswal, Anamika Yadav, “Fuzzy Based Adaptive Congestion Control in Wireless Sensor Networks”, IEEE 2013, Raipur , India.
Arpita Chakroborty, Srinjoy Ganguly, Mrinal Kanti Naskar, Anupam Karmakar, “A Trust Based Fuzzy Algorithm for Congestion Control in Wireless Multimedia Sensor Networks”, Journal of IEEE 2013, Kolkata, India.
Rakha Chakravarthi, C Gomathy, “IFCCDC: A Fuzzy control based Congestion Detection and Control in Wireless Sensor Networks”, International Journal of Computer Applications, 12-17, June 2012.
Roxanne Hawi, George Okayo, Michael kimwale, “ Smart Traffic Light Control using Fuzzy Logic and Wireless Sensor Networks”, IEEE 2017, 18-20 , July , London, UK.
C. Chrysostomou , K. Tatas and A.R. Runcan, “A Dynamic Fuzzy logic based Routing Scheme for Bufferless NoCs”, IEEE 2012, Nicosia , Cyprus.
Rekha Chakravarthi, “A Fuzzy Approach to Detect and Control Congestion in Wireless Sensor Networks”, IJCSE, Chennai, India.
Hemba S, Islam N, “Fuzzy Logic: A Review”, IJCSE, Guwahati, India.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
