Presenting a new routing protocol to improve energy consumption and congestion control in MANET communication networks using fuzzy logic

Document Type : Original Article

Authors

1 Department of Computer Engineering, Faculty of Engineering, Higher Educational Complex of Saravan,

2 Faculty of Engineering, Velayat University, Iranshahr

Abstract

With the advancement of wireless communication technology, MANET networks have attracted a lot of attention due to the improvement of flexibility and cost reduction. Mobile stations in a MANET are constantly moving, so a routing protocol needs to be implemented to cope with these changes. Designing such protocols usually brings special challenges and problems. One of these challenges is the possibility of congestion due to the high rate of sending information to the destination node and also the high energy consumption of the nodes. Congestion causes loss of information and waste of energy in nodes. Accordingly, in this article, in order to control congestion, a new method based on fuzzy logic is proposed. In the proposed protocol, fuzzy logic detects, announces and controls congestion by using three parameters of queue buffer length, node mobility speed and available bandwidth as inputs. By simulating the proposed method and comparing it with the CBP protocol, it can be seen that the proposed protocol has a much better performance than CBP for congestion control.

Keywords


[1]    Camp, T., Boleng, J., & Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless communications and mobile computing, 2(5), 483-502.
 
[2]    Castellanos, W. E., Guerri, J. C., & Arce, P. (2016). A QoS-aware routing protocol with adaptive feedback scheme for video streaming for mobile networks. Computer Communications, 77, 10-25.
 
[3]     Sarkar, S., & Datta, R. (2016). A secure and energy-efficient stochastic multipath routing for self-organized mobile ad hoc networks. Ad Hoc Networks, 37, 209-227.
 
[4]    Budyal, V. R., & Manvi, S. S. (2014). ANFIS and agent based bandwidth and delay aware anycast routing in mobile ad hoc networks. Journal of Network and Computer Applications, 39, 140-151.
 
[5]    Chatterjee, S., & Das, S. (2015). Ant colony optimization based enhanced dynamic source routing algorithm for mobile Ad-hoc network. Information Sciences, 295, 67-90.
 
[6]    Chettibi, S., & Chikhi, S. (2016). Dynamic fuzzy logic and reinforcement learning for adaptive energy efficient routing in mobile ad-hoc networks. Applied Soft Computing, 38, 321-328.
 
[7]     Basurra, S. S., De Vos, M., Padget, J., Ji, Y., Lewis, T., & Armour, S. (2015). Energy efficient zone based routing protocol for MANETs. Ad Hoc Networks, 25, 16-37.
 
[8]    Kumar, C. N., & Satyanarayana, N. (2015). Multipath QoS routing for traffic splitting in MANETs. Procedia Computer Science, 48, 414-426.
 
[9]    Rhaiem, O. B., Fourati, L. C., & Ajib, W. (2016). Network coding-based approach for efficient video streaming over MANET. Computer Networks, 103, 84-100.
 
[10] Safa, H., Karam, M., & Moussa, B. (2014). PHAODV: Power aware heterogeneous routing protocol for MANETs. Journal of Network and Computer Applications, 46, 60-71.
 
[11]   Muchtar, F., Abdullah, A. H., Al-Adhaileh, M., & Zamli, K. Z. (2020). Energy conservation strategies in Named Data Networking based MANET using congestion control: A review. Journal of Network and Computer Applications, 152, 102511
 
[12]  Anshul, S., Kashif, M., Rohit Reddy, P. B., Ashwin, U., & Arshad, K. (2020). Erratum regarding missing Declaration of Competing Interest statements in previously published articles. Journal of clinical orthopaedics and trauma, 11(6), 1177.
 
[13]  Farheen, N. S., & Jain, A. (2020). Improved routing in MANET with optimized multi path routing fine tuned with hybrid modeling. Journal of King Saud University-Computer and Information Sciences.
 
[14]  Khan, A. F., & Rajalakshmi, C. N. (2022). A multi-attribute based trusted routing for embedded devices in MANET-IoT. Microprocessors and Microsystems, 89, 104446.
 
[15]   Danilchenko, K., Azoulay, R., Reches, S., & Haddad, Y. (2022). Deep learning method for delay minimization in MANET. ICT Express, 8(1), 7-10.
 
[16] Perkins, C. E. (2003). Ad hoc ondemand distance vector (AODV) routing. RFC, 3561.
 
[17] Ghasemnezhad, S., & Ghaffari, A. (2018). Fuzzy logic based reliable and real-time routing protocol for mobile ad hoc networks. Wireless Personal Communications, 98(1), 593-611.
 
[18]   Tabatabaei, S., & Nosrati Nahook, H. (2020). A new routing protocol in MANET using Cuckoo optimization algorithm. Journal of Electrical and Computer Engineering Innovations (JECEI), 9(1), 75-82.