Vol.44, No.2, 2023, pp.1583-1600, doi:10.32604/csse.2023.027424
Fuzzy Fruit Fly Optimized Node Quality-Based Clustering Algorithm for Network Load Balancing
  • P. Rahul1,*, N. Kanthimathi1, B. Kaarthick2, M. Leeban Moses1
1 Department of Electronics and Communication Engineering, Bannari Amman Institute of Technology Sathyamangalam, 638401, India
2 Department of Electronics and Communication Engineering, Coimbatore Institute of Engineering and Technology, Coimbatore, 641109, India
* Corresponding Author: P. Rahul. Email:
Received 17 January 2022; Accepted 23 February 2022; Issue published 15 June 2022
Recently, the fundamental problem with Hybrid Mobile Ad-hoc Networks (H-MANETs) is to find a suitable and secure way of balancing the load through Internet gateways. Moreover, the selection of the gateway and overload of the network results in packet loss and Delay (DL). For optimal performance, it is important to load balance between different gateways. As a result, a stable load balancing procedure is implemented, which selects gateways based on Fuzzy Logic (FL) and increases the efficiency of the network. In this case, since gateways are selected based on the number of nodes, the Energy Consumption (EC) was high. This paper presents a novel Node Quality-based Clustering Algorithm (NQCA) based on Fuzzy-Genetic for Cluster Head and Gateway Selection (FGCHGS). This algorithm combines NQCA with the Improved Weighted Clustering Algorithm (IWCA). The NQCA algorithm divides the network into clusters based upon node priority, transmission range, and neighbour fidelity. In addition, the simulation results tend to evaluate the performance effectiveness of the FFFCHGS algorithm in terms of EC, packet loss rate (PLR), etc.
Ad-hoc load balancing; H-MANET; fuzzy logic system; genetic algorithm; node quality-based clustering algorithm; improved weighted clustering; fruit fly optimization
Cite This Article
P. Rahul, N. Kanthimathi, B. Kaarthick and M. Leeban Moses, "Fuzzy fruit fly optimized node quality-based clustering algorithm for network load balancing," Computer Systems Science and Engineering, vol. 44, no.2, pp. 1583–1600, 2023.
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