Open Access


Optimal Algorithms for Load Balancing in Optical Burst Switching Networks

K. Arun Kumar1,*, V. R. Venkatasubramani2, S. Rajaram2
1 Research Scholar, Department of ICE, Anna University, Chennai, 600 025, India
2 Department of ECE, Thiagarajar College of Engineering, Madurai, 625 015, India
* Corresponding Author: K. Arun Kumar. Email:

Computer Systems Science and Engineering 2022, 42(2), 739-749.

Received 03 February 2021; Accepted 23 August 2021; Issue published 04 January 2022


Data packet drop can happen in Optical Burst-Switched (OBS) when two data bursts are competing on the same wavelength. Recently, many techniques have been developed to solve this problem but they do not consider the congestion. Also, it is necessary to balance the load system in the OBS network. The Ant Colony Optimization (ACO) technique can be applied to determine the straight and the safest route. However, the ACO technique raises both power utilization as well as the execution time. In this study, Cuckoo Search (CS) and ACO methods based approach is proposed to avoid the congestion and load balancing in the OBS network. This strategy evaluates the intensity of hotspot data and then launches the congestion rate optimization process that depends on their load situations. The congestion rate optimization represents the available bandwidth, data distribution rate, queue size, and access rate, and also these factors are optimized through the CS technique. The fitness utility in the CS technique adjusts the distribution rate in the OBS network, and the proposed ACO technique solves the energy utilization problem. The simulation results proved that the presented strategy evades both the end-to-end delay as well as the possibility of packet drop.


Ant colony optimization; cuckoo search; optical burst-switched; load balancing; congestion control

Cite This Article

K. Arun Kumar, V. R. Venkatasubramani and S. Rajaram, "Optimal algorithms for load balancing in optical burst switching networks," Computer Systems Science and Engineering, vol. 42, no.2, pp. 739–749, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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