Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/175873
Title: Efficient traffic management in networks with limited resources: the switching routing strategy
Authors: Mishra, Ankit
Wen, Tao
Cheong, Kang Hao
Keywords: Computer and Information Science
Issue Date: 2024
Source: Mishra, A., Wen, T. & Cheong, K. H. (2024). Efficient traffic management in networks with limited resources: the switching routing strategy. Chaos, Solitons and Fractals, 181, 114658-. https://dx.doi.org/10.1016/j.chaos.2024.114658
Project: MOE-T2EP50120-0021
Journal: Chaos, Solitons and Fractals
Abstract: The study of network traffic dynamics in the presence of limited links bandwidth and finite node storage capacity is of significant importance, and it has garnered attention across various scientific disciplines. In this work, the switching routing strategy is applied to address this challenge and several key findings are highlighted. When networks possess infinite bandwidth, the switching strategy is efficient when the number of packets n exceeds the node storage capacity. This is observed in both Erdős-Rényi random and Barabási-Albert scale-free networks. When bandwidth constraints are introduced, the switching strategy remains efficient for networks with a large number of nodes, that is, n≥2.5C for scale-free networks and n≥2.7C for random networks. Furthermore, the efficacy of the switching strategy is more pronounced in scale-free networks than in random networks, indicating the significant role of the structural characteristics. Additionally, the results indicate that the impact of the switching strategy becomes more remarkable with increasing number of packets and storage capacity of nodes. This work sheds light on the dynamics of network traffic in the presence of bandwidth and storage constraints, providing insights into the conditions under which the switching strategy can effectively optimize traffic flow.
URI: https://hdl.handle.net/10356/175873
ISSN: 0960-0779
DOI: 10.1016/j.chaos.2024.114658
Schools: School of Computer Science and Engineering 
School of Physical and Mathematical Sciences 
Organisations: Singapore University of Technology and Design
Rights: © 2024 Published by Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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