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A fuzzy bandwidth and delay guaranteed routing algorithm for performance enhancement of video conference over MPLS networks

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Abstract

Nowadays, video conferencing is one of the state-of-the-art and highly demanded technologies for conducting online communications. Providing real-time and rapid connection establishment is one of the chief principles of video conferences which is competently achieved by Multi-Protocol Label Switching (MPLS). Also, the emerging concept of Next Generation Networks (NGN) has accelerated the advancement of IP-based multimedia networks including Voice over IP (VoIP), Video on Demand (VoD) and IPTVs. MPLS networks have formed the foundation of fulfilling multimedia requirements in NGN. Therefore, Label Switching Path (LSP) routing is one of the highlighted challenges of Traffic Engineering (TE) in MPLS networks. MPLS routing algorithms attempt to increase the acceptance rate of requests and consequently meet the Quality of Service (QoS) constraints satisfaction. In this paper, we propose a novel routing algorithm that applies fuzzy rules to meet the bandwidth and end-to-end delay constraints in the routing. The proposed fuzzy mechanism constitutes a predicting system based on weighted fuzzy rules that filters the requests with higher resource demands. We name the proposed method as Fuzzy Bandwidth and Delay guaranteed Routing Algorithm (FBDRA). Schematically, FBDRA aims to defer the requests with maximum bandwidth and minimum end-to-end delays. All simulation experiments are carried out in MATLAB R2019a on different scenarios. We have gauged several metrics such as the number of accepted requests, average path length, energy consumption, load balancing, and average end-to-end delay to evaluate our proposed algorithm performance. The simulation results evidence the superiority of FBDRA in video conference applications.

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Correspondence to Jianhu Gong.

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Gong, J., Nazari, H. A fuzzy bandwidth and delay guaranteed routing algorithm for performance enhancement of video conference over MPLS networks. J Ambient Intell Human Comput 14, 7079–7090 (2023). https://doi.org/10.1007/s12652-021-03560-8

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