The increasing demand for high-speed, reliable, and fair network services in multi-gigabit-wide area networks (WANs) has necessitated the development of advanced bandwidth allocation mechanisms. This paper proposes a Fair and QoS-Aware Dynamic Bandwidth Allocation (FQ-DBA) algorithm designed to address the dual challenges of fairness and Quality of Service (QoS) prioritisation in multi-gigabit networks. FQ-DBA dynamically allocates bandwidth to ensure equitable distribution among users while meeting the stringent QoS requirements of high-priority traffic, such as VoIP and video streaming. The algorithm integrates traffic classification, fairness enforcement, and QoS-aware allocation to optimise network performance. Simulation results demonstrate that FQ-DBA achieves a high fairness index, meets QoS guarantees, and maximises throughput while minimising latency. The proposed framework is scalable, energy-efficient, and compatible with existing network protocols, making it a promising solution for next-generation WANs.

The rapid growth of network traffic in multi-gigabit wide area networks (WANs) has necessitated the development of advanced bandwidth allocation mechanisms to ensure optimal Quality of Service (QoS). This paper proposes a Predictive Real-Time Dynamic Bandwidth Allocation (PRT-DBA) algorithm designed to address the challenges of real-time adaptability and predictive analytics in multi-gigabit networks. PRT-DBA leverages machine learning techniques to predict future traffic patterns and dynamically adjusts bandwidth allocation based on real-time network conditions. The algorithm integrates predictive modelling, real-time monitoring, and dynamic allocation to optimise QoS, minimise latency, and maximise throughput. Simulation results demonstrate that PRT-DBA significantly improves network performance, reduces congestion, and ensures efficient resource utilisation. The proposed framework is scalable, secure, and compatible with existing network protocols, making it a promising solution for next-generation WANs.

The increasing demand for high-speed, reliable, and fair network services in multi-gigabit wide area networks (WANs) has necessitated the development of advanced bandwidth allocation mechanisms. This paper proposes a Fair and QoS-Aware Dynamic Bandwidth Allocation (FQ-DBA) algorithm designed to address the dual challenges of fairness and Quality of Service (QoS) prioritisation in multi-gigabit networks. FQ-DBA dynamically allocates bandwidth to ensure equitable distribution among users while meeting the stringent QoS requirements of high-priority traffic, such as VoIP and video streaming. The algorithm integrates traffic classification, fairness enforcement, and QoS-aware allocation to optimise network performance. Simulation results demonstrate that FQ-DBA achieves a high fairness index, meets QoS guarantees, and maximises throughput while minimizing latency. The proposed framework is scalable, energy-efficient, and compatible with existing network protocols, making it a promising solution for next-generation WANs.

The rapid growth of network traffic and the emergence of multi-gigabit wide area networks (WANs) have necessitated the development of advanced bandwidth allocation mechanisms to ensure optimal Quality of Service (QoS). This paper proposes a Traffic-Aware Predictive Dynamic Bandwidth Allocation (TAP-DBA) algorithm designed to address the challenge of real-time adaptability in multi-gigabit networks. TAP-DBA integrates Traffic Classification and Predictive Bandwidth Allocation to optimize QoS for diverse traffic types, including real-time, bulk, and best-effort traffic. The algorithm leverages Deep Packet Inspection (DPI) and Machine Learning (ML)-based predictive analytics to dynamically allocate bandwidth while ensuring low latency, efficient utilisation, and fairness. Simulation results demonstrate the effectiveness of TAP-DBA in reducing latency for critical traffic, maximising throughput, and maintaining equitable bandwidth distribution. The proposed framework is scalable, secure, and compatible with existing network protocols, making it a promising solution for next-generation WANs.

The increasing demand for high-speed, reliable, and resilient network services in multi-gigabit wide area networks (WANs) has highlighted the need for advanced bandwidth allocation mechanisms. This paper proposes a Resilient Multi-Path Dynamic Bandwidth Allocation (RMP-DBA) algorithm designed to enhance network resilience and performance by leveraging multi-path routing and dynamic bandwidth allocation. RMP-DBA dynamically allocates bandwidth across multiple paths, ensuring fault tolerance, load balancing, and optimal resource utilisation. The algorithm incorporates real-time path monitoring, adaptive path selection, and failure recovery mechanisms to maintain uninterrupted network services even in the presence of link failures or congestion. Simulation results demonstrate that RMP-DBA significantly improves resilience, throughput, and latency while ensuring efficient bandwidth utilisation. The proposed framework is scalable, energy-efficient, and compatible with existing network protocols, making it a promising solution for next-generation multi-gigabit WANs.