An efficient software defined network controller based routing adaptation for enhancing QoE of multimedia streaming service

Taha, Miran

doi:10.1007/s11042-023-14938-5

Cited by 5 publications

(1 citation statement)

References 38 publications

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“…The latest work [32] estimates the cost of a given path in the network based on five criteria: adaptive network packet size, accurate packet count, overall required time interval, QoS (Quality of Service) link capacity (bandwidth), and shortest path in terms of hops. This paper also takes into account QoS.…”

Section: Simulation Resultsmentioning

confidence: 99%

QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks

Xue

Yang²,

Yang

et al. 2023

Drones

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With the growing utilization of intelligent unmanned aerial vehicle (UAV) clusters in both military and civilian domains, the routing protocol of flying ad-hoc networks (FANETs) has promised a crucial role in facilitating cluster communication. However, the highly dynamic nature of the network topology, owing to the rapid movement and changing direction of aircraft nodes, as well as frequent accesses and exits from the network, has resulted in an increased interruption rate of FANETs links. While traditional protocols can satisfy basic network service quality (QoS) requirements in mobile ad-hoc networks (MANETs) with relatively fixed topology changes, they may fail to achieve optimal routes and consequently restrict information dissemination in FANETs with topology changes, which ultimately leads to elevated packet loss and delay. This paper undertakes an in-depth investigation of the challenges faced by current routing protocols in high dynamic topology scenarios, such as delay and packet loss. It proposes a Q-learning empowered highly dynamic, and latency-aware routing algorithm for flying ad-hoc networks (QEHLR). Traditional routing algorithms are unable to effectively route packets in highly dynamic FANETs; hence, this paper employs a Q-learning method to learn the link status in the network and effectively select routes through Q-values to avoid connection loss. Additionally, the remaining time of the link or path lifespan is incorporated into the routing protocol to construct the routing table. QEHLR can delete predicted failed links based on network status, thereby reducing packet loss caused by failed route selection. Simulations show that the enhanced algorithm significantly improves the packet transmission rate, which addresses the challenge of routing protocols’ inability to adapt to various mobility scenarios in FANETs with dynamic topology by introducing a calculation factor based on the QEHLR protocol. The experimental results indicate that the improved routing algorithm achieves superior network performance.

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Section: Simulation Resultsmentioning

confidence: 99%

QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks

Xue

Yang²,

Yang

et al. 2023

Drones

View full text Add to dashboard Cite

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SoftWind: Software-defined trajectory correction modelling of gust wind effects on internet of drone things using glowworm swarm optimization

Hazra,

2024

Ad Hoc Networks

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Hierarchical Game‐Theoretic Framework for Live Video Transmission with Dynamic Network Computing Integration

Zeng,

Zhuang,

et al. 2024

International Journal of Intelligent Systems

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Recently, live streaming technology has been widely utilized in areas such as online gaming, e‐healthcare, and video conferencing. The increasing network and computational resources required for live streaming increase the cost of content providers and Internet Service Providers (ISPs), which may lead to increased latency or even unavailability of live streaming services. The current research primarily focuses on providing high‐quality services by assessing the resource status of network nodes individually. However, the role assignment within nodes and the interconnectivity among nodes are often overlooked. To fill this gap, we propose a hierarchical game theory‐based live video transmission framework to coordinate the heterogeneity of live tasks and nodes and to improve the resource utilization of nodes and the service satisfaction of users. Secondly, the service node roles are set as producers who are closer to the live streaming source and provide content, consumers who are closer to the end users and process data, and silent nodes who do not participate in the service process, and a non‐cooperative game‐based role competition algorithm is designed to improve the node resource utilization. Furthermore, a matching‐based optimal path algorithm for media services is designed to establish optimal matching associations among service nodes to optimize the service experience. Finally, extensive simulation experiments show that our approach performs better in terms of service latency and bandwidth.

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An efficient software defined network controller based routing adaptation for enhancing QoE of multimedia streaming service

Cited by 5 publications

References 38 publications

QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks

QEHLR: A Q-Learning Empowered Highly Dynamic and Latency-Aware Routing Algorithm for Flying Ad-Hoc Networks

SoftWind: Software-defined trajectory correction modelling of gust wind effects on internet of drone things using glowworm swarm optimization

Hierarchical Game‐Theoretic Framework for Live Video Transmission with Dynamic Network Computing Integration

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