{"title":"Maximization of Communication Network Throughput using Dynamic Traffic Allocation Scheme","authors":"Md. Arquam, Suchi Kumari","doi":"arxiv-2409.04724","DOIUrl":null,"url":null,"abstract":"Optimizing network throughput in real-world dynamic systems is critical,\nespecially for diverse and delay-sensitive multimedia data types such as VoIP\nand video streaming. Traditional routing protocols, which rely on static\nmetrics and single shortest-path algorithms, were unable in managing this\ncomplex information. To address these challenges, we propose a novel approach\nthat enhances resource utilization while maintaining Quality of Service (QoS).\nOur dynamic traffic allocation model prioritizes different data types based on\ntheir delay sensitivity and allocates traffic by considering factors such as\nbandwidth, latency, and network failures. This approach is shown to\nsignificantly improve network throughput compared to static load balancing,\nespecially for multimedia applications. Simulation results confirm the\neffectiveness of this dynamic method in maximizing network throughput and\nmaintaining QoS across various data types.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":"66 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Networking and Internet Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.04724","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Optimizing network throughput in real-world dynamic systems is critical,
especially for diverse and delay-sensitive multimedia data types such as VoIP
and video streaming. Traditional routing protocols, which rely on static
metrics and single shortest-path algorithms, were unable in managing this
complex information. To address these challenges, we propose a novel approach
that enhances resource utilization while maintaining Quality of Service (QoS).
Our dynamic traffic allocation model prioritizes different data types based on
their delay sensitivity and allocates traffic by considering factors such as
bandwidth, latency, and network failures. This approach is shown to
significantly improve network throughput compared to static load balancing,
especially for multimedia applications. Simulation results confirm the
effectiveness of this dynamic method in maximizing network throughput and
maintaining QoS across various data types.