HEAVY TRAFFIC ANALYSIS OF DATA TRANSMISSION AND COMMUNICATION SYSTEMS USING QUEUING THEORY
Krati Garg
Computer Science
June 2024
Introduction: First of all, managing large heavy traffic is essential for maintaining performance and dependability in the field of data transmission and communication networks. This study investigates the use of queuing theory to analyse heavy traffic, providing a methodical way to anticipate and resolve congestion problems. Aim: The purpose of this study is to explore and use Queuing Theory models, namely (M/M/1): ((C+1)/FCFS) and (M/M/2): ((C+1)/FCFS), to the prediction and stabilisation of congestion rates in communication and data transmission systems during periods of heavy traffic. Method: To analyse heavy traffic, we use Queuing Theory models (M/M/1) and (M/M/2) with ((C+1)/FCFS) configurations. The main goals of the research are to develop methods for predicting periods of heavy traffic and creating consistent congestion rate formulas. To provide a thorough strategy for real-time traffic estimation and monitoring, these models are combined with standard heavy traffic monitoring characteristics. Findings: Using Queuing Theory models, the study presents efficient approaches for predicting periods of heavy traffic and creating reliable equations for the rate of congestion. The study demonstrates how well (M/M/1) and (M/M/2) models forecast and control congestion under various traffic loads. Conclusion: Performance and resilience are improved when Queuing Theory models are incorporated into the analysis of heavy traffic in data transmission and communication systems. The established techniques allow for precise forecasts and effective data flow management, guaranteeing that systems can withstand spikes in traffic volumes with little disturbance.
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