Streams of Data Flow in Transmission Control Protocol (TCP) Request-Response Cycle Efficiency

Abstract

This study examines the complexities of data transmission in Transmission Control Protocol (TCP) Request-Response cycles, with the goal of improving overall efficiency. The research aims to enhance the efficiency of these cycles by studying the dynamic characteristics of data streams. An experimental analysis was carried out utilising a thorough examination of TCP streams of HTTP request-response cycle, with a focus on the complex interaction between client requests and server responses. This study utilises BlazeMeter and JMeter to analyse the effectiveness of TCP request-response cycles, specifically examining the dynamics of data flow. Significant variances were seen in performance indicators across a range of different settings. Analysis of certain experimental request-response scenarios reveals that consistently high response times leads to a persistent server load as well as resource limitations, which negatively affect the overall user experience. In contrast, certain request-response scenarios demonstrate a greater throughput, suggesting a more efficient data transfer capacity, whilst lower throughput scenarios in the experimental conditions indicate the possible bottlenecks as well as network problems. The analysis encompasses various thread groups, providing insights into error rates, response times, and throughputs. These findings enhance the understanding of the efficiency of the TCP request-response cycle and emphasise the elements that affect the flow of data during transmission sessions. Consequently, the research concludes that the data flow within TCP request-response cycles lacks a discernible pattern that can be utilised for training purposes in the field of Artificial Intelligence