Round Trip Time (RTT) Analysis using Wireshark under Various Traffic Conditions

INTRODUCTION

Computer networks play a crucial role in modern communication systems by enabling efficient data transfer between devices. One of the key performance parameters used to evaluate network efficiency is Round Trip Time (RTT). RTT refers to the time taken for a data packet to travel from the source to the destination and back again. It is an important metric that reflects network delay and responsiveness.

In this experiment, RTT is measured and analysed using Wireshark under different traffic conditions such as normal, medium, and high traffic. The study helps in understanding how increasing network load affects packet transmission delay and overall network performance.

OBJECTIVES

• To measure Round Trip Time (RTT) using Wireshark
• To analyze RTT under different traffic conditions
• To study the impact of network congestion on RTT
• To visualize RTT variations using graphical analysis

REFERENCE SOURCE

This experiment was initiated based on resources from Wireshark official documentation and network traffic analysis tutorials such as SharkFest. These sources provided insights into packet capturing, filtering techniques, and performance parameter evaluation using Wireshark.

ARCHITECTURE OF WORK

PROCEDURE

1. Wireshark was opened and the active network interface was selected.
2. Packet capturing was started using the Wi-Fi interface.
3. ICMPv6 packets were generated using the ping command with different packet counts to simulate varying traffic conditions.
4. For normal traffic, a lower number of packets was sent, while for medium and high traffic, the number of packets was increased significantly.
5. After sending packets, the capture was stopped in Wireshark.
6. The filter icmpv6 was applied to display only relevant packets.
7. RTT was calculated by finding the time difference between Echo Request and corresponding Echo Reply packets.
8. The calculated RTT values were recorded in tabular form.
9. Graphs were generated to visualize RTT variations under different traffic conditions.

INFERENCES (GRAPH ANALYSIS)

This graph shows the variation of RTT with packet number under normal traffic conditions for a small set of packets. The RTT values range approximately between 68 ms and 92 ms, showing relatively stable behavior with minor fluctuations. A noticeable peak is observed around packet 3, indicating a temporary increase in delay. The lower line represents packet progression, while the RTT trend remains consistent overall. This indicates that the network is operating efficiently with minimal congestion under normal traffic conditions.

This graph shows the variation of RTT with packet number under medium traffic conditions. The RTT values range approximately between 40 ms and 110 ms, showing noticeable fluctuations compared to normal traffic. Several peaks and dips are observed, particularly around packets 6 and 12, indicating variable delay due to increased network load. The variation in RTT reflects moderate congestion and inconsistent packet transmission times. Overall, this graph demonstrates that network performance begins to degrade as traffic increases from normal to medium levels.

This graph shows the variation of RTT with packet number under high traffic conditions. The RTT values initially exhibit a sharp peak close to 100 ms, followed by a sudden drop and gradual stabilization between approximately 45 ms and 65 ms. The initial spike indicates heavy congestion at the start of transmission, while the later values show relatively stable but elevated delays compared to normal traffic. The gradual increase in RTT with packet number reflects sustained network load. Overall, this graph demonstrates that high traffic conditions lead to increased delay and reduced network performance.

This graph shows the variation of RTT with packet number for a detailed set of packets under normal traffic conditions. The RTT values range approximately between 35 ms and 120 ms, indicating moderate fluctuations. Significant peaks are observed around packets 6 and 15, while a sharp drop occurs near packet 12, reflecting temporary variations in network delay. Despite these fluctuations, most RTT values remain within a consistent range. This indicates generally stable network performance with occasional transient delays.

This graph shows the variation in RTT between consecutive packets, representing the difference in delay from one packet to the next. The RTT difference ranges approximately from -50 ms to +60 ms, indicating both sudden increases and decreases in delay. Significant positive spikes indicate abrupt increases in network delay, while negative dips show sudden improvements in transmission time. The irregular pattern reflects inconsistent packet delivery under varying network conditions. Overall, this graph highlights the dynamic nature of network performance and the presence of transient congestion effects.

This graph shows the relationship between RTT and throughput. As RTT increases from approximately 40 ms to 120 ms, the throughput decreases from around 28 units to below 10 units. The downward trend clearly indicates an inverse relationship between RTT and throughput. Higher RTT values correspond to increased network delay, which reduces the efficiency of data transmission. This demonstrates that as network congestion increases, throughput decreases, leading to degraded overall network performance.

This graph shows the moving average of RTT over a sequence of packets, which helps smooth out short-term fluctuations and highlight the overall trend in network delay. The RTT values vary approximately between 50 ms and 95 ms, showing a gradual rise and fall pattern. A noticeable dip occurs around packet index 9, followed by a sharp increase, indicating temporary changes in network conditions. The moving average reduces noise from sudden spikes and provides a clearer view of delay trends. Overall, the graph indicates moderate variability in RTT with identifiable periods of higher and lower delay.

This graph shows the distribution of RTT values across different ranges using a histogram. The RTT values are spread approximately between 40 ms and 120 ms, with most values concentrated in the range of 60 ms to 90 ms. The higher frequency in this range indicates that the network delay is generally consistent within this interval. Fewer occurrences are observed at extreme values, representing occasional spikes or drops in delay. Overall, the distribution suggests moderate variability in RTT with a tendency toward stable performance in the mid-range.

 

This graph shows the variation of throughput with respect to time (or packet progression). The throughput remains relatively low and stable in the initial phase, indicating steady but limited data transmission. As the packet index increases, a sharp rise in throughput is observed, followed by noticeable fluctuations. The peak values indicate periods of high data transfer efficiency, while the drops reflect temporary reductions in network performance. Overall, the graph demonstrates that throughput increases with sustained transmission but becomes unstable under higher load conditions.

 

This graph shows the comparison of average RTT values across different traffic conditions. The average RTT is highest under normal traffic and gradually decreases as the traffic level changes, indicating variation in delay behavior across conditions. The downward trend suggests that RTT values stabilize or reduce under sustained packet transmission. However, variations may occur due to network adaptation and buffering effects. Overall, the graph highlights how average RTT differs across traffic scenarios and reflects changing network performance characteristics.

This graph shows the variation of throughput over time (or packet progression). The throughput remains relatively low and stable for most of the duration, indicating steady data transmission. A sudden sharp spike is observed around the middle of the graph, where throughput increases significantly for a short period. This spike represents a temporary burst of high data transfer, possibly due to favorable network conditions or buffering effects. After the peak, the throughput quickly drops back to normal levels, indicating that the high performance was not sustained. Overall, the graph highlights the presence of transient spikes in throughput under dynamic network conditions

This graph shows the variation of throughput over time (or packet progression). The throughput remains low and stable initially, followed by multiple sharp spikes at different intervals. These peaks indicate short bursts of high data transmission, possibly due to temporary improvements in network conditions or buffering effects. Between these spikes, the throughput drops significantly, showing inconsistency in network performance. After the peak periods, the throughput stabilizes again at a lower level. Overall, the graph highlights that throughput under varying conditions is highly dynamic and characterized by intermittent bursts rather than sustained performance.

 

This graph shows the variation of throughput over time. Initially, the throughput increases rapidly from a low value and stabilizes around a higher level, indicating efficient data transmission. For most of the duration, the throughput remains relatively steady, showing consistent network performance. However, a sudden sharp drop is observed near the later time interval, indicating a temporary disruption or packet loss. Following this drop, the throughput quickly recovers, suggesting restoration of normal network conditions. Overall, the graph demonstrates that while throughput is generally stable, sudden disruptions can occur but may be quickly resolved.

 

NEW FINDINGS AND RECOMMENDATIONS

• RTT increases significantly with higher traffic conditions
• Network congestion leads to increased packet delay
• Stability decreases under heavy load
• Efficient traffic management can improve performance
• Optimization of network resources is necessary to reduce RTT

AI tools were utilized to assist in structuring the documentation, generating graphical analysis, and improving clarity of explanations. AI also helped in organizing data and presenting insights effectively.

CONCLUSION

The experiment successfully demonstrated the analysis of Round Trip Time (RTT) using Wireshark under different traffic conditions. It was observed that RTT increases as network traffic increases, which affects the overall performance of the network. The study highlights the importance of managing network load to ensure efficient and reliable communication.

YOUTUBE VIDEO LINK

https://youtu.be/8kH7-ru5JtU

GITHUB REPOSITORY LINK

https://ravibalamv.github.io/Wireshark-RTT-Analysis/

REFERENCES

1. Wireshark Official Documentation
2. SharkFest Network Analysis Tutorials
3. General Networking Concepts from Online Resources 

ACKNOWLEDGEMENT

I would like to express my sincere gratitude to the School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Chennai, for offering the Computer Networks course during the Winter Semester 2025–2026 with an industry-standard syllabus.

I would like to thank my course faculty, Dr. T. Subbulakshmi, Professor, SCOPE, VIT Chennai, for her valuable guidance and support throughout this work.

I extend my appreciation to Gerald Combs, the founder of Wireshark and ACM Software System Award winner (2018), for providing an excellent tool for network traffic analysis.

I would also like to thank my peers and classmates for their valuable suggestions and support during this work.

I am grateful to my friends who helped me understand the concepts and complete this work successfully.

Finally, I would like to thank my parents and family members for their continuous encouragement and support.

AUTHOR

Mr. Ravibala M V, II year B.Tech. CSE student, School of Computer Science and Engineering, VIT Chennai