python get round trip time

• Selected Reading
• UPSC IAS Exams Notes
• Developer's Best Practices
• Questions and Answers
• Effective Resume Writing
• HR Interview Questions
• Computer Glossary

Python Program to calculate the Round Trip Time (RTT)

Here we will see how Python can be used to get the Round Trip Time (RTT). The RTT is the time which is taken by the entire trip of a signal. It means the time between the starting time when a signal is sent and the receiving time of the acknowledge signal.

The RTT results varies on different parameters like.

• The data transfer rate of the sender’s side.
• The nature of the transmission media.
• The actual distance between the sender and receiver.
• The number of nodes between sender and receiver.
• The amount of traffic on LAN.
• Number of requests handled by intermediate points.

Example Code

I love programming (: That's all I know

Related Articles

• C Program to calculate the Round Trip Time (RTT)
• C# Round-trip ("R") Format Specifier
• C++ Program to find out if a round trip is possible from a particular city
• Python program to calculate acceleration, final velocity, initial velocity and time
• Haskell Program to Calculate the Execution Time of Methods
• Java Program to calculate the time of sorting an array
• C Program to calculate the difference between two time periods
• C++ Program to Calculate Difference Between Two Time Period
• Golang Program to Calculate Difference Between Two Time Periods
• Java Program to Calculate difference between two Time Periods
• Python Program to calculate the area of Cube
• Python Program to calculate the volume of Cube
• Python Program to demonstrate the time arithmetic
• Program to find out the minimum number of intercountry travels in a road trip in Python
• PHP program to calculate the total time given an array of times

Kickstart Your Career

Get certified by completing the course

Round Trip Time (RTT) with Python

RTT is the length of time it takes for a signal to be sent plus the length of time it takes for an acknowledgment of that signal to be received [1] . In other words, a small packet will be sent to a specific computer and it will send the packet back. The time difference between sending and receiving of the packet (in client side) is known as RTT or Ping Time. The following figure shows the TCP connection and RTT.

In this regard, I want to measure RTT for 2 computers and a server which is an AWS EC2 instance located in Frankfurt. One of the computers located in Berlin, the other one is another EC2 instance which is located in Frankfurt and is near to the server. The simplified configuration is shown in Figure 2.

Server Application

EC2 Server consists of two server applications:

Socket server

Flask Server

Socket server has three important tasks. The first task is creating and maintaining the connection between the client and the server. To this end, a new thread will be created whenever a new connection is established. The second task is measuring RTT value and the last one is timestamping and saving RTT values on the database, in this case, Influxdb is used. So Flask server is able to retrieve the values.

Flask server has also three important tasks which are:

Running a web framework

Retrieving data from Database

Representing data on graphs

Client Application

The application of the client-side is relatively easy. It connects to the server and whenever gets a packet from the server; it just sends it back.

RTT value depends on various parameters such as:

Physical distance (Geographical location) between computers

Number of hubs/nodes between source and destination

Internet connection quality, Data Transfer Rate

Medium types such as LAN or WiFi

The following figures show the values of RTT for both connections. X-Axis number of samples and Y-Axis demonstrate the calculated RTT value in [ms]. It is important to notice that every three seconds the server will send a byte data to each client and by receiving it back, the server will calculate the RTT value.

As we can see in Figure 3, the RTT values for EC2 near to the server is lower than 1.35 ms, i.e. the maximum value would be around 1.35 ms.

On the other hand, RTT values for the computer located in Berlin is much higher than the other one, as shown in Figure 4. The maximum value, in this case, reaches 125 ms.

You can download the source code from my Github repository and test it on your server and client. Please share the result on the comment section below; I’ll glad to know them.

Related Posts

Tech Enthusiast

Your email address will not be published. Required fields are marked *

Email Address: *

 Yes, add me to your mailing list

Program to Calculate the Round Trip Time (RTT)

Round-trip time(RTT) in networking, also called the round-trip delay time is a benchmark that measures the amount of time it takes for a data packet to be sent in addition to the amount of time it takes for acceptance of that signal to be received in milliseconds. RTT delay also includes propagation times between two communication endpoints.

What is Round-Trip Time?

RTT can be defined by an end-user with the help of Internet protocol by pinging that address .

What is a Good Round-Trip Time?

Situations can be different for every other application. So it's not possible to predict an exact time.

A fully managed and determined desktop virtualization service such as AWS WorkSpaces allows its users to access the resource and applications they need. It has basically three thresholds for RTT.

• The round-trip time from the client's network to the AWS Region that the WorkSpaces are in should be lower than 100ms .
• If the round-trip time is between 100ms and 200ms , the user can access WorkSpace, but performance is pompous .
• If the round-trip time is between 200ms and 375ms , the performance is cheapened .
• If the round-trip time exceeds 375ms , the WorkSpaces client connection is discarded .

So in general the users should have a round-trip time of 100 milliseconds for normal usage of the application and a maximum of 200 milliseconds before the application starts to degrade.

Implementation in Python

Here's a Python code implementation to calculate the RTT

How to Reduce RTT

There are two ways through which Round-Trip Time can be reduced.

1. Reducing RTT with Amazon CDN Distribution

CDNs or Content Delivery Networks were created to solve to reduce round-trip time . Using CDN as a service it is reasonable to expect a decrease in RTT by up to half or more.

CDN can affect RTT in the following ways:

• Scalability: CDN as a cloud service, provides high scalability and the ability to exercise a vast number of user requests.
• Load Distribution: When the traffic is high, CDNs use backup edge servers with lower congestion for route requests, this speed's up the server's response time and lowers RTT.
• Points of Presence (PoPs): Content Delivery Network also manages a geographical network of dispersed PoPs data centers , each of them containing cached copies of site content data, which are in charge of communicating with site visitors in their region. This helps in reducing the distance a signal has to travel and the number of network stops required to reach a server.
• Web Caching: CDN has the power to cache media, HTML, and dynamic content on a PoP in close proximity to the user. One advantage of this is sometimes the request is fulfilled using a local PoP without traveling to the origin server , which helps in lowering RTT .

2. General Ways to Reduce RTT

• Browser Caching: Modern Browser can cache certain resources of a website locally in the system to reduce RTT .
• Discarding Broken links: Requests which result in 404/410 errors , can be discarded to avoid wasteful reports .
• Bringing content closer to the user: Servers close to the user should be used, this lower's the RTT by several amounts.
• Merging external scripts: If external scripts can be merged into as few files, this helps to lower RTT several times.
• Lessen HTTP/s directs: Minimizing HTTP/s directs from one URL to another lowers RTT and wait time.
• RTT is a crucial tool for determining the strength of the network. It is the time between the request of the data and the display of the data.
• Factors such as Distance, Network Hops, and Traffic levels can bring a massive change to the value of RTT.
• In Satellite transmissions, RTT can be measured using Jacobson/Karels algorithm.
• Calculation of RTT is advantageous because it helps the user and operators how long will it take the signal to complete the transmission .
• RTT also helps in determining the reliability of the network as the speed of a network.

• Engineering Mathematics
• Discrete Mathematics
• Operating System
• Computer Networks
• Digital Logic and Design
• C Programming
• Data Structures
• Theory of Computation
• Compiler Design
• Computer Org and Architecture
• What is Latency?
• What are Different Types of Passwords used in Securing Cisco Router?
• Why is YouTube using TCP but not UDP?
• What is RTS(Real Time Streaming)?
• DNS vs VPN - What's the Difference?
• Types of switches in Computer Network
• TCP Fast Open and TCP/IP Acceleration
• Satellite and Fibre Internet
• What is P2P (Peer-to-Peer Process)?
• TCP vs UDP for Video Streaming
• Spanning Tree Port States
• TCP/IP in Computer Networking
• VIRUS Full Form
• What is WRAN (Wireless Regional Area Network)?
• What is E2EE(End to End Encryption)?
• What is a Next generation Firewall?
• How does Frame Relay Work?
• How Data Encapsulation & De-encapsulation Works?
• How to Mitigate a DDoS Attack?

What is RTT(Round Trip Time)?

RTT (Round Trip Time) also called round-trip delay is a crucial tool in determining the health of a network. It is the time between a request for data and the display of that data. It is the duration measured in milliseconds. 

RTT can be analyzed and determined by pinging a certain address. It refers to the time taken by a network request to reach a destination and to revert back to the original source. In this scenario, the source is the computer and the destination is a system that captures the arriving signal and reverts it back. 

RTT(Round Trip Time) Measurement

What Are Common Factors that Affect RTT?

There are certain factors that can bring huge changes in the value of RTT. These are enlisted below:

• Distance: It is the length in which a signal travels for a request to reach the server and for a response to reach the browser,
• Transmission medium: The medium which is used to route a signal, which helps in faster transfer of request is transmitted.
• Network hops: It is the time that servers take to process a signal, on increasing the number of hops, RTT will also increase.
• Traffic levels: Round Trip Time generally increases when a network is having huge traffic which results in that, for low traffic RTT will also be less.
• Server response time: It is the time taken by a server to respond to a request which basically depends on the capacity of handling requests and also sometimes on the nature of the request.

Applications of RTT

Round Trip Time refers to a wide variety of transmissions such as wireless Internet transmissions and satellite transmissions. In Internet transmissions, RTT may be identified by using the ping command. In satellite transmissions, RTT can be calculated by making use of the Jacobson/Karels algorithm.  

Advantages of RTT

Calculation of RTT is advantageous because:

• It allows users and operators to identify how long a signal will take to complete the transmission.
• It also determines how fast a network can work and the reliability of the network.

Example: Let us assume there are two users, one of which wants to contact the other one. One of them is located in California while the other one is situated in Germany. When the one in California makes the request, the network traffic is transferred across many routers before reaching the server located in Germany. Once the request reverts back to California, a rough estimation of the time taken for this transmission could be made. This time taken by the transmitted request is referred to as RTT. The Round Trip Time is a mere estimate. The path between the two locations can change as the passage and network congestion can come into play, affecting the total period of transmission. 

How Does Round-Trip Time Work?

Consider a topology where an appliance named “Exinda” is located between the client and the server. The diagram shown below depicts how the concept of RTT works: 

RTT Calculation

  For the calculation of Average RTT, RTTS for server and client needs to be calculated separately. The performed calculations are shown below:

Server RTT: RTT1 = T2 – T1 RTT2 = T5 – T4

Client RTT: RTT3 = T3 – T2 RTT4 = T7 – T6 

Average RTT: Avg Server RTT = (RTTs1 + RTTs2) / 2 Avg Client RTT = (RTTc1 + RTTc2) / 2 Avg Total RTT = Avg Server RTT + Avg Client RTT 

You can refer to the Program to calculate RTT for more details.

Measures To Reduce RTT

 A significant reduction in RTT can be made using Content Delivery Network (CDN) . A CDN refers to a network of various servers, each acquiring a copy of the content on a particular website. It addresses the factors affecting RTT in the enlisted ways:

• Points of Presence (PoP)
• Web caching
• Load distribution
• Scalability
• Tier 1 access 

CDN has been largely successful in reducing the value of RTT and due to this, a decrease in RTT by 50% is achievable.

Please Login to comment...

Similar reads.

• 10 Best Slack Integrations to Enhance Your Team's Productivity
• 10 Best Zendesk Alternatives and Competitors
• 10 Best Trello Power-Ups for Maximizing Project Management
• Google Rolls Out Gemini In Android Studio For Coding Assistance
• 30 OOPs Interview Questions and Answers (2024)

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Network observability using TCP handshake round-trip time

In Red Hat OpenShift Container Platform (RHOCP), ensuring efficient packet delivery is paramount for maintaining seamless communication between applications. However, challenges like network congestion, misconfigured systems, or hardware limitations can lead to slow connections, impacting overall performance. Round-trip time (RTT), typically measured in milliseconds, plays a crucial role in monitoring network health and diagnosing issues.

Implementing smooth round-trip time (SRTT) with eBPF

The RTT is the time it takes for a packet to travel from the sender to the receiver and back. In a network, RTT can vary due to factors like network congestion, varying route lengths, and other dynamic conditions. SRTT is introduced to provide a more consistent and less jittery representation of the RTT.

In Transmission Control Protocol (TCP), RTT is a crucial metric.

Our implementation leverages eBPF to register to fentry eBPF hook for tcp_rcv_established() . We extract the SRTT (smooth round-trip time) value from TCP sockets, correlating it to existing flows and enriching them with RTT values in nanoseconds.

When a new NetObserv flow is created and the RTT feature is enabled, an initial RTT of 10usec is assigned. This initial value for RTT may be considered quite low.

Upon triggering the eBPF socket, the flow RTT value is updated to reflect the maximum RTT value for that specific flow. See Figure 1.

For more detailed explanation of smoothed RTT estimation, refer to Karn's algorithm paper .

Why use fentry eBPF hook?

The eBPF fentry programs have lower overhead as they trigger the hook before calling the kernel function of interest.

In our implementation:

• Register and link fentry hook for kernel's tcp_rcv_established() SEC("fentry/tcp_rcv_established") int BPF_PROG(tcp_rcv_fentry, struct sock *sk, struct sk_buff *skb) { if (sk == NULL || skb == NULL) { return 0; } return calculate_flow_rtt_tcp(sk, skb); }

Reconstruct the NetObserv flow key, including incoming interface Layer2, Layer3, and Layer4 info.

Match existing flows in the PerCPU hashmap flow table and enrich them with SRTT info from TCP sockets. If multiple SRTT values exist for the same flow, we take the maximum value.

Currently, our approach calculates RTT only for the TCP packets so flows, which are non-TCP, do not show RTT information.

Potential use cases

Flow RTT captured from eBPF flow_monitor hookpoints can serve various purposes.

Network monitoring: Gain insights into TCP handshakes, helping network administrators identify unusual patterns, potential bottlenecks, or performance issues.

Troubleshooting: Debug TCP-related issues by tracking latency and identifying misconfigurations.

How to enable RTT

To enable this feature, we need to create a FlowCollector object with the following fields enabled in eBPF config section as below.

A quick tour of the UI

Once the FlowRTT feature is enabled, the RHOCP console plug-in automatically adapts to provide additional filter and show information across Netflow Traffic page views.

Open your RHOCP console and move to Administrator view -> Observe -> Network Traffic page as usual.

A new filter, Flow RTT is available in the common section. The FlowRTT filter will allow you to capture any flow that has an RTT more than a specific time in nanoseconds.

For production users, filtering on the TCP protocol, Ingress direction, and looking for FlowRTT values greater than 10,000,000 nanoseconds (10ms) can help identify TCP flows with high latency. This filtering approach allows users to focus on specific network flows that may be experiencing significant delays. By setting a threshold of 10ms , you can efficiently isolate and address potential latency issues in your TCP traffic.

New graphs are introduced in the Advanced options -> Manage panels popup (Figure 2).

• Top X average TCP handshake round-trip time with overall (donut or lines)
• Bottom X minimum TCP handshake round-trip time with overall (donut or lines)
• Top X maximum TCP handshake round-trip time with overall (donut or lines)
• Top X 90th percentile TCP handshake round-trip time with overall (donut or lines)
• Top X 99th percentile TCP handshake round-trip time with overall (donut or lines)

These two graphs (see Figure 3) can help you to identify the slowest TCP flows and their trends over time. Use the filters to drill down into specific pods, namespaces, or nodes.

Traffic flows

The table view (Figure 4) shows the Flow RTT in both column and side panel.

Last but not least, the topology view displays min / max / avg / p90 / p99 RTT latency on edges. Clicking on a node or an edge will allow you to see per direction metrics and the related graph. See Figure 5.

Future improvements

Here is a non-exhaustive list of future improvements coming for a full featured round-trip time analysis:

• Latest RTT in Topology view
• Prometheus metrics and alerting

We hope you liked this article!

NetObserv is an open source project available on GitHub . Feel free to share your ideas , use cases , or ask the community for help .

• Red Hat Enterprise Linux
• Red Hat OpenShift
• Red Hat Ansible Automation Platform
• See all products
• See all technologies
• Developer Sandbox
• Developer Tools
• Interactive Tutorials
• API Catalog
• Operators Marketplace
• Learning Resources
• Cheat Sheets

Communicate

• Contact sales
• Find a partner

Report a website issue

• Site Status Dashboard
• Report a security problem

RED HAT DEVELOPER

Build here. Go anywhere.

We serve the builders. The problem solvers who create careers with code.

Join us if you’re a developer, software engineer, web designer, front-end designer, UX designer, computer scientist, architect, tester, product manager, project manager or team lead.

Red Hat legal and privacy links

• About Red Hat
• Contact Red Hat
• Red Hat Blog
• Diversity, equity, and inclusion
• Cool Stuff Store
• Red Hat Summit
• Privacy statement
• Terms of use
• All policies and guidelines
• Digital accessibility

Search code, repositories, users, issues, pull requests...

Provide feedback.

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly.

To see all available qualifiers, see our documentation .

round-trip-time

Here are 9 public repositories matching this topic..., das-group / rba-dataset.

Login feature data of more than 33M login attempts and 3M users (IP, UA, RTT)

• Updated Jun 29, 2022

shashwatkathuria / P2P-Network-Monitoring-System

P2P Network Monitoring - Implemented Round Trip Time(RTT) and Online/Offline status of peers.

• Updated Feb 29, 2020

toreamun / hanetprobe

Network uptime monitor publishing to Home Assistant MQTT discovery

• Updated Nov 4, 2022

dhoard / k-synthetic-test

Kafka synthetic test

• Updated Mar 2, 2023

keivanK1 / round-trip-time-python-influxdb

Round Trip Time measurement in python

• Updated Sep 11, 2018

MichalSoltysikSOC / Cybersecurity-content-videos

Cybersecurity content (YouTube videos) | (1) Deep packet inspection analyses - why the typical approach is not enough | (2) Remcos RAT threat analysis on Windows including IEC 60870-5-104 traffic

• Updated Feb 29, 2024

newtein / RTT_Analysis

Research Project | A study of active fingerprinting of hosts in an institutional network.

• Updated Jan 31, 2019
• Jupyter Notebook

luizalaquini / Round-Trip-Time

Algoritmo Round Trip Time - Trabalho de Estrutura de Dados II - UFES-2021-1 - Tem como base a implementação da estrutura Heap e do algoritmo de Dijkstra - Utilização da linguagem C

• Updated Sep 2, 2021

Henriquelay / RTT-meter

🖥️-💻 A Round-Trip-Time measuring tool using Dijkstra with priority heap. Assignment for Data Structures 2 course, 2020/2 on UFES

• Updated Apr 15, 2021

Improve this page

Add a description, image, and links to the round-trip-time topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the round-trip-time topic, visit your repo's landing page and select "manage topics."

Solar eclipse 2024: Photos from the path of totality and elsewhere in the U.S.

Images show the Great American Eclipse, seen by tens of millions of people in parts of Mexico, 15 U.S. states and eastern Canada for the first time since 2017.

Millions gathered across North America on Monday to bask in the glory of the Great American Eclipse — the moment when the moon passes between the Earth and the sun. 

The path of totality measures more than 100 miles wide and will first be visible on Mexico’s Pacific coast before moving northeast through Texas, Oklahoma, Arkansas, Missouri, Illinois and upward toward New York, New Hampshire and Maine, then on to Canada.

Total solar eclipse 2024 highlights: Live coverage, videos and more

During the cosmic spectacle, the moon’s movements will temporarily block the sun’s light, creating minutes of darkness, and will make the sun's outer atmosphere, or the corona, visible as a glowing halo.

Here are moments of the celestial activities across the country:

Breaking News Reporter

Elise Wrabetz is a Senior Photo Editor for NBC News digital

Chelsea Stahl is the art director for NBC News Digital