Experiential Learning of Networking Technologies: Understanding Network Delays

2017 ◽  
Author(s):  
Ram P. Rustagi ◽  
Viraj Kumar
Keyword(s):  
Experiential Learning ◽  
Web Page ◽  
Network Delay ◽  
Web Servers ◽  
Simple Set ◽  
Network Delays ◽  
End To End ◽  
Networking Technologies ◽  
The Moment

We have all experienced a degree of frustration when a web page takes longer than expected to load. The delay between the moment when the user enters a URL (or clicks a link) and when the page contents are finally displayed has two causes: the time needed to fetch the page contents from one or more web servers (known as the end to end network delay) and the time needed to render the content in the browser window (known as the page load time). In this article, we will explore the components of the former delay via a simple set of experiments.

scholarly journals Understanding Traversal of a Packet in Internet

2020 ◽  
Author(s):  
Ram Rustagi P
Keyword(s):  
Experiential Learning ◽  
Network Protocols ◽  
Network Activity ◽  
Local Network ◽  
Application Layer ◽  
Web Page ◽  
Web Browser ◽  
Holistic View ◽  
Packet Delivery ◽  
Networking Technologies

In this series of articles on Experiential Learning of Networking Technologies, we have discussed a number of network protocols starting from HTTP [7] at application layer, TCP [3] and UDP [1] protocols at transport layers that provide end to end communications, and IP addressing [2] and routing for packet delivery at network layer. We have defined a number of experiential exercises for each underlying concept which provide a practical understanding of these protocols. Now, we would like to take a holistic view of these protocols which we have learned so far and look at how all these protocols come into play when an internet user makes a simple web request, e.g., what happens from network perspective when a user enters google.com in the URL bar of a web browser [12]. From the perspective of user, web page of Google’s search interface is displayed in the browser window, but inside the network both at the user’s local network and the internet, a lot of network activity takes place. The focus of this article is to understand the traversal of packets in the network triggered by any such user activity.

Experiential Learning of Networking Technologies: Understanding Web Security

2018 ◽  
Author(s):  
Ram P. Rustagi ◽  
Viraj Kumar
Keyword(s):  
Experiential Learning ◽  
Web Security ◽  
Web Based ◽  
Security Issues ◽  
Hands On ◽  
Networking Technologies

With the rapid increase in the volume of e-commerce, the security of web-based transactions is of increasing concern. A widespread but dangerously incorrect belief among web users is that all security issues are taken care of when a website uses HTTPS (secure HTTP). While HTTPS does provide security, websites are often developed and deployed in ways that make them and their users vulnerable to hackers. In this article we explore some of these vulnerabilities. We first introduce the key ideas and then provide several experiential learning exercises so that readers can understand the challenges and possible solutions to them in a hands-on manner.

Dual-Hop Amplify-and-Forward Variable Gain Relaying over Mixture Gamma Fading Channels

2015 ◽  
Vol 719-720 ◽  
pp. 767-772
Author(s):  
Wei Jun Cheng
Keyword(s):  
Fading Channels ◽  
Signal To Noise Ratio ◽  
Symbol Error Rate ◽  
Amplify And Forward ◽  
Variable Gain ◽  
Average Symbol Error Rate ◽  
Simulation Results ◽  
End To End ◽  
The Moment ◽  
Relaying System

In this paper, we present the end-to-end performance of a dual-hop amplify-and-forward variablegain relaying system over Mixture Gamma distribution. Novel closed-form expressions for the probability density function and the moment-generation function of the end-to-end Signal-to-noise ratio (SNR) are derived. Moreover, the average symbol error rate, the average SNR and the average capacity are found based on the above new expressions, respectively. These expressions are more simple and accuracy than the previous ones obtained by using generalized-K (KG) distribution. Finally, numerical and simulation results are shown to verify the accuracy of the analytical results.

Dynamic Voltage Scaling in Multitier Web Servers with End-to-End Delay Control

2007 ◽  
Vol 56 (4) ◽  
pp. 444-458 ◽  
Author(s):  
Tibor Horvath ◽  
Tarek Abdelzaher ◽  
Kevin Skadron ◽  
Xue Liu
Keyword(s):  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Web Servers ◽  
End To End Delay ◽  
Delay Control ◽  
Dynamic Voltage ◽  
End To End

The Influence of Web Page Images on the Performance of Web Servers

2001 ◽  
pp. 821-828 ◽  
Author(s):  
Cristina Hava Muntean ◽  
Jennifer McManis ◽  
John Murphy
Keyword(s):  
Web Page ◽  
Web Servers

Dual-Hop Fixed Gain Relaying Transmissions with Semi-Blind in Asymmetric Multipath/Shadowing Fading Channels

2015 ◽  
Vol 9 (1) ◽  
pp. 82-90
Author(s):  
Weijun Cheng ◽  
Teng Chen
Keyword(s):  
Fading Channels ◽  
Cumulative Distribution Function ◽  
Signal To Noise Ratio ◽  
Ergodic Capacity ◽  
Moment Generating Function ◽  
Symbol Error Rate ◽  
Cumulative Distribution ◽  
Simulation Results ◽  
End To End ◽  
The Moment

In this paper, we investigate the end-to-end performance of a dual-hop fixed gain relaying system with semiblind relay under asymmetric fading environments. In such environments, the wireless links of the considered system undergo asymmetric multipath/shadowing fading conditions, where one link is subject to only the Nakagami-m fading, the other link is subject to the composite Nakagami-lognormal fading which is approximated by using mixture gamma fading model. First, the cumulative distribution function (CDF), the moment generating function (MGF) and the moments of the end-to-end signal-to-noise ratio (SNR) are derived under two asymmetric scenarios. Then, novel closed-form expressions of the outage probability, the average end-to-end SNR, the symbol error rate and the ergodic capacity for the dual-hop system are obtained based on the CDF and the MGF, respectively. Finally, some numerical and simulation results are shown and discussed to validate the accuracy of the analytical results under different scenarios, such as varying average SNR, fading parameters per hop, the choice of the semi-blind gain and the location of relaying nodes.

EXPERIENTIAL LEARNING OF NETWORKING TECHNOLOGIES: Understanding TCP Flow Control and Congestion Control

2019 ◽  
Author(s):  
RAM P. RUSTAGI ◽  
VIRAJ KUMAR
Keyword(s):  
Experiential Learning ◽  
Flow Control ◽  
Congestion Control ◽  
Tcp Performance ◽  
Underlying Network ◽  
Tcp Congestion Control ◽  
Networking Technologies

In a TCP connection, the underlying network drops packets when it lacks the capacity to deliver all the packets sent by the sender to the receiver. This phenomenon is called congestion. TCP at the sender’s side will not receive acks for these dropped packets. Since TCP is a reliable protocol, the sender must retransmit all these packets. The mechanism used by TCP to deal with such situations is called TCP Congestion Control. In this article, we explain the basics of congestion control and provide experiential exercises to help understand its impact on TCP performance.

Experiential Learning of Networking Technologies: Understanding TCP States – Part 2

2018 ◽  
Author(s):  
Ram P Rustagi ◽  
Viraj Kumar
Keyword(s):  
Experiential Learning ◽  
Resource Utilization ◽  
Web Applications ◽  
Poor Performance ◽  
Networking Technologies ◽  
Tcp Connections ◽  
Web Developers

This article focuses on the states of a TCP connection once one of the endpoints decides to terminate the connection. This so-called teardown phase involves the exchange of numerous messages (for reasons we will explore), and the TCP connection itself transitions through several states. Web developers often have only an overly simplistic understanding of these states, which may suffice when the network behaves reliably. However, a deeper understanding of TCP states is essential to design web applications that robustly manage TCP connections even in the presence of network faults during the teardown phase, and debug poorly design applications that exhibit poor resource utilization and poor performance in such situations. As always, we will explore these issues through a series of experiential learning exercises.

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