Copy introduction

Problem statement

If millions of users worldwide use the data-intensive applications, and we have our service deployed at a data center to serve the users’ requests, what possible problems can arise?

The data between the client and the server travels over a network that introduces network delays due to the distance between the client and the server and the size of the data to be transferred. That implies that increasing the distance of our application’s user from the physical server will increase the latency. User-perceived latency has many components, such as transmission delays (a function of available bandwidth), propagation delays (a function of distance), queuing delays (a function of network congestion), and end-node delays.

Transmitting the data over a large distance results in the propagation delay (a latency component) that indirectly affects available bandwidth. This is because data might pass through many networks, and some might be congested. Therefore, we can bring data near the user by placing a small data center near the user and storing copies of the data there. Content Delivery Network (CDN) primarily targets propagation delay by bringing the data closer to its users. CDN providers go the extra mile to have sufficient bandwidth available through the path and bring data closer to the users (possibly within their ISP). They also try to reduce transmission and queueing delays because presumably, ISP will have more bandwidth available within the autonomous system. We will discuss CDN in detail in this lesson.

According to one of the readings on 2021-12-21, the average latency from US East (N. Virginia) to US West (N. California) was 62.9 milliseconds, and across continents, for example, from the US East (N. Virginia) to Africa (Cape Town) was 225.63 milliseconds. Here, we are discussing a two-way latency known as round-trip latency.