Online Algorithms
Online algorithms are computational methods that process input data sequentially, piece-by-piece, without having access to the entire input set in advance. They must make irrevocable decisions at each step based only on the data seen so far, often aiming to optimize performance (e.g., minimize cost or maximize efficiency) in real-time scenarios. This contrasts with offline algorithms, which have full knowledge of all input data from the start.
Developers should learn online algorithms when building systems that handle streaming data, real-time decision-making, or resource allocation under uncertainty, such as in web caching, load balancing, or financial trading platforms. They are essential for applications where data arrives continuously and immediate responses are required, helping to design efficient and responsive solutions in dynamic environments like network routing or online advertising auctions.