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Current video streaming applications have gained the interest of various industries due to their ability to create a comprehensive reality and get people close to each other. Constraints on available resources (such as bandwidth) cause packet loss and re-transmission when the network is overloaded, which refers to “congestion”. The main concept that controls the conversational video for WebRTC is the congestion control algorithm. The goal of this project is to provide an analysis of the performance of different TCP congestion control algorithms. Furthermore, a suitable environment is implemented to achieve the optimum performance for the selected algorithms.

Previous and current networking paradigms always introduced new technologies incorporated in various applications over the internet. Some of them demand high transmission throughput or low delay, which led to new issues since it increased the traffic over the internet. Congestion refers to the issue where the processing is slower than the receiving rate. Such an issue causes packet loss and, in some cases, collapses the whole network. Thus, it is crucial to address such problems by implementing a congestion control algorithm to handle such cases. No congestion control mechanism was implemented in the original standardized TCP design. Later, new mechanisms were designed, such as slow start, congestion avoidance, additive increase, multiplicative decrease, etc. Finally, new variants of TCP appeared to manage the congestion window differently, such as TCP Tahoe, Reno, NewReno, Vegas, Hybla, etc. This project aims to implement the specified TCP variants and analyze their performance in different network conditions to create a comprehensive and generalized idea regarding their performance.