This thesis demonstrates the performance of Probabilistic Early Response TCP (PERT), a new TCP congestion control, for video streaming. As a delay based protocol, it measures the delay at the end host and adjusts the congestion window accordingly. Our experiments show that PERT improves video delivery performance by decreasing the fraction of packets delivered late. Furthermore, our Linux live streaming test indicates that PERT is able to reduce the playback glitches, when high resolution video is delivered over a link with non-zero packet loss. In order to operate PERT at higher thoughputs, we design PERT to work with Acknowledgement (ACK) coalescing at the receiver. ACK coalescing makes data transfers burstier and makes it hard to estimate delays accurately. We apply TCP pacing to fix this issue, and validate its effectiveness in the aspects of throughput, packet loss and fairness. Our experiment results also show that PERT with Delayed ACK and Pacing is more friendly, and therefore more suitable when multiple traffic flows are competing for limited bottleneck bandwidth or sharing the same router buffer.

The stability of the Internet is at risk if the amount of voice and video traffic continues to increase at the current pace. While current transport layer protocols do work well for most applications, they still present some problems. TCP is reliable, tracks the state of some network conditions and reacts drastically to an indication of congestion. TCP serves data-oriented applications very well but it can lead to unacceptably low quality for streaming applications by multiplicatively reducing the congestion window upon a sign of congestion. The other main transport layer protocol, UDP, provides good service for streaming applications but is not friendly to TCP and can cause the well-known existing congestion collapse problem in the Internet. This thesis proposes a new protocol to provide a good service for voice and video applications while being friendly to TCP and solving the congestion collapse problem. The protocol utilizes a fuzzy logic controller that considers network related information to govern the applications sending rate while satisfying the users needs. Using network information such as the available bandwidth, Packet Loss Rates (PLR), and Round Trip Times (RTT) a fuzzy inference system optimizes the applications send rate to meet the requested rate in a smooth manner without wasting network resources unnecessarily. The fuzzy logic controller is designed and its performance evaluated using MATLAB model simulations. The results indicate that the fuzzy controller solves the congestion collapse problem by reducing the number of undelivered packets into the network by nearly 100%. It provides smooth transition changes as demonstrated by the controlled UDP flow utilizing an estimated 44% more of the available bandwidth to smooth the send rate than the TCP flow in a highly varying bandwidth environment. The controller also remains friendly with TCP which was demonstrated to share the bandwidth at nearly 50% with one other competing controlled UDP flow.

No / People, systems, and things in the cities generate large amount of data which is considered to be the most scalable asset of any smart city. Linux users are rapidly increased in last few years, and many large multinational organizations are deploying long distance high bandwidth (LDHB) cloud networks for centralizing the data from various smart cities on a central location. TCP is responsible for reliable communication of data in these cloud networks. For reliability communication among various smart cities, a number of TCP congestion control mechanisms have been developed in the past. TCP Compound, TCP Fusion, and TCP CUBIC are the default TCP congestion control mechanisms for Microsoft Windows, Sun Solaris, and Linux operating systems respectively. The response function of TCP CUBIC is higher than the response function of Standard TCP, which is a trademark congestion control mechanism. As a result, TCP CUBIC does not behave friendly with Standard TCP in LDHB cloud networks. The Congestion Window (cwnd) reduction and growth of TCP CUBIC is very aggressive, which causes high packet loss rate and unfair share of available link bandwidth among competing flows from various smart cities. The aim of this research is to design a new TCP congestion control mechanism for Linux operating system to achieve maximum performance in LDHB cloud networks being used by smart cities. In this paper, congestion control module for slow start (CCM-SS) is designed by increasing the lower boundary limit of cwnd size in slow start phase of communication. Congestion control module for loss event (CCM-LE) is designed by increasing the cwnd reduction rate at each packet loss event and finally Advance Response Function for TCP CUBIC (ARFC) is proposed to design a new congestion control mechanism for Linux operating system. NS-2 is used to compare the performance of TCP CUBIC* with TCP CUBIC in short distance high bandwidth (SDHB) and long distance high bandwidth (LDHB) cloud networks. Results show that TCP CUBIC* has outperformed in LDHB networks, at least by a factor of 18% as compared to TCP CUBIC.