Optimization of transmission control protocol and feedback control mechanisms for wireless internet

University of Technology, Sydney. Dept. of Computer Systems.All current versions of reliable Transmission Control Protocol (TCP) react to packet losses differently and adjust the TCP congestion window in various ways. These protocols assume congestion in the network to be the primary cause for packet losses and unusual delays. TCP performs well over wired networks by adapting to end-to-end delays and packet losses caused by congestion. The TCP sender uses the cumulative acknowledgements it receives to determine which packets have reached the receiver, and provides reliability by retransmitting lost packets. The sender identifies the loss of a packet either by the arrival of several duplicate cumulative acknowledgements (say, three ACKs) or the absence of an acknowledgement for the packet within a timeout. TCP reacts to packet losses by reducing its transmission (congestion) window size before retransmitting packets, initiating congestion window or avoidance mechanisms and backing off its retransmission timer. These measures result in a reduction in the load on the intermediate links, thereby controlling the congestion in the network. Unfortunately, when packets are lost in the networks for reasons other than congestion, these measures result in an unnecessary reduction in end-to-end throughput and sub-optimal performance. Wireless links typically have much higher bit error rates. This implies that packet loss would occur frequently. If no error correction is attempted at lower layer, TCP will exercise its congestion control procedure unnecessarily and the throughput will be reduced significantly. If the link layer performs error control by performing the retransmission itself, packet transmission time will vary greatly, sometime even exceeding TCP retransmission time out and again TCP slow start will occur. In wireless networks, “packet loss ’’ problem is also encountered during handover when a mobile device moves from the coverage of one cell to that of another. During the handover, if the mobile station decides to make a handover before the segments are transmitted over the air interface, it is likely that some TCP segments buffered in a base station may be forwarded to another base station. This results in excessive segment delay or loss. Thus, there is a clear demand for methods that can suppress the problems caused by the wireless environment. Recently, several techniques have been developed to improve end-to-end TCP performance over wireless links. They can be classified into three categories: end-to-end TCP, split TCP and link layer TCP. However, they have not addressed these problems successfully. In this thesis, we propose, design and implement several algorithms that are applicable to the wireless networks in order to solve outstanding problems. Firstly, the research investigates the relationship between packet loss and network congestion and introduces a feedback based end-to-end congestion control algorithm to the wireless network. This algorithm is a modification of a Fair Intelligent Congestion Control (FICC) proposed in [19]. The innovation of the algorithm is to modify the original FICC in such a way that the queue lengths can be effectively controlled when it is jointly employed with TCP in the wireless network. The next algorithm is the new design of Explicit Loss Notification (ELN) at base station in Wired-Cum-Wireless networks. With the combination of new ELN algorithm and Wireless FICC algorithm, the end-to-end performance and fairness are greatly improved by eliminating the misinterpretation of error related lost packets from congestion. Finally, the research investigates the effects of network congestion, which often happens over low bandwidth wireless link, and QoS performance (e.g. fairness, delay variation) of multiple sessions of TCP traffic in a hybrid network. We propose a framework, which consists of two main algorithms, feedback based congestion control and Explicit Window Adaptation (EWA)

Application-Oriented Flow Control: Fundamentals, Algorithms and Fairness

This paper is concerned with flow control and resource allocation problems in computer networks in which real-time applications may have hard quality of service (QoS) requirements. Recent optimal flow control approaches are unable to deal with these problems since QoS utility functions generally do not satisfy the strict concavity condition in real-time applications. For elastic traffic, we show that bandwidth allocations using the existing optimal flow control strategy can be quite unfair. If we consider different QoS requirements among network users, it may be undesirable to allocate bandwidth simply according to the traditional max-min fairness or proportional fairness. Instead, a network should have the ability to allocate bandwidth resources to various users, addressing their real utility requirements. For these reasons, this paper proposes a new distributed flow control algorithm for multiservice networks, where the application's utility is only assumed to be continuously increasing over the available bandwidth. In this, we show that the algorithm converges, and that at convergence, the utility achieved by each application is well balanced in a proportionally (or max-min) fair manner

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms