Scalable reliable on-demand media streaming protocols

This thesis considers the problem of delivering streaming media, on-demand, to potentially large numbers of concurrent clients. The problem has motivated the development in prior work of scalable protocols based on multicast or broadcast. However, previous protocols do not allow clients to efficiently: 1) recover from packet loss; 2) share bandwidth fairly with competing flows; or 3) maximize the playback quality at the client for any given client reception rate characteristics. In this work, new protocols, namely Reliable Periodic Broadcast (RPB) and Reliable Bandwidth Skimming (RBS), are developed that efficiently recover from packet loss and achieve close to the best possible server bandwidth scalability for a given set of client characteristics. To share bandwidth fairly with competing traffic such as TCP, these protocols can employ the Vegas Multicast Rate Control (VMRC) protocol proposed in this work. The VMRC protocol exhibits TCP Vegas-like behavior. In comparison to prior rate control protocols, VMRC provides less oscillatory reception rates to clients, and operates without inducing packet loss when the bottleneck link is lightly loaded. The VMRC protocol incorporates a new technique for dynamically adjusting the TCP Vegas threshold parameters based on measured characteristics of the network. This technique implements fair sharing of network resources with other types of competing flows, including widely deployed versions of TCP such as TCP Reno. This fair sharing is not possible with the previously defined static Vegas threshold parameters. The RPB protocol is extended to efficiently support quality adaptation. The Optimized Heterogeneous Periodic Broadcast (HPB) is designed to support a range of client reception rates and efficiently support static quality adaptation by allowing clients to work-ahead before beginning playback to receive a media file of the desired quality. A dynamic quality adaptation technique is developed and evaluated which allows clients to achieve more uniform playback quality given time-varying client reception rates

Comparative Study on the Performance of Different TCP Flavors

Indeed the Transmission Control Protocol (TCP) is the main transport layer protocol for the end-to-end control that helps the creation of information communication. Most of today`s Internet applications depend on the Performance TCP simply because the most frequently used networks by today are the TCP/IP networks. TCP was originally created to handle the problem of network congestion collapse. In this research project, we had investigated the performance of four TCP variants namely Reno, Vegas, NewReno and SACK based on two performance measures: The Bandwidth (effective throughput) and fairness. The network topology is simple wired network and it will be configured into different scenarios to maximize the chances of achieving the desired goal. Simulation methodology is used in this study. The simulation tool or software that was used as an investigation environment is the popular NS-2 simulator. The objective was to investigate and find out the performance of TCP variants according to the bandwidth and fairness in a simple dumbbell wired network, in a hope to observe a better performance.However, the results are daunting, TCP Reno is the most aggressive (least fair one), and highest amount of throughput. In the case of TCP NewReno it follows Reno’s steps by becoming the second most aggressive (second least fair), and second highest throughput.SACK (Sack1) is fair to Reno and NewReno, but when it is competing with Vegas, it shows that it is very unfair. Finally Vegas shows the highest degree of fairness (least aggressive) and as well Vegas produces the lowest amount throughput

Necessary and sufficient conditions for optimal flow control in multirate multicast networks

The authors consider the optimal flow control problem in multirate multicast networks where all receivers of the same multicast group can receive service at different rates with different QoS. The objective is to achieve the fairness transmission rates that maximise the total receiver utility under the capacity constraint of links. They first propose necessary and sufficient conditions for the optimal solution to the problem, and then derive a new optimal flow control strategy using the Lagrangian multiplier method. Like the unicast case, the basic algorithm consists of a link algorithm to update the link price, and a receiver algorithm to adapt the transmission rate according to the link prices along its path. In particular if some groups contain only one receiver and become unicast, the algorithm will degrade to their previously proposed unicast algorithm

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

Active congestion control using ABCD (available bandwidth-based congestion detection).

With the growth of the Internet, the problem of congestion has attained the distinction of being a perennial problem. The Internet community has been trying several approaches for improved congestion control techniques. The end-to-end approach is considered to be the most robust one and it has served quite well until recently, when researchers started to explore the information available at the intermediate node level. This approach triggered a new field called Active Networks where intermediate nodes have a much larger role to play than that of the naive nodes. This thesis proposes an active congestion control (ACC) scheme based on Available Bandwidth-based Congestion Detection (ABCD), which regulates the traffic according to network conditions. Dynamic changes in the available bandwidth can trigger re-negotiation of flow rate. We have introduced packet size adjustment at the intermediate router in addition to rate control at sender node, scaled according to the available bandwidth, which is estimated using three packet probes. To verify the improved scheme, we have extended Ted Faber\u27s ACC work in NS-2 simulator. With this simulator we verify ACC-ABCD\u27s gains such as a marginal improvement in average TCP throughput at each endpoint, fewer packet drops and improved fairness index. Our tests on NS-2 prove that the ACC-ABCD technique yields better results as compared to TCP congestion control with or without the cross traffic. Source: Masters Abstracts International, Volume: 43-03, page: 0870. Adviser: A. K. Aggarwal. Thesis (M.Sc.)--University of Windsor (Canada), 2004

Dealing with Heterogeneity in a Fully Reliable Multicast Protocol

Many of the proposed multicast congestion avoidance algorithms are single-rate where heterogeneity is accommodated by adjusting the transmission rate as a response to the worst receiver in the group. Due to the Internet heterogeneity, a single-rate congestion co ntrol affects the overall satisfaction of the receivers in a multicast session. In this paper, we propose a multi-rate replicated scheme where some receivers (instead of the source) are designated to perform data replication for other receivers with lower capacity. To be more scalable and to minimize the bandwidth consumption due to data replication, the partitioning algorithm is per- formed on-the-fly by the routers depending on the feedback they receive. Neither a prior estimation of the receivers capacity is necessary nor a complex computation is required to execute our partitioning algorithm