End-to-End Resilience Mechanisms for Network Transport Protocols

The universal reliance on and hence the need for resilience in network communications has been well established. Current transport protocols are designed to provide fixed mechanisms for error remediation (if any), using techniques such as ARQ, and offer little or no adaptability to underlying network conditions, or to different sets of application requirements. The ubiquitous TCP transport protocol makes too many assumptions about underlying layers to provide resilient end-to-end service in all network scenarios, especially those which include significant heterogeneity. Additionally the properties of reliability, performability, availability, dependability, and survivability are not explicitly addressed in the design, so there is no support for resilience. This dissertation presents considerations which must be taken in designing new resilience mechanisms for future transport protocols to meet service requirements in the face of various attacks and challenges. The primary mechanisms addressed include diverse end-to-end paths, and multi-mode operation for changing network conditions

Enhanced Multimedia Exchanges over the Internet

Although the Internet was not originally designed for exchanging multimedia streams, consumers heavily depend on it for audiovisual data delivery. The intermittent nature of multimedia traffic, the unguaranteed underlying communication infrastructure, and dynamic user behavior collectively result in the degradation of Quality-of-Service (QoS) and Quality-of-Experience (QoE) perceived by end-users. Consequently, the volume of signalling messages is inevitably increased to compensate for the degradation of the desired service qualities. Improved multimedia services could leverage adaptive streaming as well as blockchain-based solutions to enhance media-rich experiences over the Internet at the cost of increased signalling volume. Many recent studies in the literature provide signalling reduction and blockchain-based methods for authenticated media access over the Internet while utilizing resources quasi-efficiently. To further increase the efficiency of multimedia communications, novel signalling overhead and content access latency reduction solutions are investigated in this dissertation including: (1) the first two research topics utilize steganography to reduce signalling bandwidth utilization while increasing the capacity of the multimedia network; and (2) the third research topic utilizes multimedia content access request management schemes to guarantee throughput values for servicing users, end-devices, and the network. Signalling of multimedia streaming is generated at every layer of the communication protocol stack; At the highest layer, segment requests are generated, and at the lower layers, byte tracking messages are exchanged. Through leveraging steganography, essential signalling information is encoded within multimedia payloads to reduce the amount of resources consumed by non-payload data. The first steganographic solution hides signalling messages within multimedia payloads, thereby freeing intermediate node buffers from queuing non-payload packets. Consequently, source nodes are capable of delivering control information to receiving nodes at no additional network overhead. A utility function is designed to minimize the volume of overhead exchanged while minimizing visual artifacts. Therefore, the proposed scheme is designed to leverage the fidelity of the multimedia stream to reduce the largest amount of control overhead with the lowest negative visual impact. The second steganographic solution enables protocol translation through embedding packet header information within payload data to alternatively utilize lightweight headers. The protocol translator leverages a proposed utility function to enable the maximum number of translations while maintaining QoS and QoE requirements in terms of packet throughput and playback bit-rate. As the number of multimedia users and sources increases, decentralized content access and management over a blockchain-based system is inevitable. Blockchain technologies suffer from large processing latencies; consequently reducing the throughput of a multimedia network. Reducing blockchain-based access latencies is therefore essential to maintaining a decentralized scalable model with seamless functionality and efficient utilization of resources. Adapting blockchains to feeless applications will then port the utility of ledger-based networks to audiovisual applications in a faultless manner. The proposed transaction processing scheme will enable ledger maintainers in sustaining desired throughputs necessary for delivering expected QoS and QoE values for decentralized audiovisual platforms. A block slicing algorithm is designed to ensure that the ledger maintenance strategy is benefiting the operations of the blockchain-based multimedia network. Using the proposed algorithm, the throughput and latency of operations within the multimedia network are then maintained at a desired level

Advancing Multimedia: Application Sharing, Latency Measurements and User-Created Services

Online collaboration tools exist and have been used since the early days of the Internet. Asynchronous tools such as wikis and discussion boards and real-time tools such as instant messaging and voice conferencing have been the only viable collaboration solutions up until recently, due to the low bandwidth between participants. With the increasing bandwidth in computer networks, multimedia collaboration such as application sharing and video conferencing have become feasible. Application and desktop sharing allows sharing of any application with one or more people over the Internet. The participants receive the screen-view of the shared application from the server. Their mouse and keyboard events are delivered and regenerated at the server. Application and desktop sharing enables collaborative work, software tutoring, and e-learning over the Internet. I have developed a high performance application and desktop sharing system called BASS which is efficient, reliable, independent of the operating system, scales well via heterogeneous multicast, supports all applications, and features true application sharing. Most of the time an application sharing session requires audio and video conferencing to be more useful. High quality video conferencing requires a fair amount of bandwidth and unfortunately Internet bandwidth of home users is still limited and shared by more than one application and user. Therefore, I measured the performance of popular video conferencing applications under congestion to understand whether they are flexible enough to adapt to fluctuating and limited bandwidth conditions. In particular, I analyzed how Skype, Windows Live Messenger, Eyebeam and X-Lite react to changes in available bandwidth, presence of HTTP and BitTorrent traffic and wireless packet losses. To perform these measurements more effectively, I have also developed vDelay, a novel tool for measuring the capture-to-display latency (CDL) and frame rate of real-time video conferencing sessions. vDelay enables developers and testers to measure the CDL and frame rate of any video conferencing application without modifying the source code. Further, it does not require any specialized hardware. I have used vDelay to measure the CDL and frame rate of popular video chat applications including Skype, Windows Live Messenger, and GMail video chat. vDelay can also be used to measure the CDL and frame rate of these applications in the presence of bandwidth variations. The results from the performance study showed that existing products, such as Skype, adapt to bandwidth fluctuations fairly well and can differentiate wireless and congestion-based packet losses. Therefore, rather than trying to improve video conferencing tools, I changed my focus to end-user created communication-related services to increase the utility of existing stand alone Internet services, devices in the physical world, communication and online social networks. I have developed SECE (Sense Everything, Control Everything), a new language and its supporting software infrastructure for user created services. SECE allows non-technical end-users to create services that combine communication, social networks, presence, calendaring, location and devices in the physical world. SECE is an event-driven system that uses a natural-English-like language to trigger action scripts. Users associate actions with events and when an event happens its associated action is executed. Presence updates, social network updates, incoming calls, email, calendar and time events, sensor inputs and location updates can trigger rules. SECE retrieves all this information from multiple sources to personalize services and to adapt them to changes in the user's context and preferences. Actions can control the delivery of email, change the handling of phone calls, update social network status and set the state of actuators such as lights, thermostats and electrical appliances

Live Streaming with Gossip

Peer-to-peer (P2P) architectures have emerged as a popular paradigm to support the dynamic and scalable nature of distributed systems. This is particularly relevant today, given the tremendous increase in the intensity of information exchanged over the Internet. A P2P system is typically composed of participants that are willing to contribute resources, such as memory or bandwidth, in the execution of a collaborative task providing a benefit to all participants. File sharing is probably the most widely used collaborative task, where each participant wants to receive an individual copy of some file. Users collaborate by sending fragments of the file they have already downloaded to other participants. Sharing files containing multimedia content, files that typically reach the hundreds of megabytes to gigabytes, introduces a number of challenges. Given typical bandwidths of participants of hundreds of kilobits per second to a couple of megabits per second, it is unacceptable to wait until completion of the download before actually being able to use the file as the download represents a non negligible time. From the point of view of the participant, getting the (entire) file as fast as possible is typically not good enough. As one example, Video on Demand (VoD) is a scenario where a participant would like to start previewing the multimedia content (the stream), offered by a source, even though only a fraction of it has been received, and then continue the viewing while the rest of the content is being received. Following the same line of reasoning, new applications have emerged that rely on live streaming: the source does not own a file that it wants to share with others, but shares content as soon as it is produced. In other words, the content to distribute is live, not pre-recorded and stored. Typical examples include the broadcasting of live sports events, conferences or interviews. The gossip paradigm is a type of data dissemination that relies on random communication between participants in a P2P system, sharing similarities with the epidemic dissemination of diseases. An epidemic starts to spread when the source randomly chooses a set of communication partners, of size fanout, and infects them, i.e., it shares a rumor with them. This set of participants, in turn, randomly picks fanout communication partners each and infects them, i.e., share with them the same rumor. This paradigm has many advantages including fast propagation of rumors, a probabilistic guarantee that each rumor reaches all participants, high resilience to churn (i.e., participants that join and leave) and high scalability. Gossip therefore constitutes a candidate of choice for live streaming in large-scale systems. These advantages, however, come at a price. While disseminating data, gossip creates many duplicates of the same rumor and participants usually receive multiple copies of the same rumor. While this is obviously a feature when it comes to guaranteeing good dissemination of the rumor when churn is high, it is a clear disadvantage when spreading large amounts of multimedia data (i.e., ordered and time-critical) to participants with limited resources, namely upload bandwidth in the case of high-bandwidth content dissemination. This thesis therefore investigates if and how the gossip paradigm can be used as a highly effcient communication system for live streaming under the following specific scenarios: (i) where participants can only contribute limited resources, (ii) when these limited resources are heterogeneously distributed among nodes, and (iii) where only a fraction of participants are contributing their fair share of work while others are freeriding. To meet these challenges, this thesis proposes (i) gossip++: a gossip-based protocol especially tailored for live streaming that separates the dissemination of metadata, i.e., the location of the data, and the dissemination of the data itself. By first spreading the location of the content to interested participants, the protocol avoids wasted bandwidth in sending and receiving duplicates of the payload, (ii) HEAP: a fanout adaptation mechanism that enables gossip to adapt participants' contribution with respect to their resources while still preserving its reliability, and (iii) LiFT: a protocol to secure high-bandwidth gossip-based dissemination protocols against freeriders

Adaptive Voice Applications over Delay Tolerant Networks

Internet is predominantly based on best effort packet transmission. Performance of applications over internet suffers due to disconnections, delays, losses and dynamic nature of elements in the network. Voice communications, such as Voice over Internet Protocols (VoIP), over mobile networks has to deal with technical barriers such as delays and temporary disconnections. Delay tolerant networks provides communication based on asynchronous messaging that deals with delays and disconnections; which provides a mechanism to deliver the messages irrespective of instantaneous end-to-end path connectivity. In the thesis, delay tolerant adaptive media is proposed to allow DTN-based communication as a fall-back if real time end-to-end voice communication fails. We designed a system which adapts to delays and losses by switching between RTP/UDP and RTP/DTN-based voice packets transmission. The real time communication works fine as long as continuous end-to-end path exists. The continuous path might not exist when there are changes in the network topology of mobile users. So in the case of non-availability of end-to-end path, we swiftly adapt to RTP/DTN-based voice with variable length messaging mechanism. To assess the call quality in different modes of operation, we used R values of E model specified by ITU-T. The results show that the proposed delay tolerant adaptive media for adaptive voice over delay tolerant networks achieves better utility for the users when end-to-end connectivity is not available or when delays are higher

Dynamic adaptive video streaming with minimal buffer sizes

Recently, adaptive streaming has been widely adopted in video streaming services to improve the Quality-of-Experience (QoE) of video delivery over the Internet. However, state-of-the-art bitrate adaptation achieves satisfactory performance only with extensive buffering of several tens of seconds. This leads to high playback latency in video delivery, which is undesirable especially in the context of live content with a low upper bound on the latency. Therefore, this thesis aims at pushing the application of adaptive streaming to its limit with respect to the buffer size, which is the dominant factor of the streaming latency. In this work, we first address the minimum buffering size required in adaptive streaming, which provides us with guidelines to determine a reasonable low latency for streaming systems. Then, we tackle the fundamental challenge of achieving such a low-latency streaming by developing a novel adaptation algorithm that stabilizes buffer dynamics despite a small buffer size. We also present advanced improvements by designing a novel adaptation architecture with low-delay feedback for the bitrate selection and optimizing the underlying transport layer to offer efficient realtime streaming. Experimental evaluations demonstrate that our approach achieves superior QoE in adaptive video streaming, especially in the particularly challenging case of low-latency streaming.In letzter Zeit setzen immer mehr Anbieter von Video-Streaming im Internet auf adaptives Streaming um die Nutzererfahrung (QoE) zu verbessern. Allerdings erreichen aktuelle Bitrate-Adaption-Algorithmen nur dann eine zufriedenstellende Leistung, wenn sehr große Puffer in der Größenordnung von mehreren zehn Sekunden eingesetzt werden. Dies führt zu großen Latenzen bei der Wiedergabe, was vor allem bei Live-Übertragungen mit einer niedrigen Obergrenze für Verzögerungen unerwünscht ist. Aus diesem Grund zielt die vorliegende Dissertation darauf ab adaptive Streaming-Anwendung im Bezug auf die Puffer-Größe zu optimieren da dies den Hauptfaktor für die Streaming-Latenz darstellt. In dieser Arbeit untersuchen wir zuerst die minimale benötigte Puffer-Größe für adaptives Streaming, was uns ermöglicht eine sinnvolle Untergrenze für die erreichbare Latenz festzulegen. Im nächsten Schritt gehen wir die grundlegende Herausforderung an dieses Optimum zu erreichen. Hierfür entwickeln wir einen neuartigen Adaptionsalgorithmus, der es ermöglicht den Füllstand des Puffers trotz der geringen Größe zu stabilisieren. Danach präsentieren wir weitere Verbesserungen indem wir eine neue Adaptions-Architektur für die Datenraten-Anpassung mit geringer Feedback-Verzögerung designen und das darunter liegende Transportprotokoll optimieren um effizientes Echtzeit-Streaming zu ermöglichen. Durch experimentelle Prüfung zeigen wir, dass unser Ansatz eine verbesserte Nutzererfahrung für adaptives Streaming erreicht, vor allem in besonders herausfordernden Fällen, wenn Streaming mit geringer Latenz gefordert ist

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

Resource allocation and adaptive scheduling for scalable video streaming

The obvious recent advances in areas such as video compression and network architectures allow for the deployment of novel video distribution applications. These have the potential to provide ubiquitous media access to end users. In recent years, applications based on audio and video streaming have turned out to be immensely popular and the Internet has become the most widely used vector for media content distribution, due to its high availability and connectivity. However, the nature of the Internet infrastructure is not adapted to the specific characteristics of multimedia traffic, which presents a certain tolerance to losses, but strict delay and high bandwidth requirements. In this thesis, our goal is to improve the efficiency of media delivery over the existing network architecture. In order to do so we consider the delivery of scalable video in three main delivery scenarios, namely one-to-one client server architectures, one-to-many broadcasting architectures, and many-to-one distributed streaming architectures. First, we propose a distributed media-friendly rate allocation algorithm for the delivery of both finely and coarsely scalable video streams. Unlike existing solutions, our algorithm explicitly takes the characteristics of media streams into consideration. As a result, it provides rate allocations that better fit the heterogeneous characteristics of media streams. We outline an implementation that is robust to random feedback delays and that permits a scalable deployment of the algorithm. The rate allocation that is computed by our algorithm achieves network stability and high bandwidth utilization. It moreover allows to maximize the average received quality for all streams that are delivered in the network. While considering the transmission of coarsely layered streams, we derive conditions on the encoding rates of the video layers. These conditions depend on the allowed end-to-end delay and on the rate allocation algorithm that controls the sending rates. They allow us to take full advantage of the allocated transmission rates. Second, we investigate the problem of jointly addressing the needs of multiple receivers that consume different versions of a layered media stream in a broadcasting scenario. We provide optimal scheduling algorithms that jointly optimize the playback delay and the buffer occupancy at all of these receivers when the used channel is known. Furthermore we analyze low complexity heuristics based optimization techniques, which provide close to optimal results when only limited channel knowledge is available. Finally, we explore the possibility to exploit the inherent network diversity that is provided by the Internet infrastructure. In particular, we consider media delivery schemes where multiple senders are available for the transmission of a scalable video stream to a single client. Such an architecture is referred to as a distributed streaming architecture. It has the benefit of aggregating multiple unreliable channels into a single more robust channel with high availability. Through the use of Fountain codes, we are able to transform the distributed streaming problem into a rate allocation problem of lower complexity. The solution to this problem is shown to depend not only on the average packet loss rate, but also on the average length of packet loss bursts that are observed on each of the available channels. The coding scheme that we suggest enables our system to adapt the streamed content to the network characteristics, as well as to the needs of the receiving client