Scalable download protocols

Scalable on-demand content delivery systems, designed to effectively handle increasing request rates, typically use service aggregation or content replication techniques. Service aggregation relies on one-to-many communication techniques, such as multicast, to efficiently deliver content from a single sender to multiple receivers. With replication, multiple geographically distributed replicas of the service or content share the load of processing client requests and enable delivery from a nearby server.Previous scalable protocols for downloading large, popular files from a single server include batching and cyclic multicast. Analytic lower bounds developed in this thesis show that neither of these protocols consistently yields performance close to optimal. New hybrid protocols are proposed that achieve within 20% of the optimal delay in homogeneous systems, as well as within 25% of the optimal maximum client delay in all heterogeneous scenarios considered.In systems utilizing both service aggregation and replication, well-designed policies determining which replica serves each request must balance the objectives of achieving high locality of service, and high efficiency of service aggregation. By comparing classes of policies, using both analysis and simulations, this thesis shows that there are significant performance advantages in using current system state information (rather than only proximities and average loads) and in deferring selection decisions when possible. Most of these performance gains can be achieved using only “local” (rather than global) request information.Finally, this thesis proposes adaptations of already proposed peer-assisted download techniques to support a streaming (rather than download) service, enabling playback to begin well before the entire media file is received. These protocols split each file into pieces, which can be downloaded from multiple sources, including other clients downloading the same file. Using simulations, a candidate protocol is presented and evaluated. The protocol includes both a piece selection technique that effectively mediates the conflict between achieving high piece diversity and the in-order requirements of media file playback, as well as a simple on-line rule for deciding when playback can safely commence

Partitioning and Offloading for IoT and Video Streaming Applications that Utilize Computing Resources at the Network Edge

The Internet of Things (IoT) is a concept in which physical objects embedded with sensors, actuators, and network connectivity can communicate and react to their surroundings. IoT applications connect physical objects for the purpose of decision making by sensing and analysing generated data from the embedded sensors in physical objects. IoT applications are growing rapidly as sensors become less expensive. Sensors generate large amounts of data that may meaningless unless the data is used to derive knowledge with in a certain period of time. Stream processing paradigm is used by IoT to provide requirements of IoT applications. In a stream processing paradigm, unlike traditional data bases, data is not stored but rather processed as it is generated. To transfer generated data from distributed data sources to a processing center such as cloud may not allow for real-time processing due to the network delay. Another high-demand application is live streaming of video. The performance of live video stream systems is inferior when there is a sudden large demand in the number of users. This thesis addresses some of the limitations of current architectures for video streaming systems and IoT applications based on the use of nearby computing resources (e.g., cloudlet, fog). First, we addressed the degrading performance in video stream systems when a flash crowd occurs. The performance of video streaming systems is affected by flash crowd and degrade the quality of service for subscribers to the content delivery system. A flash crowd happens when there is a sudden large increase in the number of users. Therefore, flash crowds increase network traffic for any particular server. The main challenge is to make sure that the video streaming system has sufficient capacity to handle the occurrence of flash crowds. Second, we address the limitation of current architectures for running mobile applications by introducing a dynamic partitioning and offloading of a mobile application. Mobile devices have limited resources including short battery life, storage capacity and processor performance. This limits the applications that can run on it. Mobile applications can be partitioned so that some of the application runs on a cloud. This works well for applications with relatively little data to be transferred and that do not have a high level of interaction with the user. Challenges with applications that have large amounts of data to be transferred and have a high level interactiveness is the high latency incurred by the network and packet loss of the wireless network. A mobile application can be partitioned so that part of it runs on a nearby computing resource e.g., fog node or cloudlet. This thesis presents a framework that introduces fine-grained offloading approach and support for runtime and dynamic partitioning of an application. Third, we present a solution for placement of stream operators over distributed fog nodes for live processing of data streams from geographically distributed data sources. This placement of stream operators takes place in such a way that it supports applications with a high volume of data that require real-time (or near real-time) analysis To this end, this thesis proposed a set of algorithms for placement of stream operators among fog nodes

Proactive Mechanisms for Video-on-Demand Content Delivery

Video delivery over the Internet is the dominant source of network load all over the world. Especially VoD streaming services such as YouTube, Netflix, and Amazon Video have propelled the proliferation of VoD in many peoples' everyday life. VoD allows watching video from a large quantity of content at any time and on a multitude of devices, including smart TVs, laptops, and smartphones. Studies show that many people under the age of 32 grew up with VoD services and have never subscribed to a traditional cable TV service. This shift in video consumption behavior is continuing with an ever-growing number of users. satisfy this large demand, VoD service providers usually rely on CDN, which make VoD streaming scalable by operating a geographically distributed network of several hundreds of thousands of servers. Thereby, they deliver content from locations close to the users, which keeps traffic local and enables a fast playback start. CDN experience heavy utilization during the day and are usually reactive to the user demand, which is not optimal as it leads to expensive over-provisioning, to cope with traffic peaks, and overreacting content eviction that decreases the CDN's performance. However, to sustain future VoD streaming projections with hundreds of millions of users, new approaches are required to increase the content delivery efficiency. To this end, this thesis identifies three key research areas that have the potential to address the future demand for VoD content. Our first contribution is the design of vFetch, a privacy-preserving prefetching mechanism for mobile devices. It focuses explicitly on OTT VoD providers such as YouTube. vFetch learns the user interest towards different content channels and uses these insights to prefetch content on a user terminal. To do so, it continually monitors the user behavior and the device's mobile connectivity pattern, to allow for resource-efficient download scheduling. Thereby, vFetch illustrates how personalized prefetching can reduce the mobile data volume and alleviate mobile networks by offloading peak-hour traffic. Our second contribution focuses on proactive in-network caching. To this end, we present the design of the ProCache mechanism that divides the available cache storage concerning separate content categories. Thus, the available storage is allocated to these divisions based on their contribution to the overall cache efficiency. We propose a general work-flow that emphasizes multiple categories of a mixed content workload in addition to a work-flow tailored for music video content, the dominant traffic source on YouTube. Thereby, ProCache shows how content-awareness can contribute to efficient in-network caching. Our third contribution targets the application of multicast for VoD scenarios. Many users request popular VoD content with only small differences in their playback start time which offers a potential for multicast. Therefore, we present the design of the VoDCast mechanism that leverages this potential to multicast parts of popular VoD content. Thereby, VoDCast illustrates how ISP can collaborate with CDN to coordinate on content that should be delivered by ISP-internal multicast

Peer-to-peer stream merging for stored multimedia

In recent years, with the fast development of resource capability of both the Internet and personal computers, multimedia applications like video-on-demand (VOD) streaming have gained dramatic growth and been shown to be potential killer applications in the current and next-generation Internet. Scalable deployment of these applications has become a hot problem area due to the potentially high server and network bandwidth required in these systems.The conventional approach in a VOD streaming system dedicates a media stream for each client request, which is not scalable in a wide-area delivery system serving potentially very large numbers of clients. Recently, various efficient delivery techniques have been proposed to improve the scalability of VOD delivery systems. One approach is to use a scalable delivery protocol based on multicast, such as periodic broadcast or stream merging. These protocols have been mostly developed for single-server based systems and attempt to have each media stream serve as many clients as possible, so as to minimize the required server and network bandwidth. However, the performance improvements possible with techniques that deliver all streams from a single server are limited, especially regarding the required network bandwidth. Another approach is based on proxy caching and content replication, such as in content delivery networks (CDN). Although this approach is able to effectively distribute load across multiple CDN servers, the cost of this approach may be high.With the focus on further improving the system efficiency regarding the server and network bandwidth requirement, a new scalable streaming protocol is developed in this work. It adapts a previously proposed technique called hierarchical multicast stream merging (HMSM) to use a peer-to-peer delivery approach. To be more efficient in media delivery, the conventional early merging policy associated with HMSM is extended to be compatible with the peer-to-peer environment, and various peer selection policies are designed for initiation of media streams. The impact of limited peer resource capability is also studied in this work. In the performance study, a number of simulation experiments are conducted to evaluate the performance of the new protocol and various design policies, and promising results are reported

Planification et dimensionnement des réseaux optiques de longues distances

Le projet de recherche porte sur l'étude des problèmes de conception et de planification d'un réseau optique de longue distance, aussi appelé réseau de coeur (OWAN-Optical Wide Area Network en anglais). Il s'agit d'un réseau qui transporte des flots agrégés en mode commutation de circuits. Un réseau OWAN relie différents sites à l'aide de fibres optiques connectées par des commutateurs/routeurs optiques et/ou électriques. Un réseau OWAN est maillé à l'échelle d'un pays ou d’un continent et permet le transit des données à très haut débit. Dans une première partie du projet de thèse, nous nous intéressons au problème de conception de réseaux optiques agiles. Le problème d'agilité est motivé par la croissance de la demande en bande passante et par la nature dynamique du trafic. Les équipements déployés par les opérateurs de réseaux doivent disposer d'outils de configuration plus performants et plus flexibles pour gérer au mieux la complexité des connexions entre les clients et tenir compte de la nature évolutive du trafic. Souvent, le problème de conception d'un réseau consiste à prévoir la bande passante nécessaire pour écouler un trafic donné. Ici, nous cherchons en plus à choisir la meilleure configuration nodale ayant un niveau d'agilité capable de garantir une affectation optimale des ressources du réseau. Nous étudierons également deux autres types de problèmes auxquels un opérateur de réseau est confronté. Le premier problème est l'affectation de ressources du réseau. Une fois que l'architecture du réseau en termes d'équipements est choisie, la question qui reste est de savoir : comment dimensionner et optimiser cette architecture pour qu'elle rencontre le meilleur niveau possible d'agilité pour satisfaire toute la demande. La définition de la topologie de routage est un problème d'optimisation complexe. Elle consiste à définir un ensemble de chemins optiques logiques, choisir les routes physiques suivies par ces derniers, ainsi que les longueurs d'onde qu'ils utilisent, de manière à optimiser la qualité de la solution obtenue par rapport à un ensemble de métriques pour mesurer la performance du réseau. De plus, nous devons définir la meilleure stratégie de dimensionnement du réseau de façon à ce qu'elle soit adaptée à la nature dynamique du trafic. Le second problème est celui d'optimiser les coûts d'investissement en capital(CAPEX) et d'opération (OPEX) de l'architecture de transport proposée. Dans le cas du type d'architecture de dimensionnement considérée dans cette thèse, le CAPEX inclut les coûts de routage, d'installation et de mise en service de tous les équipements de type réseau installés aux extrémités des connexions et dans les noeuds intermédiaires. Les coûts d'opération OPEX correspondent à tous les frais liés à l'exploitation du réseau de transport. Étant donné la nature symétrique et le nombre exponentiel de variables dans la plupart des formulations mathématiques développées pour ces types de problèmes, nous avons particulièrement exploré des approches de résolution de type génération de colonnes et algorithme glouton qui s'adaptent bien à la résolution des grands problèmes d'optimisation. Une étude comparative de plusieurs stratégies d'allocation de ressources et d'algorithmes de résolution, sur différents jeux de données et de réseaux de transport de type OWAN démontre que le meilleur coût réseau est obtenu dans deux cas : une stratégie de dimensionnement anticipative combinée avec une méthode de résolution de type génération de colonnes dans les cas où nous autorisons/interdisons le dérangement des connexions déjà établies. Aussi, une bonne répartition de l'utilisation des ressources du réseau est observée avec les scénarios utilisant une stratégie de dimensionnement myope combinée à une approche d'allocation de ressources avec une résolution utilisant les techniques de génération de colonnes. Les résultats obtenus à l'issue de ces travaux ont également démontré que des gains considérables sont possibles pour les coûts d'investissement en capital et d'opération. En effet, une répartition intelligente et hétérogène de ressources d’un réseau sur l'ensemble des noeuds permet de réaliser une réduction substantielle des coûts du réseau par rapport à une solution d'allocation de ressources classique qui adopte une architecture homogène utilisant la même configuration nodale dans tous les noeuds. En effet, nous avons démontré qu'il est possible de réduire le nombre de commutateurs photoniques tout en satisfaisant la demande de trafic et en gardant le coût global d'allocation de ressources de réseau inchangé par rapport à l'architecture classique. Cela implique une réduction substantielle des coûts CAPEX et OPEX. Dans nos expériences de calcul, les résultats démontrent que la réduction de coûts peut atteindre jusqu'à 65% dans certaines jeux de données et de réseau.The research project focuses on the design and planning problems of long distance optical networks also called OWANs (Optical Wide Area Networks) or "backbone". These are networks that carry aggregate flows in circuit switching mode. OWAN networks connect sites with optical fibers, cross-connected by optical and/or electric switches/routers. OWAN networks are meshed throughout a country or continent and allow the transit of data at very high speed. In the first part of the thesis, we are interested in the design problem of agile optical networks. The problem of agility is motivated by the growing of bandwidth demand and by the dynamic pattern of client traffic. Equipment deployed by network operators must allow greater reconfigurability and scalability to manage the complexity of connections among clients and deal with a dynamic traffic pattern. Often, the problem of network design is to provide the required bandwidth to grant a given traffic pattern. Here, we seek to choose the best nodal configuration with the agility level that can guarantee the optimal network resource provisioning. We will also study two other types of problems that can face a network operator. The first problem is the network resource provisioning. Once the network architecture design is chosen, the remaining question is : How to resize and optimize the architecture to meet the agility level required to grant any demand. The definition of the network provisioning scheme is a complex optimization problem. It consists of defining a set of optical paths, choosing the routes followed by them, and their assigned wavelengths, so as to optimize the solution quality with respect to some network metrics. Moreover, we need to define the best design strategy adapted to the dynamic traffic pattern. The second problem is to optimize the capital investment cost (CAPEX) and the operational expenses (OPEX) of the selected optical transport architecture. In the case of the design architecture considered in this thesis, the CAPEX includes the routing cost, the installation cost and the commissioning service cost for all required network equipment in end connections and intermediate nodes. OPEX correspond to expenses related to the operation of the transport network. Given the symmetrical nature and the exponential number of variables in most mathematical formulations developed for these types of problems, we particularly explored solving approaches based on a column generation algorithm and greedy heuristics which adapt well to these types of modeling and large scale mathematical models. A comparative study of several provisioning strategies and solution algorithms on different traffic and OWAN network instances show that the minimum network cost is obtained in two cases : An anticipative dimensioning strategy combined with a column generation solution combined with a rounding off heuristic in the context of no disturbance or possible disturbance of previously granted connections. Also, a good repartition of used network resources (MSPPs, PXC and wavelengths) is observed with the scenarios using a myopic strategy and a column generation solution approach. The results obtained from this thesis also show that a considerable saving in CAPEX and OPEX costs are possible in the case of an intelligent allocation and heteregenous distribution of network resources through network nodes compared with the classical architecture that adopts a uniform architecture using the same configuration in all nodes. Indeed, we demonstrated that it is possible to reduce the number of PXCs (Photonic Switches) while satisfying the traffic matrix and keeping the overall cost of provisioning network unchanged compared to what is happening in a classic architecture. This implies a substantial reduction in network CAPEX and OPEX costs. In our experiments with various network and traffic instances, we show that a careful dimensioning and location of the nodal equipment can save up to 65% of network expenses

Large-scale sensor-rich video management and delivery

Ph.DDOCTOR OF PHILOSOPH

Investigating the Effects of Network Dynamics on Quality of Delivery Prediction and Monitoring for Video Delivery Networks

Video streaming over the Internet requires an optimized delivery system given the advances in network architecture, for example, Software Defined Networks. Machine Learning (ML) models have been deployed in an attempt to predict the quality of the video streams. Some of these efforts have considered the prediction of Quality of Delivery (QoD) metrics of the video stream in an effort to measure the quality of the video stream from the network perspective. In most cases, these models have either treated the ML algorithms as black-boxes or failed to capture the network dynamics of the associated video streams. This PhD investigates the effects of network dynamics in QoD prediction using ML techniques. The hypothesis that this thesis investigates is that ML techniques that model the underlying network dynamics achieve accurate QoD and video quality predictions and measurements. The thesis results demonstrate that the proposed techniques offer performance gains over approaches that fail to consider network dynamics. This thesis results highlight that adopting the correct model by modelling the dynamics of the network infrastructure is crucial to the accuracy of the ML predictions. These results are significant as they demonstrate that improved performance is achieved at no additional computational or storage cost. These techniques can help the network manager, data center operatives and video service providers take proactive and corrective actions for improved network efficiency and effectiveness

Content Replication and Placement Schemes for Wireless Mesh Networks

Recently, Wireless Mesh Networks (WMNs) have attracted much of interest from both academia and industry, due to their potential to provide an alternative broadband wireless Internet connectivity. However, due to different reasons such as multi-hop forwarding and the dynamic wireless link characteristics, the performance of current WMNs is rather low when clients are soliciting Web contents. Due to the evolution of advanced mobile computing devices; it is anticipated that the demand for bandwidth-onerous popular content (especially multimedia content) in WMNs will dramatically increase in the coming future. Content replication is a popular approach for outsourcing content on behalf of the origin content provider. This area has been well explored in the context of the wired Internet, but has received comparatively less attention from the research community when it comes to WMNs. There are a number of replica placement algorithms that are specifically designed for the Internet. But they do not consider the special features of wireless networks such as insufficient bandwidth, low server capacity, contention to access the wireless medium, etc. This thesis studies the technical challenges encountered when transforming the traditional model of multi-hop WMNs from an access network into a content network. We advance the thesis that support from packet relaying mesh routers to act as replica servers for popular content such as media streaming, results in significant performance improvement. Such support from infrastructure mesh routers benefits from knowledge of the underlying network topology (i.e., information about the physical connections between network nodes is available at mesh routers). The utilization of cross-layer information from lower layers opens the door to developing efficient replication schemes that account for the specific features of WMNs (e.g., contention between the nodes to access the wireless medium and traffic interference). Moreover, this can benefit from the underutilized resources (e.g., storage and bandwidth) at mesh routers. This utilization enables those infrastructure nodes to participate in content distribution and play the role of replica servers. In this thesis, our main contribution is the design of two lightweight, distributed, and scalable object replication schemes for WMNs. The first scheme follows a hierarchical approach, while the second scheme follows a flat one. The challenge is to replicate content as close as possible to the requesting clients and thus, reduce the access latency per object, while minimizing the number of replicas. The two schemes aim to address the questions of where and how many replicas should be placed in the WMN. In our schemes, we consider the underlying topology joint with link-quality metrics to improve the quality of experience. We show using simulation tests that the schemes significantly enhance the performance of a WMN in terms of reducing the access cost, bandwidth consumption and computation/communication cost

Recent Trends in Communication Networks

In recent years there has been many developments in communication technology. This has greatly enhanced the computing power of small handheld resource-constrained mobile devices. Different generations of communication technology have evolved. This had led to new research for communication of large volumes of data in different transmission media and the design of different communication protocols. Another direction of research concerns the secure and error-free communication between the sender and receiver despite the risk of the presence of an eavesdropper. For the communication requirement of a huge amount of multimedia streaming data, a lot of research has been carried out in the design of proper overlay networks. The book addresses new research techniques that have evolved to handle these challenges