Adaptive Resource Management Schemes for Web Services

Web cluster systems provide cost-effective solutions when scalable and reliable web services are required. However, as the number of servers in web cluster systems increase, web cluster systems incur long and unpredictable delays to manage servers. This study presents the efficient management schemes for web cluster systems. First of all, we propose an efficient request distribution scheme in web cluster systems. Distributor-based systems forward user requests to a balanced set of waiting servers in complete transparency to the users. The policy employed in forwarding requests from the frontend distributor to the backend servers plays an important role in the overall system performance. In this study, we present a proactive request distribution (ProRD) to provide an intelligent distribution at the distributor. Second, we propose the heuristic memory management schemes through a web prefetching scheme. For this study, we design a Double Prediction-by-Partial-Match Scheme (DPS) that can be adapted to the modern web frameworks. In addition, we present an Adaptive Rate Controller (ARC) to determine the prefetch rate depending on the memory status dynamically. For evaluating the prefetch gain in a server node, we implement an Apache module. Lastly, we design an adaptive web streaming system in wireless networks. The rapid growth of new wireless and mobile devices accessing the internet has contributed to a whole new level of heterogeneity in web streaming systems. Particularly, in-home networks have also increased in heterogeneity by using various devices such as laptops, cell phone and PDAs. In our study, a set-top box(STB) is the access pointer between the internet and a home network. We design an ActiveSTB which has a capability of buffering and quality adaptation based on the estimation for the available bandwidth in the wireless LAN

Middleware for Large-scale Distributed Systems

Nos últimos anos o aumento exponencial da utilização de dispositivos móveis e serviços disponibilizados na “Cloud” levou a que a forma como os sistemas são desenhados e implementados mudasse, numa perspectiva de tentar alcançar requisitos que até então não eram essenciais. Analisando esta evolução, com o enorme aumento dos dispositivos móveis, como os “smartphones” e “tablets” fez com que o desenho e implementação de sistemas distribuidos fossem ainda mais importantes nesta área, na tentativa de promover sistemas e aplicações que fossem mais flexíveis, robutos, escaláveis e acima de tudo interoperáveis. A menor capacidade de processamento ou armazenamento destes dispositivos tornou essencial o aparecimento e crescimento de tecnologias que prometem solucionar muitos dos problemas identificados. O aparecimento do conceito de Middleware visa solucionar estas lacunas nos sistemas distribuidos mais evoluídos, promovendo uma solução a nível de organização e desenho da arquitetura dos sistemas, ao memo tempo que fornece comunicações extremamente rápidas, seguras e de confiança. Uma arquitetura baseada em Middleware visa dotar os sistemas de um canal de comunicação que fornece uma forte interoperabilidade, escalabilidade, e segurança na troca de mensagens, entre outras vantagens. Nesta tese vários tipos e exemplos de sistemas distribuídos e são descritos e analisados, assim como uma descrição em detalhe de três protocolos (XMPP, AMQP e DDS) de comunicação, sendo dois deles (XMPP e AMQP) utilzados em projecto reais que serão descritos ao longo desta tese. O principal objetivo da escrita desta tese é demonstrar o estudo e o levantamento do estado da arte relativamente ao conceito de Middleware aplicado a sistemas distribuídos de larga escala, provando que a utilização de um Middleware pode facilitar e agilizar o desenho e desenvolvimento de um sistema distribuído e traz enormes vantagens num futuro próximo.Over the last few years the designing and implementation of applications have evolved to a new breed of applications that are used by a huge number of users at the same time and are capable of being executed in up to thousands of machines physically distributed, even geographically, such as the cloud computing systems, the new concept of “big data” and smart cities. The existence of several components of these systems, distributed in independent machines, brings inevitable issues in terms of designing and implementation of those systems in order to achieve flexible, scalable, robust, reliable and interoperable systems. It is extremely important to design and implement systems that can be capable of providing a communication and coordination among all the components of the system. The concept of implementing a Middleware seems to be a great option to solve most of these issues, allowing a system to communicate with other systems in a really fast, robust and secure way. This thesis pretends to demonstrate that the usage of Middleware technologies to ensure the communication in distributed systems brings a huge number of advantages, such as interoperability between systems, robustness regarding the communication layer, scalability and high speed communications

Quality of experience and access network traffic management of HTTP adaptive video streaming

The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming

Improving Mobile Network Performance Through Measurement-driven System Design Approaches

Mobile networks are complex, dynamic, and often perform poorly. Many factors affect network performance and energy consumption: examples include highly varying network latencies and loss rates, diurnal user movement patterns in cellular networks that impact network congestion, and how radio energy states interacts with application traffic. Because mobile devices experience uniquely dynamic and complex network conditions and resource tradeoffs, incorporating ongoing, continuous measurements of network performance, resource usage and user and app behavior into mobile systems is essential in addressing the pervasive performance problems in these systems. This dissertation examines five different approaches to this problem. First, we discuss three measurement studies which help us understand mobile systems and how to improve them. The first examines how RRC state performance impacts network performance in the wild and argues carriers should measure RRC state performance from the user's perspective when managing their networks. The second looks at trends in applications' background network energy consumption, and shows that more systematic approaches are needed to manage app behavior. The third examines how Server Push, a new feature of HTTP/2, can in certain cases improve mobile performance, but shows that it is necessary to use measurements to determine if Server Push will be helpful or harmful. Two other projects show how measurements can be incorporated directly into systems that predict and manage network traffic. One project examines how a carrier can support prefetching over time spans of hours by predicting the network loads a user will see in the future and scheduling highly delay-tolerant traffic accordingly. The other examines how the network requests of mobile apps can be predicted, a first step towards an automated and general app prefetching system. Overall, measurements of network performance and app and user behavior are powerful tools in building better mobile systems.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/136944/1/sanae_1.pd

System designs for bulk and user-generated content delivery in the internet

This thesis proposes and evaluates new system designs to support two emerging Internet workloads: (a) bulk content, such as downloads of large media and scientific libraries, and (b) user-generated content (UGC), such as photos and videos that users share online, typically on online social networks (OSNs). Bulk content accounts for a large and growing fraction of today\u27s Internet traffic. Due to the high cost of bandwidth, delivering bulk content in the Internet is expensive. To reduce the cost of bulk transfers, I proposed traffic shaping and scheduling designs that exploit the delay-tolerant nature of bulk transfers to allow ISPs to deliver bulk content opportunistically. I evaluated my proposals through software prototypes and simulations driven by real-world traces from commercial and academic ISPs and found that they result in considerable reductions in transit costs or increased link utilization. The amount of user-generated content (UGC) that people share online has been rapidly growing in the past few years. Most users share UGC using online social networking websites (OSNs), which can impose arbitrary terms of use, privacy policies, and limitations on the content shared on their websites. To solve this problem, I evaluated the feasibility of a system that allows users to share UGC directly from the home, thus enabling them to regain control of the content that they share online. Using data from popular OSN websites and a testbed deployed in 10 households, I showed that current trends bode well for the delivery of personal UGC from users\u27 homes. I also designed and deployed Stratus, a prototype system that uses home gateways to share UGC directly from the home.Schwerpunkt dieser Doktorarbeit ist der Entwurf und die Auswertung neuer Systeme zur Unterstützung von zwei entstehenden Internet-Workloads: (a) Bulk-Content, wie zum Beispiel die Übertragung von großen Mediendateien und wissenschaftlichen Datenbanken, und (b) nutzergenerierten Inhalten, wie zum Beispiel Fotos und Videos, die Benutzer üblicherweise in sozialen Netzwerken veröffentlichen. Bulk-Content macht einen großen und weiter zunehmenden Anteil im heutigen Internetverkehr aus. Wegen der hohen Bandbreitenkosten ist die Übertragung von Bulk-Content im Internet jedoch teuer. Um diese Kosten zu senken habe ich neue Scheduling- und Traffic-Shaping-Lösungen entwickelt, die die Verzögerungsresistenz des Bulk-Verkehrs ausnutzen und es ISPs ermöglichen, Bulk-Content opportunistisch zu übermitteln. Durch Software-Prototypen und Simulationen mit Daten aus dem gewerblichen und akademischen Internet habe ich meine Lösungen ausgewertet und herausgefunden, dass sich die Übertragungskosten dadurch erheblich senken lassen und die Ausnutzung der Netze verbessern lässt. Der Anteil an nutzergenerierten Inhalten (user-generated content, UGC), die im Internet veröffentlicht wird, hat in den letzen Jahren ebenfalls schnell zugenommen. Meistens wird UGC in sozialen Netzwerken (online social networks, OSN) veröffentlicht. Dadurch sind Benutzer den willkürlichen Nutzungsbedingungen, Datenschutzrichtlinien, und Einschränkungen des OSN-Providers unterworfen. Um dieses Problem zu lösen, habe ich die Machbarkeit eines Systems ausgewertet, anhand dessen Benutzer UGC direkt von zu Hause veröffentlichen und die Kontrolle über ihren UGC zurückgewinnen können. Meine Auswertung durch Daten aus zwei populären OSN-Websites und einem Feldversuch in 10 Haushalten deutet darauf hin, dass angesichts der Fortschritte in der Bandbreite der Zugangsnetze die Veröffentlichung von persönlichem UGC von zu Hause in der nahen Zukunft möglich sein könnte.Schließlich habe ich Stratus entworfen und entwickelt, ein System, das auf Home-Gateways basiert und mit dem Benutzer UGC direkt von zu Hause veröffentlichen können

QoE management of multimedia streaming services in future networks : a tutorial and survey

No embargo require

Personal Data Management in the Internet of Things

Due to a sharp decrease in hardware costs and shrinking form factors, networked sensors have become ubiquitous. Today, a variety of sensors are embedded into smartphones, tablets, and personal wearable devices, and are commonly installed in homes and buildings. Sensors are used to collect data about people in their proximity, referred to as users. The collection of such networked sensors is commonly referred to as the Internet of Things. Although sensor data enables a wide range of applications from security, to efficiency, to healthcare, this data can be used to reveal unwarranted private information about users. Thus it is imperative to preserve data privacy while providing users with a wide variety of applications to process their personal data. Unfortunately, most existing systems do not meet these goals. Users are either forced to release their data to third parties, such as application developers, thus giving up data privacy in exchange for using data-driven applications, or are limited to using a fixed set of applications, such as those provided by the sensor manufacturer. To avoid this trade-off, users may chose to host their data and applications on their personal devices, but this requires them to maintain data backups and ensure application performance. What is needed, therefore, is a system that gives users flexibility in their choice of data-driven applications while preserving their data privacy, without burdening users with the need to backup their data and providing computational resources for their applications. We propose a software architecture that leverages a user's personal virtual execution environment (VEE) to host data-driven applications. This dissertation describes key software techniques and mechanisms that are necessary to enable this architecture. First, we provide a proof-of-concept implementation of our proposed architecture and demonstrate a privacy-preserving ecosystem of applications that process users' energy data as a case study. Second, we present a data management system (called Bolt) that provides applications with efficient storage and retrieval of time-series data, and guarantees the confidentiality and integrity of stored data. We then present a methodology to provision large numbers of personal VEEs on a single physical machine, and demonstrate its use with LinuX Containers (LXC). We conclude by outlining the design of an abstract framework to allow users to balance data privacy and application utility

Software Defined Applications in Cellular and Optical Networks

abstract: Small wireless cells have the potential to overcome bottlenecks in wireless access through the sharing of spectrum resources. A novel access backhaul network architecture based on a Smart Gateway (Sm-GW) between the small cell base stations, e.g., LTE eNBs, and the conventional backhaul gateways, e.g., LTE Servicing/Packet Gateways (S/P-GWs) has been introduced to address the bottleneck. The Sm-GW flexibly schedules uplink transmissions for the eNBs. Based on software defined networking (SDN) a management mechanism that allows multiple operator to flexibly inter-operate via multiple Sm-GWs with a multitude of small cells has been proposed. This dissertation also comprehensively survey the studies that examine the SDN paradigm in optical networks. Along with the PHY functional split improvements, the performance of Distributed Converged Cable Access Platform (DCCAP) in the cable architectures especially for the Remote-PHY and Remote-MACPHY nodes has been evaluated. In the PHY functional split, in addition to the re-use of infrastructure with a common FFT module for multiple technologies, a novel cross functional split interaction to cache the repetitive QAM symbols across time at the remote node to reduce the transmission rate requirement of the fronthaul link has been proposed.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201