ON OPTIMIZATIONS OF VIRTUAL MACHINE LIVE STORAGE MIGRATION FOR THE CLOUD

Virtual Machine (VM) live storage migration is widely performed in the data cen- ters of the Cloud, for the purposes of load balance, reliability, availability, hardware maintenance and system upgrade. It entails moving all the state information of the VM being migrated, including memory state, network state and storage state, from one physical server to another within the same data center or across different data centers. To minimize its performance impact, this migration process is required to be transparent to applications running within the migrating VM, meaning that ap- plications will keep running inside the VM as if there were no migration operations at all. In this dissertation, a thorough literature review is conducted to provide a big picture of the VM live storage migration process, its problems and existing solutions. After an in-depth examination, we observe that a severe IO interference between the VM IO threads and migration IO threads exists and causes both types of the IO threads to suffer from performance degradation. This interference stems from the fact that both types of IO threads share the same critical IO path by reading from and writing to the same shared storage system. Owing to IO resource contention and requests interference between the two different types of IO requests, not only will the IO request queue lengthens in the storage system, but the time-consuming disk seek operations will also become more frequent. Based on this fundamental observation, this dissertation research presents three related but orthogonal solutions that tackle the IO interference problem in order to improve the VM live storage migration performance. First, we introduce the Workload-Aware IO Outsourcing scheme, called WAIO, to improve the VM live storage migration efficiency. Second, we address this problem by proposing a novel scheme, called SnapMig, to improve the VM live storage migration efficiency and eliminate its performance impact on user applications at the source server by effectively leveraging the existing VM snapshots in the backup servers. Third, we propose the IOFollow scheme to improve both the VM performance and migration performance simultaneously. Finally, we outline the direction for the future research work. Advisor: Hong Jian

Network Function Virtualization over Cloud-Cloud Computing as Business Continuity Solution

Cloud computing provides resources by using virtualization technology and a pay-as-you-go cost model. Network Functions Virtualization (NFV) is a concept, which promises to grant network operators the required flexibility to quickly develop and provision new network functions and services, which can be hosted in the cloud. However, cloud computing is subject to failures which emphasizes the need to address user’s availability requirements. Availability refers to the cloud uptime and the cloud capability to operate continuously. Providing highly available services in cloud computing is essential for maintaining customer confidence and satisfaction and preventing revenue losses. Different techniques can be implemented to increase the system’s availability and assure business continuity. This chapter covers cloud computing as business continuity solution and cloud service availability. This chapter also covers the causes of service unavailability and the impact due to service unavailability. Further, this chapter covers various ways to achieve the required cloud service availability

High availability using virtualization

High availability has always been one of the main problems for a data center. Till now high availability was achieved by host per host redundancy, a highly expensive method in terms of hardware and human costs. A new approach to the problem can be offered by virtualization. Using virtualization, it is possible to achieve a redundancy system for all the services running on a data center. This new approach to high availability allows to share the running virtual machines over the servers up and running, by exploiting the features of the virtualization layer: start, stop and move virtual machines between physical hosts. The system (3RC) is based on a finite state machine with hysteresis, providing the possibility to restart each virtual machine over any physical host, or reinstall it from scratch. A complete infrastructure has been developed to install operating system and middleware in a few minutes. To virtualize the main servers of a data center, a new procedure has been developed to migrate physical to virtual hosts. The whole Grid data center SNS-PISA is running at the moment in virtual environment under the high availability system. As extension of the 3RC architecture, several storage solutions have been tested to store and centralize all the virtual disks, from NAS to SAN, to grant data safety and access from everywhere. Exploiting virtualization and ability to automatically reinstall a host, we provide a sort of host on-demand, where the action on a virtual machine is performed only when a disaster occurs.Comment: PhD Thesis in Information Technology Engineering: Electronics, Computer Science, Telecommunications, pp. 94, University of Pisa [Italy

Managing Smartphone Testbeds with SmartLab

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. In this paper, we make three major contributions: First, we propose a comprehensive architecture, coined SmartLab1, for managing a cluster of both real and virtual smartphones that are either wired to a private cloud or connected over a wireless link. Second, we propose and describe a number of Android management optimizations (e.g., command pipelining, screen-capturing, file management), which can be useful to the community for building similar functionality into their systems. Third, we conduct extensive experiments and microbenchmarks to support our design choices providing qualitative evidence on the expected performance of each module comprising our architecture. This paper also overviews experiences of using SmartLab in a research-oriented setting and also ongoing and future development efforts

A Personal Virtual Computer Recorder

Continuing advances in hardware technology have enabled the proliferation of faster, cheaper, and more capable personal computers. Users of all backgrounds rely on their computers to handle ever-expanding information, communication, and computation needs. As users spend more time interacting with their computers, it is becoming increasingly important to archive and later search the knowledge, ideas and information that they have viewed through their computers. However, existing state-of-the-art web and desktop search tools fail to provide a suitable solution, as they focus on static, accessible documents in isolation. Thus, finding the information one has viewed among the ever-increasing and chaotic sea of data available from a computer remains a challenge. This dissertation introduces DejaView, a personal virtual computer recorder that enhances personal computers with the ability to process display-centric content to help users with all the information they see through their computers. DejaView continuously records a user's session to provide a complete WYSIWYS (What You Search Is What You've Seen) record of a desktop computing experience, enabling users to playback, browse, search, and revive records, making it easier to retrieve and interact with information they have seen before. DejaView records visual output, checkpoints corresponding application and file system states, and captures onscreen text with contextual information to index the record. A user can then browse and search the record for any visual information that has been previously displayed on the desktop, and revive and interact with the desktop computing state corresponding to any point in the record. DejaView introduces new, transparent operating system, display and file system virtualization techniques and novel semantic display-centric information recording, and combines them to provide its functionality without any modifications to applications, window systems, or operating system kernels. Our results demonstrate that DejaView can provide continuous low-overhead recording without any user-noticeable performance degradation, and allows users to playback, browse, search, and time-travel back to records fast enough for interactive use. This dissertation also demonstrates how DejaView's execution virtualization and recording extend beyond the desktop recorder context. We introduce a coordinated, parallel checkpoint-restart mechanism for distributed applications that minimizes synchronization overhead and uniquely supports complete checkpoint and restart of network state in a transport protocol independent manner, for both reliable and unreliable protocols. We introduce a scalable system that enables significant energy saving by migrating network state and applications off of idle hosts allowing the hosts to enter low-power suspend state, while preserving their network presence. Finally, we show how our techniques can be integrated into a commodity operating system, mainline Linux, thereby allowing the entire operating systems community to benefit from mature checkpoint-restart that is transparent, secure, reliable, efficient, and integral to the Linux kernel

SimuBoost: Scalable Parallelization of Functional System Simulation

Für das Sammeln detaillierter Laufzeitinformationen, wie Speicherzugriffsmustern, wird in der Betriebssystem- und Sicherheitsforschung häufig auf die funktionale Systemsimulation zurückgegriffen. Der Simulator führt dabei die zu untersuchende Arbeitslast in einer virtuellen Maschine (VM) aus, indem er schrittweise Instruktionen interpretiert oder derart übersetzt, sodass diese auf dem Zustand der VM arbeiten. Dieser Prozess ermöglicht es, eine umfangreiche Instrumentierung durchzuführen und so an Informationen zum Laufzeitverhalten zu gelangen, die auf einer physischen Maschine nicht zugänglich sind. Obwohl die funktionale Systemsimulation als mächtiges Werkzeug gilt, stellt die durch die Interpretation oder Übersetzung resultierende immense Ausführungsverlangsamung eine substanzielle Einschränkung des Verfahrens dar. Im Vergleich zu einer nativen Ausführung messen wir für QEMU eine 30-fache Verlangsamung, wobei die Aufzeichnung von Speicherzugriffen diesen Faktor verdoppelt. Mit Simulatoren, die umfangreichere Instrumentierungsmöglichkeiten mitbringen als QEMU, kann die Verlangsamung um eine Größenordnung höher ausfallen. Dies macht die funktionale Simulation für lang laufende, vernetzte oder interaktive Arbeitslasten uninteressant. Darüber hinaus erzeugt die Verlangsamung ein unrealistisches Zeitverhalten, sobald Aktivitäten außerhalb der VM (z. B. Ein-/Ausgabe) involviert sind. In dieser Arbeit stellen wir SimuBoost vor, eine Methode zur drastischen Beschleunigung funktionaler Systemsimulation. SimuBoost führt die zu untersuchende Arbeitslast zunächst in einer schnellen hardwaregestützten virtuellen Maschine aus. Dies ermöglicht volle Interaktivität mit Benutzern und Netzwerkgeräten. Während der Ausführung erstellt SimuBoost periodisch Abbilder der VM (engl. Checkpoints). Diese dienen als Ausgangspunkt für eine parallele Simulation, bei der jedes Intervall unabhängig simuliert und analysiert wird. Eine heterogene deterministische Wiederholung (engl. heterogeneous deterministic Replay) garantiert, dass in dieser Phase die vorherige hardwaregestützte Ausführung jedes Intervalls exakt reproduziert wird, einschließlich Interaktionen und realistischem Zeitverhalten. Unser Prototyp ist in der Lage, die Laufzeit einer funktionalen Systemsimulation deutlich zu reduzieren. Während mit herkömmlichen Verfahren für die Simulation des Bauprozesses eines modernen Linux über 5 Stunden benötigt werden, schließt SimuBoost die Simulation in nur 15 Minuten ab. Dies sind lediglich 16% mehr Zeit, als der Bau in einer schnellen hardwaregestützten VM in Anspruch nimmt. SimuBoost ist imstande, diese Geschwindigkeit auch bei voller Instrumentierung zur Aufzeichnung von Speicherzugriffen beizubehalten. Die vorliegende Arbeit ist das erste Projekt, welches das Konzept der Partitionierung und Parallelisierung der Ausführungszeit auf die interaktive Systemvirtualisierung in einer Weise anwendet, die eine sofortige parallele funktionale Simulation gestattet. Wir ergänzen die praktische Umsetzung mit einem mathematischen Modell zur formalen Beschreibung der Beschleunigungseigenschaften. Dies erlaubt es, für ein gegebenes Szenario die voraussichtliche parallele Simulationszeit zu prognostizieren und gibt eine Orientierung zur Wahl der optimalen Intervalllänge. Im Gegensatz zu bisherigen Arbeiten legt SimuBoost einen starken Fokus auf die Skalierbarkeit über die Grenzen eines einzelnen physischen Systems hinaus. Ein zentraler Schlüssel hierzu ist der Einsatz moderner Checkpointing-Technologien. Im Rahmen dieser Arbeit präsentieren wir zwei neuartige Methoden zur effizienten und effektiven Kompression von periodischen Systemabbildern

System Support for Managing Risk in Cloud Computing Platforms

Cloud platforms sell computing to applications for a price. However, by precisely defining and controlling the service-level characteristics of cloud servers, they expose applications to a number of implicit risks throughout the application’s lifecycle. For example, user’s request for a server may be denied, leading to rejection risk; an allocated resource may be withdrawn, resulting in revocation risk; an acquired cloud server’s price may rise relative to others, causing price risk; a cloud server’s performance may vary due to external factors, triggering valuation risk. Though these risks are implicit, the costs they bear on the applications are not. While some risks exist in all Infrastructure-as-a-Service offerings, they are most pronounced in an emerging category called transient cloud servers. Since transient servers are carved out of instantaneous idle cloud capacity, they exhibit two distinct features: (i) revocations that are intentional, frequent and come with advanced warning, and (ii) prices that are low in average but vary across time and location. Thus, despite enabling inexpensive access to at-scale computing, transient cloud servers expose applications to risks, the scale of which were unseen in the past platforms. Unfortunately, the current generation system software are not designed to handle these risks, which in turn results in inconsistent performances, unexpected failures, missed savings, and slower adoption. In this dissertation, we elevate risk management to a first-class system design principle. Our goal is to identify the risks, quantify their costs, and explicitly manage them for applications deployed on cloud platforms. Towards that goal, we adapt and extend concepts from finance and economics to propose a new system design approach called financializing cloud computing. By treating cloud resources as investments, and by quantifying the cost of their risks, financialization enables system software to manage the risk-reward trade-offs, explicitly and autonomously. We demonstrate the utility of our approach via four contributions: (i) mitigating revocation risk with insurance policy, (ii) reducing price risk through active trading, (iii) eliminating uncertainty risk by index tracking, and (iv) minimizing server’s valuation risk via asset pricing. We conclude by observing that diversity and asymmetry in the creation and consumption of cloud compute resources is on the rise, and that financialization can be effectively employed to manage its complexity and risks

Potential impact assessment of climate-related hazards on urban public health services: interaction of changing climate-related hazards and urban development in the future, Khon Kaen City, Thailand

Current understanding of the interactions between the future urban development change and climate change in the local context, considering infrastructure operation & functionality, is still primitive, especially in public health services. This study offers a climate-resilient operationalization framework for urban public health services considering the interaction between urban development change and climate change across scales, the so-called Health Integrative Climate Resilience and Adaptation Future (HICRAF). HICRAF integrates collaborative scenario planning and composite indicators developed based on the IPCC Fifth Assessment Report (AR5) 's climate risk concept. It combines a mixed-methods approach of quantitative and qualitative techniques and demonstrates how different methods and scales (spatial and temporal) can be linked and create new knowledge on cascading risk patterns in a medium-sized city with a universal health care coverage setting; Khon Kaen city, Thailand. The results show that the approach allows local public health care to operationalize their potential impact and climate-resilient targets in a forward-looking manner with multiple service operation aspects. The scenario assessment outcomes prove that public health devotions can help their operation and functionality fail-safe when confronting future climatic and non-climatic challenges. However, achieving climate-resilient targets requires sectoral integration with urban development and health determining domains. Hence, more integrated spatial planning of public health services and critically revisiting conventional cost-benefit assessments on public health infrastructure investment are key entry points for creating climate-resilient urban health services. In addition to addressing missing links between global climate trajectories and local climate adaptation scenarios that involved stakeholders' normative judgements and cross-sectoral interests. HICRAF highlights a clear constraint of applying a purely place-based concept on climate vulnerability/risk assessment in reflecting the realities of network operation and functionality of urban systems. Thus, the co-existing paradox between the place-based and network-based concepts should be investigated further in climate vulnerability/risk assessment studies. Furthermore, exploration and disputation of HICRAF and its composite indicators with a wider scale and diversified settings are invited to enhance its robustness and universality