MACHS: Mitigating the Achilles Heel of the Cloud through High Availability and Performance-aware Solutions

Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their HA and satisfying the QoS requirements. Second, a Stochastic Petri Net (SPN) model is proposed to capture the stochastic characteristics of cloud services and quantify the expected availability offered by an application deployment. The SPN model is then associated with an extensible policy-driven cloud scoring system that integrates other cloud challenges (i.e. green and cost concerns) with HA objectives. The proposed HA-aware solutions are extended to include a live virtual machine migration model that provides a trade-off between the migration time and the downtime while maintaining HA objective. Furthermore, the thesis proposes a generic input template for cloud simulators, GITS, to facilitate the creation of cloud scenarios while ensuring reusability, simplicity, and portability. Finally, an availability-aware CloudSim extension, ACE, is proposed. ACE extends CloudSim simulator with failure injection, computational paths, repair, failover, load balancing, and other availability-based modules

Deployment of NFV and SFC scenarios

Aquest ítem conté el treball original, defensat públicament amb data de 24 de febrer de 2017, així com una versió millorada del mateix amb data de 28 de febrer de 2017. Els canvis introduïts a la segona versió són 1) correcció d'errades 2) procediment del darrer annex.Telecommunications services have been traditionally designed linking hardware devices and providing mechanisms so that they can interoperate. Those devices are usually specific to a single service and are based on proprietary technology. On the other hand, the current model works by defining standards and strict protocols to achieve high levels of quality and reliability which have defined the carrier-class provider environment. Provisioning new services represent challenges at different levels because inserting the required devices involve changes in the network topology. This leads to slow deployment times and increased operational costs. To overcome the current burdens network function installation and insertion processes into the current service topology needs to be streamlined to allow greater flexibility. The current service provider model has been disrupted by the over-the-top Internet content providers (Facebook, Netflix, etc.), with short product cycles and fast development pace of new services. The content provider irruption has meant a competition and stress over service providers' infrastructure and has forced telco companies to research new technologies to recover market share with flexible and revenue-generating services. Network Function Virtualization (NFV) and Service Function Chaining (SFC) are some of the initiatives led by the Communication Service Providers to regain the lost leadership. This project focuses on experimenting with some of these already available new technologies, which are expected to be the foundation of the new network paradigms (5G, IOT) and support new value-added services over cost-efficient telecommunication infrastructures. Specifically, SFC scenarios have been deployed with Open Platform for NFV (OPNFV), a Linux Foundation project. Some use cases of the NFV technology are demonstrated applied to teaching laboratories. Although the current implementation does not achieve a production degree of reliability, it provides a suitable environment for the development of new functional improvements and evaluation of the performance of virtualized network infrastructures

!CHAOS: A cloud of controls

The paper is aimed to present the !CHAOS open source project aimed to develop a prototype of a national private Cloud Computing infrastructure, devoted to accelerator control systems and large experiments of High Energy Physics (HEP). The !CHAOS project has been financed by MIUR (Italian Ministry of Research and Education) and aims to develop a new concept of control system and data acquisition framework by providing, with a high level of abstraction, all the services needed for controlling and managing a large scientific, or non-scientific, infrastructure. A beta version of the !CHAOS infrastructure will be released at the end of December 2015 and will run on private Cloud infrastructures based on OpenStack

Planning and Optimization During the Life-Cycle of Service Level Agreements for Cloud Computing

Ein Service Level Agreement (SLA) ist ein elektronischer Vertrag zwischen dem Kunden und dem Anbieter eines Services. Die beteiligten Partner kl aren ihre Erwartungen und Verp ichtungen in Bezug auf den Dienst und dessen Qualit at. SLAs werden bereits f ur die Beschreibung von Cloud-Computing-Diensten eingesetzt. Der Diensteanbieter stellt sicher, dass die Dienstqualit at erf ullt wird und mit den Anforderungen des Kunden bis zum Ende der vereinbarten Laufzeit ubereinstimmt. Die Durchf uhrung der SLAs erfordert einen erheblichen Aufwand, um Autonomie, Wirtschaftlichkeit und E zienz zu erreichen. Der gegenw artige Stand der Technik im SLA-Management begegnet Herausforderungen wie SLA-Darstellung f ur Cloud- Dienste, gesch aftsbezogene SLA-Optimierungen, Dienste-Outsourcing und Ressourcenmanagement. Diese Gebiete scha en zentrale und aktuelle Forschungsthemen. Das Management von SLAs in unterschiedlichen Phasen w ahrend ihrer Laufzeit erfordert eine daf ur entwickelte Methodik. Dadurch wird die Realisierung von Cloud SLAManagement vereinfacht. Ich pr asentiere ein breit gef achertes Modell im SLA-Laufzeitmanagement, das die genannten Herausforderungen adressiert. Diese Herangehensweise erm oglicht eine automatische Dienstemodellierung, sowie Aushandlung, Bereitstellung und Monitoring von SLAs. W ahrend der Erstellungsphase skizziere ich, wie die Modellierungsstrukturen verbessert und vereinfacht werden k onnen. Ein weiteres Ziel von meinem Ansatz ist die Minimierung von Implementierungs- und Outsourcingkosten zugunsten von Wettbewerbsf ahigkeit. In der SLA-Monitoringphase entwickle ich Strategien f ur die Auswahl und Zuweisung von virtuellen Cloud Ressourcen in Migrationsphasen. Anschlie end pr ufe ich mittels Monitoring eine gr o ere Zusammenstellung von SLAs, ob die vereinbarten Fehlertoleranzen eingehalten werden. Die vorliegende Arbeit leistet einen Beitrag zu einem Entwurf der GWDG und deren wissenschaftlichen Communities. Die Forschung, die zu dieser Doktorarbeit gef uhrt hat, wurde als Teil von dem SLA@SOI EU/FP7 integriertem Projekt durchgef uhrt (contract No. 216556)

On the Impact of Advance Reservations for Energy-Aware Provisioning of Bare-Metal Cloud Resources

International audienceThis work investigates factors that can impact the elasticity of bare-metal resources. We analyse data from a real bare-metal deployment system to build a deployment time model, which is used to evaluate how provisioning time impacts the reservation of bare-metal resources. Climate/Blazar, a reservation framework designed for OpenStack, is discussed. Simulation results show that reservations can help reduce the time to deliver a provisioned cluster to its customer while achieving energy savings similar to those of strategies that switch-off idle resources

A Unified Monitoring Framework for Energy Consumption and Network Traffic

International audienceProviding experimenters with deep insight about the effects of theirexperiments is a central feature of testbeds. In this paper, wedescribe Kwapi, a framework designed in the context of the Grid'5000testbed, that unifies measurements for both energy consumption andnetwork traffic. Because all measurements are taken at theinfrastructure level (using sensors in power and network equipment),using this framework has no dependencies on the experiments themselves.Initially designed for OpenStack infrastructures, the Kwapi framework allowsmonitoring and reporting of energy consumption of distributed platforms. Inthis article, we present the extension of Kwapi to network monitoring, andoutline how we overcame several challenges: scaling to a testbed the size ofGrid'5000 while still providing high-frequency measurements; providing long-termloss-less storage of measurements; handling operational issues when deployingsuch a tool on a real infrastructure

Heterogeneity, High Performance Computing, Self-Organization and the Cloud

application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaa

Heterogeneity, High Performance Computing, Self-Organization and the Cloud

application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaa

Rapid and accurate energy models through calibration with IPMI and RAPL

Energy consumption in Cloud and High Performance Computing platforms is a significant issue and affects aspects such as the cost of energy and the cooling of the data center. Host level monitoring and prediction provides the groundwork for improving energy efficiency through the placement of workloads. Monitoring must be fast and efficient without unnecessary overhead, to enable scalability. This precludes the use of Watt meters attached per host, requiring alternative approaches such as integrated measurements and models. IPMI and RAPL are subject to error and partial measurement, which may be mitigated. Models allow for prediction and more responsive measures of power consumption, but require calibrating. The causes of calibration error are discussed, along with mitigation strategies, without overly complicating the underlying model. An outcome is a Watt meter emulator that provides hosts level power measurement along with estimated power consumption for a given workload, with an average error of 0.20W

Fog computing : enabling the management and orchestration of smart city applications in 5G networks

Fog computing extends the cloud computing paradigm by placing resources close to the edges of the network to deal with the upcoming growth of connected devices. Smart city applications, such as health monitoring and predictive maintenance, will introduce a new set of stringent requirements, such as low latency, since resources can be requested on-demand simultaneously by multiple devices at different locations. It is then necessary to adapt existing network technologies to future needs and design new architectural concepts to help meet these strict requirements. This article proposes a fog computing framework enabling autonomous management and orchestration functionalities in 5G-enabled smart cities. Our approach follows the guidelines of the European Telecommunications Standards Institute (ETSI) NFV MANO architecture extending it with additional software components. The contribution of our work is its fully-integrated fog node management system alongside the foreseen application layer Peer-to-Peer (P2P) fog protocol based on the Open Shortest Path First (OSPF) routing protocol for the exchange of application service provisioning information between fog nodes. Evaluations of an anomaly detection use case based on an air monitoring application are presented. Our results show that the proposed framework achieves a substantial reduction in network bandwidth usage and in latency when compared to centralized cloud solutions