Challenges for the comprehensive management of cloud services in a PaaS framework

The 4CaaSt project aims at developing a PaaS framework that enables flexible definition, marketing, deployment and management of Cloud-based services and applications. The major innovations proposed by 4CaaSt are the blueprint and its lifecycle management, a one stop shop for Cloud services and a PaaS level resource management featuring elasticity. 4CaaSt also provides a portfolio of ready to use Cloud native services and Cloud-aware immigrant technologies.

4CaaSt: Comprehensive management of Cloud services through a PaaS

The 4CaaSt project aims at developing a PaaS framework that enables flexible definition, marketing, deployment and management of Cloud-based services and applications. The major innovations proposed by 4CaaSt are the blueprint and its management and lifecycle, a one stop shop for Cloud services and the management of resources in the PaaS level (including elasticity). 4CaaSt also provides a portfolio of ready to use Cloud native services and Cloud- aware immigrant technologies.

Reliability issues related to the usage of Cloud Computing in Critical Infrastructures

The use of cloud computing is extending to all kind of systems, including the ones that are part of Critical Infrastructures, and measuring the reliability is becoming more difficult. Computing is becoming the 5th utility, in part thanks to the use of cloud services. Cloud computing is used now by all types of systems and organizations, including critical infrastructure, creating hidden inter-dependencies on both public and private cloud models. This paper investigates the use of cloud computing by critical infrastructure systems, the reliability and continuity of services risks associated with their use by critical systems. Some examples are presented of their use by different critical industries, and even when the use of cloud computing by such systems is not widely extended, there is a future risk that this paper presents. The concepts of macro and micro dependability and the model we introduce are useful for inter-dependency definition and for analyzing the resilience of systems that depend on other systems, specifically in the cloud model.

Resilience in Cloud Computing for Critical Systems. Resilience, Dependability, Reliability in the use of Cloud Computing in Critical Systems in Public Organizations.

La informática se está convirtiendo en la quinta utilidad (gas, agua, luz, teléfono) en parte debido al impacto de Cloud Computing en las mayorías de las organizaciones. Este uso de informática es usada por cada vez más tipos de sistemas, incluidos Sistemas Críticos. Esto tiene un impacto en la complejidad internad y la fiabilidad de los sistemas de la organización y los que se ofrecen a los clientes. Este trabajo investiga el uso de Cloud Computing por sistemas críticos, centrándose en las dependencias y especialmente en la fiabilidad de estos sistemas. Se han presentado algunos ejemplos de su uso, y aunque su utilización en sistemas críticos no está extendido, se presenta cual puede llegar a ser su impacto. El objetivo de este trabajo es primero definir un modelo que pueda representar de una forma cuantitativa las interdependencias en fiabilidad y interdependencia para las organizaciones que utilicen estos sistemas, y aplicar este modelo en un sistema crítico del campo de sanidad y mostrar sus resultados. Los conceptos de “macro-dependability” y “micro-dependability” son introducidos en el modelo para la definición de interdependencia y para analizar la fiabilidad de sistemas que dependen de otros sistemas. ABSTRACT With the increasing utilization of Internet services and cloud computing by most organizations (both private and public), it is clear that computing is becoming the 5th utility (along with water, electricity, telephony and gas). These technologies are used for almost all types of systems, and the number is increasing, including Critical Infrastructure systems. Even if Critical Infrastructure systems appear not to rely directly on cloud services, there may be hidden inter-dependencies. This is true even for private cloud computing, which seems more secure and reliable. The critical systems can began in some cases with a clear and simple design, but evolved as described by Egan to "rafted" networks. Because they are usually controlled by one or few organizations, even when they are complex systems, their dependencies can be understood. The organization oversees and manages changes. These CI systems have been affected by the introduction of new ICT models like global communications, PCs and the Internet. Even virtualization took more time to be adopted by Critical systems, due to their strategic nature, but once that these technologies have been proven in other areas, at the end they are adopted as well, for different reasons such as costs. A new technology model is happening now based on some previous technologies (virtualization, distributing and utility computing, web and software services) that are offered in new ways and is called cloud computing. The organizations are migrating more services to the cloud; this will have impact in their internal complexity and in the reliability of the systems they are offering to the organization itself and their clients. Not always this added complexity and associated risks to their reliability are seen. As well, when two or more CI systems are interacting, the risks of one can affect the rest, sharing the risks. This work investigates the use of cloud computing by critical systems, and is focused in the dependencies and reliability of these systems. Some examples are presented together with the associated risks. A framework is introduced for analysing the dependability and resilience of a system that relies on cloud services and how to improve them. As part of the framework, the concepts of micro and macro dependability are introduced to explain the internal and external dependability on services supplied by an external cloud. A pharmacovigilance model system has been used for framework validation.

Unified representation of monitoring information across federated cloud infrastructures

Nowadays one of the issues hindering the potential of federating cloud-based infrastructures to reach much larger scales is their standard management and monitoring. In particular, this is true in cases where these federated infrastructures provide emerging Future Internet and Smart Cities-oriented services, such as the Internet of Things (IoT), that benefit from cloud services. The contribution of this paper is the introduction of a unified monitoring architecture for federated cloud infrastructures accompanied by the adoption of a uniform representation of measurement data. The presented solution is capable of providing multi-domain compatibility, scalability, as well as the ability to analyze large amounts of monitoring data, collected from datacenters and offered through open and standardized APIs. The solution described herein has been deployed and is currently running on a community of 5 infrastructures within the framework of the European Project XIFI, to be extended to 12 more infrastructures.

Server power modeling for run-time energy optimization of cloud computing facilities

As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. The average consumption of a single data center is equivalent to the energy consumption of 25.000 households. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. This work proposes an automatic method, based on Multi-Objective Particle Swarm Optimization, for the identification of power models of enterprise servers in Cloud data centers. Our approach, as opposed to previous procedures, does not only consider the workload consolidation for deriving the power model, but also incorporates other non traditional factors like the static power consumption and its dependence with temperature. Our experimental results shows that we reach slightly better models than classical approaches, but simul- taneously simplifying the power model structure and thus the numbers of sensors needed, which is very promising for a short-term energy prediction. This work, validated with real Cloud applications, broadens the possibilities to derive efficient energy saving techniques for Cloud facilities.

Context-awareness in task automation services by distributed event processing

Everybody has to coordinate several tasks everyday, usually in a manual manner. Recently, the concept of Task Automation Services has been introduced to automate and personalize the task coordination problem. Several user centered platforms and applications have arisen in the last years, that let their users configure their very own automations based on third party services. In this paper, we propose a new system architecture for Task Automation Services in a heterogeneous mobile, smart devices, and cloud services environment. Our architecture is based on the novel idea to employ distributed Complex Event Processing to implement innovative mixed execution profiles. The major advantage of the approach is its ability to incorporate context-awareness and real-time coordination in Task Automation Services.

Enhancing regression models for complex systems using evolutionary techniques for feature engineering

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.

FIWARE Lab: managing resources and services in a cloud federation supporting future internet applications

Real-world experimentation facilities accelerate the development of Future Internet technologies and services, advance the market for smart infrastructures, and increase the effectiveness of business processes through the Internet. The federation of facilities fosters the experimentation and innovation with larger and more powerful environment, increases the number and variety of the offered services and brings forth possibilities for new experimentation scenarios. This paper introduces a management solution for cloud federation that automates service provisioning to the largest possible extent, relieves the developers from time-consuming configuration settings, and caters for real-time information of all information related to the whole lifecycle of the provisioned services. This is achieved by proposing solutions to achieve the seamless deployment of services across the federation and ability of services to span across different infrastructures of the federation, as well as monitoring of the resources and data which can be aggregated with a common structure, offered as an open ecosystem for innovation at the developers' disposal. This solution consists of several federation management tools and components that are part of the work on Cloud Federation conducted within XIFI project to build the federation of cloud infrastructures for the Future Internet Lab (FIWARE Lab). We present the design and implementation of the solution-concerned FIWARE Lab management tools and components that are deployed within a federation of 17 cloud infrastructures distributed across Europe.

Testing a Cloud Provider Network for Hybrid P2P and Cloud Streaming Architectures

The number of online real-time streaming services deployed over network topologies like P2P or centralized ones has remarkably increased in the recent years. This has revealed the lack of networks that are well prepared to respond to this kind of traffic. A hybrid distribution network can be an efficient solution for real-time streaming services. This paper contains the experimental results of streaming distribution in a hybrid architecture that consist of mixed connections among P2P and Cloud nodes that can interoperate together. We have chosen to represent the P2P nodes as Planet Lab machines over the world and the cloud nodes using a Cloud provider's network. First we present an experimental validation of the Cloud infrastructure's ability to distribute streaming sessions with respect to some key streaming QoS parameters: jitter, throughput and packet losses. Next we show the results obtained from different test scenarios, when a hybrid distribution network is used. The scenarios measure the improvement of the multimedia QoS parameters, when nodes in the streaming distribution network (located in different continents) are gradually moved into the Cloud provider infrastructure. The overall conclusion is that the QoS of a streaming service can be efficiently improved, unlike in traditional P2P systems and CDN, by deploying a hybrid streaming architecture. This enhancement can be obtained by strategic placing of certain distribution network nodes into the Cloud provider infrastructure, taking advantage of the reduced packet loss and low latency that exists among its datacenters.

Contribution to multiuser videoconferencing systems based on cloud computing

Multi-user videoconferencing systems offer communication between more than two users, who are able to interact through their webcams, microphones and other components. The use of these systems has been increased recently due to, on the one hand, improvements in Internet access, networks of companies, universities and houses, whose available bandwidth has been increased whilst the delay in sending and receiving packets has decreased. On the other hand, the advent of Rich Internet Applications (RIA) means that a large part of web application logic and control has started to be implemented on the web browsers. This has allowed developers to create web applications with a level of complexity comparable to traditional desktop applications, running on top of the Operating Systems. More recently the use of Cloud Computing systems has improved application scalability and involves a reduction in the price of backend systems. This offers the possibility of implementing web services on the Internet with no need to spend a lot of money when deploying infrastructures and resources, both hardware and software. Nevertheless there are not many initiatives that aim to implement videoconferencing systems taking advantage of Cloud systems. This dissertation proposes a set of techniques, interfaces and algorithms for the implementation of videoconferencing systems in public and private Cloud Computing infrastructures. The mechanisms proposed here are based on the implementation of a basic videoconferencing system that runs on the web browser without any previous installation requirements. To this end, the development of this thesis starts from a RIA application with current technologies that allow users to access their webcams and microphones from the browser, and to send captured data through their Internet connections. Furthermore interfaces have been implemented to allow end users to participate in videoconferencing rooms that are managed in different Cloud provider servers. To do so this dissertation starts from the results obtained from the previous techniques and backend resources were implemented in the Cloud. A traditional videoconferencing service which was implemented in the department was modified to meet typical Cloud Computing infrastructure requirements. This allowed us to validate whether Cloud Computing public infrastructures are suitable for the traffic generated by this kind of system. This analysis focused on the network level and processing capacity and stability of the Cloud Computing systems. In order to improve this validation several other general considerations were taken in order to cover more cases, such as multimedia data processing in the Cloud, as research activity has increased in this area in recent years. The last stage of this dissertation is the design of a new methodology to implement these kinds of applications in hybrid clouds reducing the cost of videoconferencing systems. Finally, this dissertation opens up a discussion about the conclusions obtained throughout this study, resulting in useful information from the different stages of the implementation of videoconferencing systems in Cloud Computing systems. RESUMEN Los sistemas de videoconferencia multiusuario permiten la comunicación entre más de dos usuarios que pueden interactuar a través de cámaras de video, micrófonos y otros elementos. En los últimos años el uso de estos sistemas se ha visto incrementado gracias, por un lado, a la mejora de las redes de acceso en las conexiones a Internet en empresas, universidades y viviendas, que han visto un aumento del ancho de banda disponible en dichas conexiones y una disminución en el retardo experimentado por los datos enviados y recibidos. Por otro lado también ayudó la aparación de las Aplicaciones Ricas de Internet (RIA) con las que gran parte de la lógica y del control de las aplicaciones web comenzó a ejecutarse en los mismos navegadores. Esto permitió a los desarrolladores la creación de aplicaciones web cuya complejidad podía compararse con la de las tradicionales aplicaciones de escritorio, ejecutadas directamente por los sistemas operativos. Más recientemente el uso de sistemas de Cloud Computing ha mejorado la escalabilidad y el abaratamiento de los costes para sistemas de backend, ofreciendo la posibilidad de implementar servicios Web en Internet sin la necesidad de grandes desembolsos iniciales en las áreas de infraestructuras y recursos tanto hardware como software. Sin embargo no existen aún muchas iniciativas con el objetivo de realizar sistemas de videoconferencia que aprovechen las ventajas del Cloud. Esta tesis doctoral propone un conjunto de técnicas, interfaces y algoritmos para la implentación de sistemas de videoconferencia en infraestructuras tanto públicas como privadas de Cloud Computing. Las técnicas propuestas en la tesis se basan en la realización de un servicio básico de videoconferencia que se ejecuta directamente en el navegador sin la necesidad de instalar ningún tipo de aplicación de escritorio. Para ello el desarrollo de esta tesis parte de una aplicación RIA con tecnologías que hoy en día permiten acceder a la cámara y al micrófono directamente desde el navegador, y enviar los datos que capturan a través de la conexión de Internet. Además se han implementado interfaces que permiten a usuarios finales la participación en salas de videoconferencia que se ejecutan en servidores de proveedores de Cloud. Para ello se partió de los resultados obtenidos en las técnicas anteriores de ejecución de aplicaciones en el navegador y se implementaron los recursos de backend en la nube. Además se modificó un servicio ya existente implementado en el departamento para adaptarlo a los requisitos típicos de las infraestructuras de Cloud Computing. Alcanzado este punto se procedió a analizar si las infraestructuras propias de los proveedores públicos de Cloud Computing podrían soportar el tráfico generado por los sistemas que se habían adaptado. Este análisis se centró tanto a nivel de red como a nivel de capacidad de procesamiento y estabilidad de los sistemas. Para los pasos de análisis y validación de los sistemas Cloud se tomaron consideraciones más generales para abarcar casos como el procesamiento de datos multimedia en la nube, campo en el que comienza a haber bastante investigación en los últimos años. Como último paso se ideó una metodología de implementación de este tipo de aplicaciones para que fuera posible abaratar los costes de los sistemas de videoconferencia haciendo uso de clouds híbridos. Finalmente en la tesis se abre una discusión sobre las conclusiones obtenidas a lo largo de este amplio estudio, obteniendo resultados útiles en las distintas etapas de implementación de los sistemas de videoconferencia en la nube.

Riding out of the storm: How to deal with the complexity of grid and cloud management

Over the last decade, Grid computing paved the way for a new level of large scale distributed systems. This infrastructure made it possible to securely and reliably take advantage of widely separated computational resources that are part of several different organizations. Resources can be incorporated to the Grid, building a theoretical virtual supercomputer. In time, cloud computing emerged as a new type of large scale distributed system, inheriting and expanding the expertise and knowledge that have been obtained so far. Some of the main characteristics of Grids naturally evolved into clouds, others were modified and adapted and others were simply discarded or postponed. Regardless of these technical specifics, both Grids and clouds together can be considered as one of the most important advances in large scale distributed computing of the past ten years; however, this step in distributed computing has came along with a completely new level of complexity. Grid and cloud management mechanisms play a key role, and correct analysis and understanding of the system behavior are needed. Large scale distributed systems must be able to self-manage, incorporating autonomic features capable of controlling and optimizing all resources and services. Traditional distributed computing management mechanisms analyze each resource separately and adjust specific parameters of each one of them. When trying to adapt the same procedures to Grid and cloud computing, the vast complexity of these systems can make this task extremely complicated. But large scale distributed systems complexity could only be a matter of perspective. It could be possible to understand the Grid or cloud behavior as a single entity, instead of a set of resources. This abstraction could provide a different understanding of the system, describing large scale behavior and global events that probably would not be detected analyzing each resource separately. In this work we define a theoretical framework that combines both ideas, multiple resources and single entity, to develop large scale distributed systems management techniques aimed at system performance optimization, increased dependability and Quality of Service (QoS). The resulting synergy could be the key 350 J. Montes et al. to address the most important difficulties of Grid and cloud management.

The new cloud computing paradigm: the way to IT seen as a utility

In the present competitive environment, companies are wondering how to reduce their IT costs while increasing their efficiency and agility to react when changes in the business processes are required. Cloud Computing is the latest paradigm to optimize the use of IT resources considering ?everything as a service? and receiving these services from the Cloud (Internet) instead of owning and managing hardware and software assets. The benefits from the model are clear. However, there are also concerns and issues to be solved before Cloud Computing spreads across the different industries. This model will allow a pay-per-use model for the IT services and many benefits like cost savings, agility to react when business demands changes and simplicity because there will not be any infrastructure to operate and administrate. It will be comparable to the well known utilities like electricity, water or gas companies. However, this paper underlines several risk factors of the model. Leading technology companies should research on solutions to minimize the risks described in this article. Keywords - Cloud Computing, Utility Computing, Elastic Computing, Enterprise Agility

Harmony: Towards automated self-adaptive consistency in cloud storage

In just a few years cloud computing has become a very popular paradigm and a business success story, with storage being one of the key features. To achieve high data availability, cloud storage services rely on replication. In this context, one major challenge is data consistency. In contrast to traditional approaches that are mostly based on strong consistency, many cloud storage services opt for weaker consistency models in order to achieve better availability and performance. This comes at the cost of a high probability of stale data being read, as the replicas involved in the reads may not always have the most recent write. In this paper, we propose a novel approach, named Harmony, which adaptively tunes the consistency level at run-time according to the application requirements. The key idea behind Harmony is an intelligent estimation model of stale reads, allowing to elastically scale up or down the number of replicas involved in read operations to maintain a low (possibly zero) tolerable fraction of stale reads. As a result, Harmony can meet the desired consistency of the applications while achieving good performance. We have implemented Harmony and performed extensive evaluations with the Cassandra cloud storage on Grid?5000 testbed and on Amazon EC2. The results show that Harmony can achieve good performance without exceeding the tolerated number of stale reads. For instance, in contrast to the static eventual consistency used in Cassandra, Harmony reduces the stale data being read by almost 80% while adding only minimal latency. Meanwhile, it improves the throughput of the system by 45% while maintaining the desired consistency requirements of the applications when compared to the strong consistency model in Cassandra.

A federated repository for PaaS components in a multi-cloud environment

Cloud computing has seen an impressive growth in recent years, with virtualization technologies being massively adopted to create IaaS (Infrastructure as a Service) public and private solutions. Today, the interest is shifting towards the PaaS (Platform as a Service) model, which allows developers to abstract from the execution platform and focus only on the functionality. There are several public PaaS offerings available, but currently no private PaaS solution is ready for production environments. To fill this gap a new solution must be developed. In this paper we present a key element for enabling this model: a cloud repository based on the OSGi component model. The repository stores, manages, provisions and resolves the dependencies of PaaS software components and services. This repository can federate with other repositories located in the same or different clouds, both private and public. This way, dependencies can be fulfilled collaboratively, and new business models can be implemented.