Smart execution of distributed application by balancing resources in mobile devices and cloud-based avatars

L’obiettivo del progetto di tesi svolto è quello di realizzare un servizio di livello middleware dedicato ai dispositivi mobili che sia in grado di fornire il supporto per l’offloading di codice verso una infrastruttura cloud. In particolare il progetto si concentra sulla migrazione di codice verso macchine virtuali dedicate al singolo utente. Il sistema operativo delle VMs è lo stesso utilizzato dal device mobile. Come i precedenti lavori sul computation offloading, il progetto di tesi deve garantire migliori performance in termini di tempo di esecuzione e utilizzo della batteria del dispositivo. In particolare l’obiettivo più ampio è quello di adattare il principio di computation offloading a un contesto di sistemi distribuiti mobili, migliorando non solo le performance del singolo device, ma l’esecuzione stessa dell’applicazione distribuita. Questo viene fatto tramite una gestione dinamica delle decisioni di offloading basata, non solo, sullo stato del device, ma anche sulla volontà e/o sullo stato degli altri utenti appartenenti allo stesso gruppo. Per esempio, un primo utente potrebbe influenzare le decisioni degli altri membri del gruppo specificando una determinata richiesta, come alta qualità delle informazioni, risposta rapida o basata su altre informazioni di alto livello. Il sistema fornisce ai programmatori un semplice strumento di definizione per poter creare nuove policy personalizzate e, quindi, specificare nuove regole di offloading. Per rendere il progetto accessibile ad un più ampio numero di sviluppatori gli strumenti forniti sono semplici e non richiedono specifiche conoscenze sulla tecnologia. Il sistema è stato poi testato per verificare le sue performance in termini di mecchanismi di offloading semplici. Successivamente, esso è stato anche sottoposto a dei test per verificare che la selezione di differenti policy, definite dal programmatore, portasse realmente a una ottimizzazione del parametro designato.

A QoS Controller Framework Compliant with the ETSI Network Function Virtualization Specification

The 5th generation of mobile networking introduces the concept of “Network slicing”, the network will be “sliced” horizontally, each slice will be compliant with different requirements in terms of network parameters such as bandwidth, latency. This technology is built on logical instead of physical resources, relies on virtual network as main concept to retrieve a logical resource. The Network Function Virtualisation provides the concept of logical resources for a virtual network function, enabling the concept virtual network; it relies on the Software Defined Networking as main technology to realize the virtual network as resource, it also define the concept of virtual network infrastructure with all components needed to enable the network slicing requirements. SDN itself uses cloud computing technology to realize the virtual network infrastructure, NFV uses also the virtual computing resources to enable the deployment of virtual network function instead of having custom hardware and software for each network function. The key of network slicing is the differentiation of slice in terms of Quality of Services parameters, which relies on the possibility to enable QoS management in cloud computing environment. The QoS in cloud computing denotes level of performances, reliability and availability offered. QoS is fundamental for cloud users, who expect providers to deliver the advertised quality characteristics, and for cloud providers, who need to find the right tradeoff between QoS levels that has possible to offer and operational costs. While QoS properties has received constant attention before the advent of cloud computing, performance heterogeneity and resource isolation mechanisms of cloud platforms have significantly complicated QoS analysis and deploying, prediction, and assurance. This is prompting several researchers to investigate automated QoS management methods that can leverage the high programmability of hardware and software resources in the cloud.

Tecniche Cloud Avanzate per Adaptive Hadoop Load Balancing tramite Sahara

Ogni giorno vengono generati grandi moli di dati attraverso sorgenti diverse. Questi dati, chiamati Big Data, sono attualmente oggetto di forte interesse nel settore IT (Information Technology). I processi digitalizzati, le interazioni sui social media, i sensori ed i sistemi mobili, che utilizziamo quotidianamente, sono solo un piccolo sottoinsieme di tutte le fonti che contribuiscono alla produzione di questi dati. Per poter analizzare ed estrarre informazioni da questi grandi volumi di dati, tante sono le tecnologie che sono state sviluppate. Molte di queste sfruttano approcci distribuiti e paralleli. Una delle tecnologie che ha avuto maggior successo nel processamento dei Big Data, e Apache Hadoop. Il Cloud Computing, in particolare le soluzioni che seguono il modello IaaS (Infrastructure as a Service), forniscono un valido strumento all'approvvigionamento di risorse in maniera semplice e veloce. Per questo motivo, in questa proposta, viene utilizzato OpenStack come piattaforma IaaS. Grazie all'integrazione delle tecnologie OpenStack e Hadoop, attraverso Sahara, si riesce a sfruttare le potenzialita offerte da un ambiente cloud per migliorare le prestazioni dell'elaborazione distribuita e parallela. Lo scopo di questo lavoro e ottenere una miglior distribuzione delle risorse utilizzate nel sistema cloud con obiettivi di load balancing. Per raggiungere questi obiettivi, si sono rese necessarie modifiche sia al framework Hadoop che al progetto Sahara.

Managing server energy and reducing operational cost for online service providers

The past decade has seen the energy consumption in servers and Internet Data Centers (IDCs) skyrocket. A recent survey estimated that the worldwide spending on servers and cooling have risen to above $30 billion and is likely to exceed spending on the new server hardware . The rapid rise in energy consumption has posted a serious threat to both energy resources and the environment, which makes green computing not only worthwhile but also necessary. This dissertation intends to tackle the challenges of both reducing the energy consumption of server systems and by reducing the cost for Online Service Providers (OSPs). Two distinct subsystems account for most of IDC’s power: the server system, which accounts for 56% of the total power consumption of an IDC, and the cooling and humidifcation systems, which accounts for about 30% of the total power consumption. The server system dominates the energy consumption of an IDC, and its power draw can vary drastically with data center utilization. In this dissertation, we propose three models to achieve energy effciency in web server clusters: an energy proportional model, an optimal server allocation and frequency adjustment strategy, and a constrained Markov model. The proposed models have combined Dynamic Voltage/Frequency Scaling (DV/FS) and Vary-On, Vary-off (VOVF) mechanisms that work together for more energy savings. Meanwhile, corresponding strategies are proposed to deal with the transition overheads. We further extend server energy management to the IDC’s costs management, helping the OSPs to conserve, manage their own electricity cost, and lower the carbon emissions. We have developed an optimal energy-aware load dispatching strategy that periodically maps more requests to the locations with lower electricity prices. A carbon emission limit is placed, and the volatility of the carbon offset market is also considered. Two energy effcient strategies are applied to the server system and the cooling system respectively. With the rapid development of cloud services, we also carry out research to reduce the server energy in cloud computing environments. In this work, we propose a new live virtual machine (VM) placement scheme that can effectively map VMs to Physical Machines (PMs) with substantial energy savings in a heterogeneous server cluster. A VM/PM mapping probability matrix is constructed, in which each VM request is assigned with a probability running on PMs. The VM/PM mapping probability matrix takes into account resource limitations, VM operation overheads, server reliability as well as energy effciency. The evolution of Internet Data Centers and the increasing demands of web services raise great challenges to improve the energy effciency of IDCs. We also express several potential areas for future research in each chapter.

Under One Umbrella: Problems of Internet Retransmissions of Broadcasts and Implications for New Audiovisual Content Services

The development of broadband Internet connections has fostered new audiovisual media services and opened new possibilities for accessing broadcasts. The Internet retransmission case of TVCatchup before the CJEU was the first case concerning new technologies in the light of Art. 3.1. of the Information Society Directive. On the other side of the Atlantic the Aereo case reached the U.S. Supreme Court and challenged the interpretation of public performance rights. In both cases the recipients of the services could receive broadcast programs in a way alternative to traditional broadcasting channels including terrestrial broadcasting or cable transmission. The Aereo case raised the debate on the possible impact of the interpretation of copyright law in the context of the development of new technologies, particularly cloud based services. It is interesting to see whether any similar problems occur in the EU. The „umbrella” in the title refers to Art. 8 WCT, which covers digital and Internet transmission and constitutes the backrgound for the EU and the U.S. legal solutions. The article argues that no international standard for qualification of the discussed services exists.

Virtual Infrastructures as a Service enabling Converged Optical Networks and Data Centres

Abstract Cloud computing service emerged as an essential component of the Enterprise {IT} infrastructure. Migration towards a full range and large-scale convergence of Cloud and network services has become the current trend for addressing requirements of the Cloud environment. Our approach takes the infrastructure as a service paradigm to build converged virtual infrastructures, which allow offering tailored performance and enable multi-tenancy over a common physical infrastructure. Thanks to virtualization, new exploitation activities of the physical infrastructures may arise for both transport network and Data Centres services. This approach makes network and Data Centres’ resources dedicated to Cloud Computing to converge on the same flexible and scalable level. The work presented here is based on the automation of the virtual infrastructure provisioning service. On top of the virtual infrastructures, a coordinated operation and control of the different resources is performed with the objective of automatically tailoring connectivity services to the Cloud service dynamics. Furthermore, in order to support elasticity of the Cloud services through the optical network, dynamic re-planning features have been provided to the virtual infrastructure service, which allows scaling up or down existing virtual infrastructures to optimize resource utilisation and dynamically adapt to users’ demands. Thus, the dynamic re-planning of the service becomes key component for the coordination of Cloud and optical network resource in an optimal way in terms of resource utilisation. The presented work is complemented with a use case of the virtual infrastructure service being adopted in a distributed Enterprise Information System, that scales up and down as a function of the application requests.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems

Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.

Trends in Human-Centric Multimedia Networking Scenarios

The evolution of wireless access technologies and mobile devices, together with the constant demand for video services, has created new Human-Centric Multimedia Networking (HCMN) scenarios. However, HCMN poses several challenges for content creators and network providers to deliver multimedia data with an acceptable quality level based on the user experience. Moreover, human experience and context, as well as network information play an important role in adapting and optimizing video dissemination. In this paper, we discuss trends to provide video dissemination with Quality of Experience (QoE) support by integrating HCMN with cloud computing approaches. We identified five trends coming from such integration, namely Participatory Sensor Networks, Mobile Cloud Computing formation, QoE assessment, QoE management, and video or network adaptation.

A semantic scheduler architecture for federated hybrid clouds

Cloud computing is one the most relevant computing paradigms available nowadays. Its adoption has increased during last years due to the large investment and research from business enterprises and academia institutions. Among all the services cloud providers usually offer, Infrastructure as a Service has reached its momentum for solving HPC problems in a more dynamic way without the need of expensive investments. The integration of a large number of providers is a major goal as it enables the improvement of the quality of the selected resources in terms of pricing, speed, redundancy, etc. In this paper, we propose a system architecture, based on semantic solutions, to build an interoperable scheduler for federated clouds that works with several IaaS (Infrastructure as a Service) providers in a uniform way. Based on this architecture we implement a proof-of-concept prototype and test it with two different cloud solutions to provide some experimental results about the viability of our approach.

CloudRoom: una plataforma universitaria social, semántica y ubicua

Estamos viviendo la era de la Internetificación. A día de hoy, las conexiones a Internet se asumen presentes en nuestro entorno como una necesidad más. La Web, se ha convertido en un lugar de generación de contenido por los usuarios. Una información generada, que sobrepasa la idea con la que surgió esta, ya que en la mayoría de casos, su contenido no se ha diseñado más que para ser consumido por humanos, y no por máquinas. Esto supone un cambio de mentalidad en la forma en que diseñamos sistemas capaces de soportar una carga computacional y de almacenamiento que crece sin un fin aparente. Al mismo tiempo, vivimos un momento de crisis de la educación superior: los altos costes de una educación de calidad suponen una amenaza para el mundo académico. Mediante el uso de la tecnología, se puede lograr un incremento de la productividad, y una reducción en dichos costes en un campo, en el que apenas se ha avanzado desde el Renacimiento. En CloudRoom se ha diseñado una plataforma MOOC con una arquitectura ajustada a las últimas convenciones en Cloud Computing, que implica el uso de Servicios REST, bases de datos NoSQL, y que hace uso de las últimas recomendaciones del W3C en materia de desarrollo web y Linked Data. Para su construcción, se ha hecho uso de métodos ágiles de Ingeniería del Software, técnicas de Interacción Persona-Ordenador, y tecnologías de última generación como Neo4j, Redis, Node.js, AngularJS, Bootstrap, HTML5, CSS3 o Amazon Web Services. Se ha realizado un trabajo integral de Ingeniería Informática, combinando prácticamente la totalidad de aquellas áreas de conocimiento fundamentales en Informática. En definitiva se han ideado las bases de un sistema distribuido robusto, mantenible, con características sociales y semánticas, que puede ser ejecutado en múltiples dispositivos, y que es capaz de responder ante millones de usuarios. We are living through an age of Internetification. Nowadays, Internet connections are a utility whose presence one can simply assume. The web has become a place of generation of content by users. The information generated surpasses the notion with which the World Wide Web emerged because, in most cases, this content has been designed to be consumed by humans and not by machines. This fact implies a change of mindset in the way that we design systems; these systems should be able to support a computational and storage capacity that apparently grows endlessly. At the same time, our education system is in a state of crisis: the high costs of high-quality education threaten the academic world. With the use of technology, we could achieve an increase of productivity and quality, and a reduction of these costs in this field, which has remained largely unchanged since the Renaissance. In CloudRoom, a MOOC platform has been designed with an architecture that satisfies the last conventions on Cloud Computing; which involves the use of REST services, NoSQL databases, and uses the last recommendations from W3C in terms of web development and Linked Data. For its building process, agile methods of Software Engineering, Human-Computer Interaction techniques, and state of the art technologies such as Neo4j, Redis, Node.js, AngularJS, Bootstrap, HTML5, CSS3 or Amazon Web Services have been used. Furthermore, a comprehensive Informatics Engineering work has been performed, by combining virtually all of the areas of knowledge in Computer Science. Summarizing, the pillars of a robust, maintainable, and distributed system have been devised; a system with social and semantic capabilities, which runs in multiple devices, and scales to millions of users.

A multi-resource load balancing algorithm for cloud cache systems

With the advent of cloud computing model, distributed caches have become the cornerstone for building scalable applications. Popular systems like Facebook [1] or Twitter use Memcached [5], a highly scalable distributed object cache, to speed up applications by avoiding database accesses. Distributed object caches assign objects to cache instances based on a hashing function, and objects are not moved from a cache instance to another unless more instances are added to the cache and objects are redistributed. This may lead to situations where some cache instances are overloaded when some of the objects they store are frequently accessed, while other cache instances are less frequently used. In this paper we propose a multi-resource load balancing algorithm for distributed cache systems. The algorithm aims at balancing both CPU and Memory resources among cache instances by redistributing stored data. Considering the possible conflict of balancing multiple resources at the same time, we give CPU and Memory resources weighted priorities based on the runtime load distributions. A scarcer resource is given a higher weight than a less scarce resource when load balancing. The system imbalance degree is evaluated based on monitoring information, and the utility load of a node, a unit for resource consumption. Besides, since continuous rebalance of the system may affect the QoS of applications utilizing the cache system, our data selection policy ensures that each data migration minimizes the system imbalance degree and hence, the total reconfiguration cost can be minimized. An extensive simulation is conducted to compare our policy with other policies. Our policy shows a significant improvement in time efficiency and decrease in reconfiguration cost.

CloudRoom: módulo de gestión de cursos online, abiertos y masivos

La razón de este proyecto, es la de desarrollar el módulo de cursos de la plataforma de Massive Online Open Courses (MOOCs), CloudRoom. Dicho módulo está englobado en una arquitectura orientada a servicios (SOA) y en una infraestructura de Cloud Computing utilizando Amazon Web Services (AWS). Nuestro objetivo es el de diseñar un Software as a Service (SaaS) robusto con las cualidades que a un producto de este tipo se le estiman: alta disponibilidad, alto rendimiento, gran experiencia de usuario y gran extensibilidad del sistema. Para lograrlo, se llevará a cabo la integración de las últimas tendencias tecnológicas dentro del desarrollo de sistemas distribuidos como Neo4j, Node.JS, Servicios RESTful, CoffeeScript. Todo esto siguiendo un estrategia de desarrollo PLAN-DO-CHECK utilizando Scrum y prácticas de metodologías ágiles. ---ABSTRACT---The reason of this Project is to develop the courses‟ module of CloudRoom, a Massive Online Open Courses platform. This module is encapsulated in a service-oriented architecture (SOA) based on a Cloud Computing infrastructure built on Amazon Web Services (AWS). Our goal is to design a robust Software as a Service (SaaS) with the qualities that are estimated in a product of this type: high availability, high performance, great user experience and great extensibility of the system. In order to address this, we carry out the integration of the latest technology trends in the development of distributed systems: Neo4j, Node.JS, RESTful Services and CoffeeScript. All of this, following a development strategy PLAN-DO-CHECK, using Scrum and practices of agile methodologies.