4,008 research outputs found

    Semantic-based policy engineering for autonomic systems

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    This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

    Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

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    Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

    End-to-end elasticity control of cloud-network slices

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    The design of efficient elasticity control mechanisms for dynamic resource allocation is crucial to increase the efficiency of future cloud-network slice-defined systems. Current elasticity control mechanisms proposed for cloud- or network-slicing, only consider cloud- or network-type resources respectively. In this paper, we introduce the elaSticity in cLOud-neTwork Slices (SLOTS) which aims to extend the horizontal elasticity control to multi-providers scenarios in an end-to-end fashion, as well as to provide a novel vertical elasticity mechanism to deal with critical insufficiency of resources by harvesting underused resources on other slices. Finally, we present a preliminary assessment of the SLOTS prototype in a real testbed, revealing outcomes that suggest the viability of the proposal.Peer ReviewedPostprint (published version

    A Role for Contextualised Knowledge in Autonomic Communications

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    Towards autonomic networking and selfconfigurating routers

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    IP Networks, and particularly the Internet, were proposed to be a simple and robust support for heterogeneous communications. This implies that only basic controls have to be done by network elements. Connection management, along with transport, and more generally communication management, has to be done by the terminals. For example, error detection mechanisms, error recovery mechanisms with “Slow Start”, are implemented within the transport protocol, managed by the terminals. However, integration of new services and increasing need for QoS require the network to be more and more flexible and adaptive. New algorithms and protocols are then proposed to address these issues, and include new configuration layers. Manual configuration of such network architectures is then very complex, if not impossible. We think that future core network elements will have to be more adaptive, but also more autonomic. Autoconfiguration is indeed a necessary condition to integrate new services in the network. We believe that autoconfiguration requires new knowledge provisioning and computing policies. This paper then presents an architecture of software agents, collaborative and autonomic. These agents are embedded inside the routers. Their role is to share local and situated knowledge, in order to control and optimize the existing control mechanism of the router.5th IFIP International Conference on Network Control & Engineering for QoS, Security and MobilityRed de Universidades con Carreras en Informática (RedUNCI

    Distributed collaborative knowledge management for optical network

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    Network automation has been long time envisioned. In fact, the Telecommunications Management Network (TMN), defined by the International Telecommunication Union (ITU), is a hierarchy of management layers (network element, network, service, and business management), where high-level operational goals propagate from upper to lower layers. The network management architecture has evolved with the development of the Software Defined Networking (SDN) concept that brings programmability to simplify configuration (it breaks down high-level service abstraction into lower-level device abstractions), orchestrates operation, and automatically reacts to changes or events. Besides, the development and deployment of solutions based on Artificial Intelligence (AI) and Machine Learning (ML) for making decisions (control loop) based on the collected monitoring data enables network automation, which targets at reducing operational costs. AI/ML approaches usually require large datasets for training purposes, which are difficult to obtain. The lack of data can be compensated with a collective self-learning approach. In this thesis, we go beyond the aforementioned traditional control loop to achieve an efficient knowledge management (KM) process that enhances network intelligence while bringing down complexity. In this PhD thesis, we propose a general architecture to support KM process based on four main pillars, which enable creating, sharing, assimilating and using knowledge. Next, two alternative strategies based on model inaccuracies and combining model are proposed. To highlight the capacity of KM to adapt to different applications, two use cases are considered to implement KM in a purely centralized and distributed optical network architecture. Along with them, various policies are considered for evaluating KM in data- and model- based strategies. The results target to minimize the amount of data that need to be shared and reduce the convergence error. We apply KM to multilayer networks and propose the PILOT methodology for modeling connectivity services in a sandbox domain. PILOT uses active probes deployed in Central Offices (COs) to obtain real measurements that are used to tune a simulation scenario reproducing the real deployment with high accuracy. A simulator is eventually used to generate large amounts of realistic synthetic data for ML training and validation. We apply KM process also to a more complex network system that consists of several domains, where intra-domain controllers assist a broker plane in estimating accurate inter-domain delay. In addition, the broker identifies and corrects intra-domain model inaccuracies, as well as it computes an accurate compound model. Such models can be used for quality of service (QoS) and accurate end-to-end delay estimations. Finally, we investigate the application on KM in the context of Intent-based Networking (IBN). Knowledge in terms of traffic model and/or traffic perturbation is transferred among agents in a hierarchical architecture. This architecture can support autonomous network operation, like capacity management.La automatización de la red se ha concebido desde hace mucho tiempo. De hecho, la red de gestión de telecomunicaciones (TMN), definida por la Unión Internacional de Telecomunicaciones (ITU), es una jerarquía de capas de gestión (elemento de red, red, servicio y gestión de negocio), donde los objetivos operativos de alto nivel se propagan desde las capas superiores a las inferiores. La arquitectura de gestión de red ha evolucionado con el desarrollo del concepto de redes definidas por software (SDN) que brinda capacidad de programación para simplificar la configuración (descompone la abstracción de servicios de alto nivel en abstracciones de dispositivos de nivel inferior), organiza la operación y reacciona automáticamente a los cambios o eventos. Además, el desarrollo y despliegue de soluciones basadas en inteligencia artificial (IA) y aprendizaje automático (ML) para la toma de decisiones (bucle de control) en base a los datos de monitorización recopilados permite la automatización de la red, que tiene como objetivo reducir costes operativos. AI/ML generalmente requieren un gran conjunto de datos para entrenamiento, los cuales son difíciles de obtener. La falta de datos se puede compensar con un enfoque de autoaprendizaje colectivo. En esta tesis, vamos más allá del bucle de control tradicional antes mencionado para lograr un proceso eficiente de gestión del conocimiento (KM) que mejora la inteligencia de la red al tiempo que reduce la complejidad. En esta tesis doctoral, proponemos una arquitectura general para apoyar el proceso de KM basada en cuatro pilares principales que permiten crear, compartir, asimilar y utilizar el conocimiento. A continuación, se proponen dos estrategias alternativas basadas en inexactitudes del modelo y modelo de combinación. Para resaltar la capacidad de KM para adaptarse a diferentes aplicaciones, se consideran dos casos de uso para implementar KM en una arquitectura de red óptica puramente centralizada y distribuida. Junto a ellos, se consideran diversas políticas para evaluar KM en estrategias basadas en datos y modelos. Los resultados apuntan a minimizar la cantidad de datos que deben compartirse y reducir el error de convergencia. Aplicamos KM a redes multicapa y proponemos la metodología PILOT para modelar servicios de conectividad en un entorno aislado. PILOT utiliza sondas activas desplegadas en centrales de telecomunicación (CO) para obtener medidas reales que se utilizan para ajustar un escenario de simulación que reproducen un despliegue real con alta precisión. Un simulador se utiliza finalmente para generar grandes cantidades de datos sintéticos realistas para el entrenamiento y la validación de ML. Aplicamos el proceso de KM también a un sistema de red más complejo que consta de varios dominios, donde los controladores intra-dominio ayudan a un plano de bróker a estimar el retardo entre dominios de forma precisa. Además, el bróker identifica y corrige las inexactitudes de los modelos intra-dominio, así como también calcula un modelo compuesto preciso. Estos modelos se pueden utilizar para estimar la calidad de servicio (QoS) y el retardo extremo a extremo de forma precisa. Finalmente, investigamos la aplicación en KM en el contexto de red basada en intención (IBN). El conocimiento en términos de modelo de tráfico y/o perturbación del tráfico se transfiere entre agentes en una arquitectura jerárquica. Esta arquitectura puede soportar el funcionamiento autónomo de la red, como la gestión de la capacidad.Postprint (published version

    A Computational Field Framework for Collaborative Task Execution in Volunteer Clouds

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    The increasing diffusion of cloud technologies is opening new opportunities for distributed and collaborative computing. Volunteer clouds are a prominent example, where participants join and leave the platform and collaborate by sharing their computational resources. The high dynamism and unpredictability of such scenarios call for decentralized self-* approaches to guarantee QoS. We present a simulation framework for collaborative task execution in volunteer clouds and propose one concrete instance based on Ant Colony Optimization, which is validated through a set of simulation experiments based on Google workload data

    A survey of self organisation in future cellular networks

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    This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

    Service-oriented networking architecture

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    University of Technology, Sydney. Faculty of Information Technology.Demand for new services offered across shared networking infrastructure, such as the Internet, is at an ever increasing level. Everyday, innovative services are continuously being proposed and developed to meet end users' demands. However, the monolithic and inflexible design of current networking infrastructure constrains the deployment of such new services. Current networking infrastructure consists of a fixed set of connectivity functions governed by static overlays of Service Level Agreements between administrative boundaries. This infrastructure hinders new service deployment to a slow process of standardisation and legal agreements, and requires large capital expenditure for the roll out of new network elements. Service-Oriented Networking is a new paradigm aimed at transforming networking infrastructure to meet new demands in a responsive and inexpensive manner. It proposes enabling on-demand introduction of services across shared and heterogeneous networking infrastructure. However, architecting the building blocks of a feasible service-oriented network poses many critical research challenges. The first challenge is in providing an architecture that enables on-demand injection and programmability of services. This architecture must not compromise current scalability and performance levels of networks. Furthermore, due to the heterogeneous nature of networks, this architecture must cater for a large number of platforms with varying capabilities. The second challenge is in enforcing security among services of competing entities on leveraging shared infrastructure. With the possibility of faulty or malicious services being deployed, mechanisms are needed to impose isolation of risk to maintain a robust network. These mechanisms must scale to a large number of entities and should not impose restrictions on programmability that would limit the operations of services. Furthermore, this needs to be achieved without the introduction of checking operations in the path of network traffic which would impede the performance of the network. The third challenge is in guaranteeing Quality of Service (QoS) levels across competing services in a differentiated and fair manner. Providing QoS guarantee would no longer be just a problem of bandwidth allocation but would now involve the allocation of computational resources needed in the fulfilment of a service. The critical issue is in formulating a resource allocation scheme among competing services where resource requirements or availability cannot be predetermined. Again, any mechanism used must be scalable for large numbers of services. Recent research in the fields of Active and Programmable Networks has produced novel architectures which adopt user-extensible software components or programmable network processors to enable rapid service deployment. However, it is currently impractical to adopt such concepts as the associated challenges (outlined above) have only been partially addressed. Meanwhile, commercial platforms are becoming both faster and increasingly more programmable. However, commercial manufacturers have developed their platforms in a proprietary and closed manner, thereby restricting users from deploying new services or customising existing services. This thesis explores a holistic approach to overcoming the challenges of Service-Oriented Networks. Specifically, it presents a new and novel architecture called Serviter: a new Service-Oriented Network Architecture for Shared Networks. With this architecture, a new class of network elements enriched with programmable functionality can be deployed to serve as the fundamental building blocks of a new Service-Oriented Networking model. Under this model, service provisioning responsibilities are divided among manufacturers, network providers, and service providers. Manufacturers' responsibilities focus on the provisioning of increasingly programmable high-performance infrastructure and their system-level drivers. Network providers are responsible for the management of their infrastructure, which would be divided into isolated shares and opened to third party service providers. The service providers are then able to deploy new services within their shares of a domain. These services can then be aggregated across domains to provision end-to-end services through the purchase of dedicated shares, or a collaborative model, spanning the required paths. Serviter enables on-demand service deployment onto commercial programmable platforms leveraging their high performance and scalability characteristics. These characteristics are maintained by enforcing the separation of the control and the forwarding planes. A programmability interface is provided through a layer of System Services. To cater for the heterogeneous nature of networks, the System Services layer is extensible. It enables each manufacturer to utilise a unified programmability approach to develop and deploy new System Services to exploit the functionality of their reprogrammable hardware. The programmability of the underlying modules is offered through a structured and flexible approach of Active Flow Manipulation (AFM) Paths. Users deploy User Services that construct AFM Paths to offer new network services. Serviter introduces novel scalable and simple partitioning techniques to address the issues of network integrity and security. Serviter provides each service provider with a secure, separate, and resource assured partition, representing a 'Virtual Router', to accommodate their services. These partitions span all components and restrict services from constructing AFM Paths on traffic outside of the Virtual Networks associated with their partition. To allocate internal router resources among competing partitions and among services within a partition, Serviter employs a scalable and autonomic resource management model called Control plane-Quality of Service {C-QoS). Due to the difficulty of determining resource availability in heterogeneous infrastructure or service resource requirements, this model is dynamically adaptive to demand and availability patterns on a per resource basis. To demonstrate the significance of the new architecture, this thesis presents an implementation of Serviter along with its deployment onto an advanced commercial networking platform. The implementation is assessed and evaluated for its ability to map on to commercial infrastructure, its partitioning enforcement, and its overall performance and scalability. This platform is used to implement novel services demonstrating Serviter capabilities. It is shown that Serviter is capable of facilitating on-demand deployment of a variety of services constrained by forward plane capabilities. This architecture opens the opportunity for service-oriented networking in large-scale shared networks, putting forth new challenging issues in the complete automation of service deployment - specifically, capability discovery, location selection, and dynamic domain aggregation to provide end-to-end service construction

    Algorithms for advance bandwidth reservation in media production networks

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    Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results
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