Toward a new addressing scheme for a service-centric Internet

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Traditional network architectures based on the Internet Protocol (IP) are now being questioned by the research community, since they are no longer positioned as the most suitable paradigm for supporting the increasing diversity of applications and uses of the Internet. A key issue in this subject is that, although the IP protocol has provided the basis for the rapid evolution of the Internet, its addressing scheme is not prepared to face the challenges posed by many foreseen applications. In light of this, different initiatives worldwide have started specific research programs to address these problems and work toward the "Future Internet". The TARIFA project represents one of these initiatives, and it is positioned as a clean slate alternative aimed at overcoming the critical issues in today's Internet. The novelty in TARIFA resides in the fact that any “commodity” in the network can be composed as a set of atomic services, which can be in turn assembled through a service-centric model for building a promising Internet architecture. In this paper, we focus on the space requirements and set the basis for a new addressing scheme suitable for service-centric network architectures such as the one proposed by TARIFA. The addressing scheme discussed in this paper is general in scope, and could be applied not only to architectures based on the composition of services but also to user and data-centric Internet architectures.This work was supported in part by the TARIFA project, by the Spanish Ministry of Science and Innovation under contract TEC2009-07041, and by the Catalan Research Council (CIRIT) under contract 2009 SGR1508.Postprint (author's final draft

Addressing the Challenges in Federating Edge Resources

This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

Service-centric networking

This chapter introduces a new paradigm for service centric networking. Building upon recent proposals in the area of information centric networking, a similar treatment of services – where networked software functions, rather than content, are dynamically deployed, replicated and invoked – is discussed. Service-centric networking provides the mechanisms required to deploy replicated service instances across highly distributed networked cloud infrastructures and to route client requests to the closest instance while providing more efficient network infrastructure usage, improved QoS and new business opportunities for application and service providers. </jats:p

Integración de inteligencia en la MIB del Modelo OSI para la gestión de redes de telecomunicaciones

La Gestión de red se define como el conjunto de actividades dedicadas al control y vigilancia de los recursos existentes en las redes de telecomunicaciones. En los complejos sistemas actuales, es necesario realizar una gestión de la red asistida por un software avanzado. La Inteligencia Artificial se incorpora a la gestión de las redes, con el fin de facilitar labores de administración y control de toda la información que proviene de los recursos gestionados, dando origen a la Gestión Inteligente de las Redes. Este nuevo paradigma, proporciona a los sistemas de gestión de un mayor grado de cohesión con las tecnologías de comunicaciones actuales, a la vez de disponer de todas las posibilidades y ventajas aportadas por la Inteligencia Artificial. Nuestro estudio tiene como objetivo perfeccionar las técnicas actuales de gestión. Para ello se establecen mecanismos que permiten una mayor correlación entre las especificaciones de la red y las aplicaciones que efectúan el tratamiento de la información de gestión. Presentamos una nueva concepción denominada “Gestión Inteligente Integrada” y una extensión del modelo de gestión OSI, que contempla la inclusión del conocimiento de gestión, en las propias especificaciones de los objetos gestionados. Este modelo consigue reunir conceptos que actualmente pertenecen a distintos ámbitos de estudio, la Inteligencia Artificial y la Información de Gestión del sistema. De esta forma se obtiene una solución global, que permite a los administradores de redes utilizar la potencia aportada por la Inteligencia Artificial, en particular de los Sistemas Expertos, de una forma sencilla y transparente

Dimensioning the future pan-European optical network with energy efficiency considerations

This paper studies the overall energy consumption of a pan-European optical transport network for three different time periods: today and in five and ten years from now. In each time period the pan-European network was dimensioned using traffic predictions based on realistic data generated by the optical networking roadmap developed in the framework of the European project Building the Future Optical Network in Europe-BONE. A wavelength routed wavelength division multiplexed optical network based on either transparent or opaque node architectures was examined considering exclusively either 10 Gbit/s or 40 Gbit/s per channel data rates. The results manifest that transparent optical networking technologies are expected to provide significant energy savings of the order of 35% to 55%. It was also shown that the migration towards higher data rates, i.e., from 10 Gbit/s to 40 Gbit/s, is assisting in improving the overall energy efficiency of the network

KinD-LCE Curve Estimation And Retinex Fusion On Low-Light Image

Low-light images often suffer from noise and color distortion. Object detection, semantic segmentation, instance segmentation, and other tasks are challenging when working with low-light images because of image noise and chromatic aberration. We also found that the conventional Retinex theory loses information in adjusting the image for low-light tasks. In response to the aforementioned problem, this paper proposes an algorithm for low illumination enhancement. The proposed method, KinD-LCE, uses a light curve estimation module to enhance the illumination map in the Retinex decomposed image, improving the overall image brightness. An illumination map and reflection map fusion module were also proposed to restore the image details and reduce detail loss. Additionally, a TV(total variation) loss function was applied to eliminate noise. Our method was trained on the GladNet dataset, known for its diverse collection of low-light images, tested against the Low-Light dataset, and evaluated using the ExDark dataset for downstream tasks, demonstrating competitive performance with a PSNR of 19.7216 and SSIM of 0.8213.Comment: Accepted by Signal, Image and Video Processin

Identifier-Based Discovery in Large-Scale Networks

The design of any network mechanism that requires collaboration among selfish agents could only benefit from accounting for the complex social and economic interactions and incentives of the agents using the design. This chapter presents a broad treatment of the main economic issues that arise in the context of identifier-based discovery on large scale networks, particularly on the Internet. An “identified” object (such as a node or service), referred to as a player, demands to be discoverable by the rest of the network on its “identifier”. A discovery scheme provides such a service to the players and incurs a cost for doing so. Providing such a service while accounting for the cost and making sure that the incentives of the players are aligned is the general economic problem that we address in this work. After introducing the identifier-based discovery problem, we present a taxonomy of discovery schemes and proposals based on their business model and we pose several questions that are becoming increasingly important as we proceed to design the inter-network of the future. An incentive model for distributed discovery in the context of the Border Gateway Protocol (BGP) and path-vector protocols in general is then presented. We model BGP route distribution and computation using a game in which a BGP speaker advertises its prefix to its direct neighbors promising them a reward for further distributing the route deeper into the network. The neighbors do the same thing with their direct neighbors, and so on. The result of this cascaded route distribution is a globally advertised prefix and hence discoverability. We present initial results on the existence of equilibria in the game and we motivate our ongoing work

A HyperNet Architecture

Network virtualization is becoming a fundamental building block of future Internet architectures. By adding networking resources into the “cloud”, it is possible for users to rent virtual routers from the underlying network infrastructure, connect them with virtual channels to form a virtual network, and tailor the virtual network (e.g., load application-specific networking protocols, libraries and software stacks on to the virtual routers) to carry out a specific task. In addition, network virtualization technology allows such special-purpose virtual networks to co-exist on the same set of network infrastructure without interfering with each other. Although the underlying network resources needed to support virtualized networks are rapidly becoming available, constructing a virtual network from the ground up and using the network is a challenging and labor-intensive task, one best left to experts. To tackle this problem, we introduce the concept of a HyperNet, a pre-built, pre-configured network package that a user can easily deploy or access a virtual network to carry out a specific task (e.g., multicast video conferencing). HyperNets package together the network topology configuration, software, and network services needed to create and deploy a custom virtual network. Users download HyperNets from HyperNet repositories and then “run” them on virtualized network infrastructure much like users download and run virtual appliances on a virtual machine. To support the HyperNet abstraction, we created a Network Hypervisor service that provides a set of APIs that can be called to create a virtual network with certain characteristics. To evaluate the HyperNet architecture, we implemented several example Hyper-Nets and ran them on our prototype implementation of the Network Hypervisor. Our experiments show that the Hypervisor API can be used to compose almost any special-purpose network – networks capable of carrying out functions that the current Internet does not provide. Moreover, the design of our HyperNet architecture is highly extensible, enabling developers to write high-level libraries (using the Network Hypervisor APIs) to achieve complicated tasks

Resource allocation in information-centric wireless networking with D2D-enabled MEC: A deep reinforcement learning approach

Recently, information-centric wireless networks (ICWNs) have become a promising Internet architecture of the next generation, which allows network nodes to have computing and caching capabilities and adapt to the growing mobile data traffic in 5G high-speed communication networks. However, the design of ICWN is still faced with various challenges with respect to capacity and traffic. Therefore, mobile edge computing (MEC) and device-to-device (D2D) communications can be employed to aid offloading the core networks. This paper investigates the optimal policy for resource allocation in ICWNs by maximizing the spectrum efficiency and system capacity of the overall network. Due to unknown and stochastic properties of the wireless channel environment, this problem was modeled as a Markov decision process. In continuousvalued state and action variables, the policy gradient approach was employed to learn the optimal policy through interactions with the environment. We first recognized the communication mode according to the location of the cached content, considering whether it is D2D mode or cellular mode. Then, we adopt the Gaussian distribution as the parameterization strategy to generate continuous stochastic actions to select power. In addition, we use softmax to output channel selection to maximize system capacity and spectrum efficiency while avoiding interference to cellular users. The numerical experiments show that our learning method performs well in a D2D-enabled MEC system. 2020 Association for Computing Machinery. All rights reserved.This work was supported in part by the National Natural Science Foundation of China under Grant 61772387, in part by the Fundamental Research Funds of Ministry of Education and China Mobile under Grant MCM20170202, in part by the National Natural Science Foundation of Shaanxi Province under Grant 2019ZDLGY03-03, in part by the Graduate Innovation Fund of Xidian University under Grant 5001-20109195456, and in part by the ISN State Key Laboratory.Scopus2-s2.0-8507753100