Offloading Content with Self-organizing Mobile Fogs

Mobile users in an urban environment access content on the internet from different locations. It is challenging for the current service providers to cope with the increasing content demand from a large number of collocated mobile users. In-network caching to offload content at nodes closer to users alleviate the issue, though efficient cache management is required to find out who should cache what, when and where in an urban environment, given nodes limited computing, communication and caching resources. To address this, we first define a novel relation between content popularity and availability in the network and investigate a node's eligibility to cache content based on its urban reachability. We then allow nodes to self-organize into mobile fogs to increase the distributed cache and maximize content availability in a cost-effective manner. However, to cater rational nodes, we propose a coalition game for the nodes to offer a maximum "virtual cache" assuming a monetary reward is paid to them by the service/content provider. Nodes are allowed to merge into different spatio-temporal coalitions in order to increase the distributed cache size at the network edge. Results obtained through simulations using realistic urban mobility trace validate the performance of our caching system showing a ratio of 60-85% of cache hits compared to the 30-40% obtained by the existing schemes and 10% in case of no coalition

A Content-based Centrality Metric for Collaborative Caching in Information-Centric Fogs

Information-Centric Fog Computing enables a multitude of nodes near the end-users to provide storage, communication, and computing, rather than in the cloud. In a fog network, nodes connect with each other directly to get content locally whenever possible. As the topology of the network directly influences the nodes' connectivity, there has been some work to compute the graph centrality of each node within that network topology. The centrality is then used to distinguish nodes in the fog network, or to prioritize some nodes over others to participate in the caching fog. We argue that, for an Information-Centric Fog Computing approach, graph centrality is not an appropriate metric. Indeed, a node with low connectivity that caches a lot of content may provide a very valuable role in the network. To capture this, we introduce acontent-based centrality (CBC) metric which takes into account how well a node is connected to the content the network is delivering, rather than to the other nodes in the network. To illustrate the validity of considering content-based centrality, we use this new metric for a collaborative caching algorithm. We compare the performance of the proposed collaborative caching with typical centrality based, non-centrality based, and non-collaborative caching mechanisms. Our simulation implements CBC on three instances of large scale realistic network topology comprising 2,896 nodes with three content replication levels. Results shows that CBC outperforms benchmark caching schemes and yields a roughly 3x improvement for the average cache hit rate

Distribution efficace des contenus dans les réseaux : partage de ressources sans fil, planification et sécurité

In recent years, the amount of traffic requests that Internet users generate on a daily basis has increased exponentially, mostly due to the worldwide success of video streaming services, such as Netflix and YouTube. While Content-Delivery Networks (CDNs) are the de-facto standard used nowadays to serve the ever increasing users’ demands, the scientific community has formulated proposals known under the name of Content-Centric Networks (CCN) to change the network protocol stack in order to turn the network into a content distribution infrastructure. In this context this Ph.D. thesis studies efficient techniques to foster content distribution taking into account three complementary problems:1) We consider the scenario of a wireless heterogeneous network, and we formulate a novel mechanism to motivate wireless access point owners to lease their unexploited bandwidth and cache storage, in exchange for an economic incentive.2) We study the centralized network planning problem and (I) we analyze the migration to CCN; (II) we compare the performance bounds for a CDN with those of a CCN, and (III) we take into account a virtualized CDN and study the stochastic planning problem for one such architecture.3) We investigate the security properties on access control and trackability and formulate ConfTrack-CCN: a CCN extension to enforce confidentiality, trackability and access policy evolution in the presence of distributed caches.Au cours de ces dernières années, la quantité de trafic que les utilisateurs Internet produisent sur une base quotidienne a augmenté de façon exponentielle, principalement en raison du succès des services de streaming vidéo, tels que Netflix et YouTube. Alors que les réseaux de diffusion de contenu (Content-Delivery Networks, CDN) sont la technique standard utilisée actuellement pour servir les demandes des utilisateurs, la communauté scientifique a formulé des propositions connues sous le nom de Content-Centric Networks (CCN) pour changer la pile de protocoles réseau afin de transformer Internet en une infrastructure de distribution de contenu. Dans ce contexte, cette thèse de doctorat étudie des techniques efficaces pour la distribution de contenu numérique en tenant compte de trois problèmes complémentaires : 1) Nous considérons le scénario d’un réseau hétérogène sans fil, et nous formulons un mécanisme pour motiver les propriétaires des points d’accès à partager leur capacité WiFi et stockage cache inutilisés, en échange d’une contribution économique.2) Nous étudions le problème centralisé de planification du réseau en présence de caches distribuées et (I) nous analysons la migration optimale du réseau à CCN; (II) nous comparons les bornes de performance d’un réseau CDN avec ceux d’un CCN, et (III) nous considérons un réseau CDN virtualisé et étudions le problème stochastique de planification d’une telle infrastructure.3) Nous considérons les implications de sécurité sur le contrôle d’accès et la traçabilité, et nous formulons ConfTrack-CCN, une extension deCCN utilisée pour garantir la confidentialité, traçabilité et l’évolution de la politique d’accès, en présence de caches distribuées

Introducing Development Features for Virtualized Network Services

Network virtualization and softwarizing network functions are trends aiming at higher network efficiency, cost reduction and agility. They are driven by the evolution in Software Defined Networking (SDN) and Network Function Virtualization (NFV). This shows that software will play an increasingly important role within telecommunication services, which were previously dominated by hardware appliances. Service providers can benefit from this, as it enables faster introduction of new telecom services, combined with an agile set of possibilities to optimize and fine-tune their operations. However, the provided telecom services can only evolve if the adequate software tools are available. In this article, we explain how the development, deployment and maintenance of such an SDN/NFV-based telecom service puts specific requirements on the platform providing it. A Software Development Kit (SDK) is introduced, allowing service providers to adequately design, test and evaluate services before they are deployed in production and also update them during their lifetime. This continuous cycle between development and operations, a concept known as DevOps, is a well known strategy in software development. To extend its context further to SDN/NFV-based services, the functionalities provided by traditional cloud platforms are not yet sufficient. By giving an overview of the currently available tools and their limitations, the gaps in DevOps for SDN/NFV services are highlighted. The benefit of such an SDK is illustrated by a secure content delivery network service (enhanced with deep packet inspection and elastic routing capabilities). With this use-case, the dynamics between developing and deploying a service are further illustrated