715 research outputs found
A Light-Weight Forwarding Plane for Content-Centric Networks
We present CCN-DART, a more efficient forwarding approach for content-centric
networking (CCN) than named data networking (NDN) that substitutes Pending
Interest Tables (PIT) with Data Answer Routing Tables (DART) and uses a novel
approach to eliminate forwarding loops. The forwarding state required at each
router using CCN-DART consists of segments of the routes between consumers and
content providers that traverse a content router, rather than the Interests
that the router forwards towards content providers. Accordingly, the size of a
DART is proportional to the number of routes used by Interests traversing a
router, rather than the number of Interests traversing a router. We show that
CCN-DART avoids forwarding loops by comparing distances to name prefixes
reported by neighbors, even when routing loops exist. Results of simulation
experiments comparing CCN-DART with NDN using the ndnSIM simulation tool show
that CCN-DART incurs 10 to 20 times less storage overhead
Information protection in content-centric networks
Information-centric networks have distinct advantages with regard to securing sensitive content as a result of their new approaches to managing data in potential future internet architectures. These kinds of systems, because of their data-centric perspective, provide the opportunity to embed policy-centric content management components that can address looming problems in information distribution that both companies and federal agencies are beginning to face with respect to sensitive content. This information-centricity facilitates the application of security techniques that are very difficult and in some cases impossible to apply in traditional packetized networks. This work addresses the current state of the art in both these kinds of cross-domain systems and information-centric networking in general. It then covers other related work, outlining why information-centric networks are more powerful than traditional packetized networks with regard to usage management. Then, it introduces a taxonomy of types of policy-centric usage managed information network systems and an associated methodology for evaluating the individual taxonomic elements. It finally delves into experimental evaluation of the various defined architectural options and presents results of comparing experimental evaluation with anticipated outcomes
PIT Overload Analysis in Content Centric Networks
Content Centric Networking represents a paradigm shift in the evolution and definition of modern network protocols. Many research efforts have been made with the purpose of proving the feasibility and the scalability of this proposal. Our main contribution is to provide an analysis of the Pending Interest Table memory requirements in real deployment scenarios, especially considering the impact of distributed denial of service attacks. In fact, the state that the protocol maintains for each resource request makes the routers more prone to resources exhaustion issues than in traditional stateless solutions. Our results are derived by using a full custom simulator and considering the different node architectures that have been proposed as valid reference models. The main outcomes point out differentiated weaknesses in each architecture we investigated and underline the need for improvements in terms of security and scalabilit
Enhancing multi-source content delivery in content-centric networks with fountain coding
Fountain coding has been considered as especially suitable for lossy environments, such as wireless networks, as it provides redundancy while reducing coordination overheads between sender(s) and receiver(s). As such it presents beneficial properties for multi-source and/or multicast communication. In this paper we investigate enhancing/increasing multi-source content delivery efficiency in the context of Content-Centric Networking (CCN) with the usage of fountain codes. In particular, we examine whether the combination of fountain coding with the in-network caching capabilities of CCN can further improve performance. We also present an enhancement of CCN's Interest forwarding mechanism that aims at minimizing duplicate transmissions that may occur in a multi-source transmission scenario, where all available content providers and caches with matching (cached) content transmit data packets simultaneously. Our simulations indicate that the use of fountain coding in CCN is a valid approach that further increases network performance compared to traditional schemes
Efficient caching in content-centric networks using OpenFlow
International audienceContent-Centric Networking (CCN) is designed for efficient content dissemination and supports caching contents on the path from content providers to content consumers to improve user experience and reduce costs. However, this strategy is not optimal inside a domain. In this paper, we propose a solution to improve caching in CCN using a Software-Defined Networking approach
NetCodCCN: A network coding approach for content-centric networks
Content-Centric Networking (CCN) naturally supports multi-path communication, as it allows the simultaneous use of multiple interfaces (e.g. LTE and WiFi). When multiple sources and multiple clients are considered, the optimal set of distribution trees should be determined in order to optimally use all the available interfaces. This is not a trivial task, as it is a computationally intense procedure that should be done centrally. The need for central coordination can be removed by employing network coding, which also offers improved resiliency to errors and large throughput gains. In this paper, we propose NetCodCCN, a protocol for integrating network coding in CCN. In comparison to previous works proposing to enable network coding in CCN, NetCodCCN permits Interest aggregation and Interest pipelining, which reduce the data retrieval times. The experimental evaluation shows that the proposed protocol leads to significant improvements in terms of content retrieval delay compared to the original CCN. Our results demonstrate that the use of network coding adds robustness to losses and permits to exploit more efficiently the available network resources. The performance gains are verified for content retrieval in various network scenarios
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