Enhancing cache robustness for content-centric networking

<p class="JESTECAbstract">Content Centric Networking (CCN) is a modern architecture that got wide attention in the current researches as a substitutional for the current IP-based architecture. Many studies have been investigated on this novel architecture but only little of them focused on Pending Interest Table (PIT) which is very important component in every CCN router. PIT has fundamental role in packet processing in both upstream process (Interest packets) and downstream process (Data packets). PIT must be fast enough in order to not become an obstruction in the packet processing and also it must be big enough to save a lot of incoming information. In this paper, we suggest a new PIT design and implementation named CF-PIT for CCN router. Our PIT design depends on modifying and utilizing an approximate data structure called Cuckoo filter (CF). Cuckoo filter has ideal characteristics like: high insertion/query/deletion performance, acceptable storage demands and false positive probability which make it with our modification convenient for PIT implementation. The experimental results showed that our CF-PIT design has high performance in different side of views which make it very suitable to be implemented on CCN routers.</p>

Content Centric Networking (CCN) is a new architecture for a future Internet. CCN is a clean-state architecture that targets the distribution of content. As such, content is located at the heart of the architecture and CCN includes two main features: communication led by names and caches everywhere. Nevertheless, CCN has been criticized due to the economical cost of replacing every IP router with a CCN router. As such, we assume that CCN will be used for small content delivery networks –Micro CDNs– located in the ISP facilities: it has already been shown that with only 100MB of caches in the ISP facilities, the ISP traffic to the Internet can be reduced by 25%. As a matter of fact, if CCN is deployed as a Micro CDN, gateways must exist to interconnect the CDN network with the Internet. In this paper, we study the advantages of using multiple gateways against a single gateway and its impact on the caching features. Our results show that multiple gateways are beneficial not only because they improve the performance of caches but also because the load of the network get distributed across several nodes.

Content Centric Networking (CCN) is a modern suggested networking architecture that aims to utilizing named data rather than named hosts for communication in order to override the limitations of the existing IP architecture. Every content in CCN paradigm is specified by its name and every packet holds a CCN name that defines the required content. Forwarding Information Base (FIB) table is one of the most significant components in any CCN router that have crucial functions in packet forwarding process. Designing a scalable FIB table that have the ability to perform quick look up on changeable-length hierarchical CCN names can be considered as a challenge in CCN paradigm. In this paper, a new design of FIB table for CCN networks has been suggested. Our design depends on modifying a Cuckoo filter (CF), an already proposed query data structure, and utilizing the resulted modified version of CF as a FIB table (we called CF-FIB). Our evaluation show that CF-FIB have the ability to attain perfect search speed and offer very acceptable scalability to large-scale prefix tables.

Recently, content centric networking (CCN) attracts attention as a next generation network on which every router forwards a packet to another router and also functions as a server. A CCN router has a forwarding table called FIB (Forwarding Information Base) but its table look-up can become a bottleneck. In this paper, we propose FIB data structure for CCN routers which can reduce the number of comparisons in its look-up table. Our proposed FIB is composed of a bloom filter and a hash table and each hash entry is connected to a balanced binary-search tree. By using our FIB, the number of comparisons cannot much increase even if hash collisions occur. Experimental results demonstrate the effectiveness of the proposed FIB over the several existing methods.

Recently, Content-Centric Networking (CCN) has been paid more and more attention. The modeling of CCN as an important research point is the foundation of the architecture. The past work of cache network modeling always assumes the virtual round trip time (VRTT) is zero for simplicity. However, this assumption isn't practical and results in model error especially in CCN. CCN's router can aggregate the content requests during the VRTT to avoid content delivery repeatedly. Thus, to modeling CCN data transfer, as well as understanding how it should be managed, the VRTT shouldn't be ignored. In this paper, we model the data transfer in CCN, and propose a multi-cache with aggregation approximation (MCAA) algorithm to get the content miss rate and VRTT at each router. Simulation results show the validity of our MCAA algorithm.

Content-Centric Network (CCN) is next generation internet communication technology to provide existing internet communication paradigm as content based communication for efficient use various information in the Internet. Therefore, unlike existing internet communication technology, which focus on host based communication process, all ofresource is defined as contents in CCN.Moreover it focuses on purpose of communication for using information.CCN communicate with between routers through broadcast flooding method in their network environments.This characteristic of CCN is not considering increasing network traffic about each of CCN routers.Therefore, when the requesters are rapidly increased to particular CCN router, network congestion may be occurred by broadcast traffic.Moreover, this characteristic of CCN has low turnaround time about user request due to reducing performance of network system.To resolve this problem, this paper proposes a traffic aware routing protocol for congestion avoidance in CCN.The proposed routing protocol considers rapidly increasing traffic in the situation and establishes another routing path to avoid increasing traffic problem in CCN.

Content-Centric Network (CCN) provides a cleanslate design for the Internet, where content becomes the primitive of communications. In CCN, routers are equipped with content stores, which act as caches for frequently requested content. This design enables the Internet to provide content distribution services without any application-layer support. On the other hand, as caches are integrated into routers, the overall performance of CCN will be influenced by the caching efficiency. This paper studies the performance issues of caches in CCN, with the aim to gain some understanding on how caches should be designed to maintain a high performance in a cost-efficient way. Specifically, we use a two-dimensional discrete-time Markov chain to model the two-layer cache hierarchy formed by CCN routers, and develop an efficient algorithm to calculate the hit ratios of these caches. Simulations validate the accuracy of our modeling method, and convey some understanding on cache design in CCN.

Content Centric Networking (CCN) is a novel network paradigm in which the communication process focusses on content rather than the host. In the current network architecture, routers forward the incoming packets based on the routing information that already had. Whereas, forwarding decisions in CCN are taken depending on networks situation. The contents in CCN are retrieved depending on their names which are URL like names that are composing of a number of string parts separated by’/’. These names are stored inside a specific data structure, called Forwarding Information Base (FIB), inside CCN routers and they are used to forward any incoming packet. Therefore, the main two challenges that face the design of FIB table are: search speed and storage utilization. Consequently, in this paper, we propose a new name matching technique (named BF-QF FIB) to design and implement a FIB table in CCN routers in order to decrease the storage utilization and to increase the lookup speed. This technique utilizes two kinds of query data structures: Bloom filter (BF) and Quotient filter (QF) as its main data structures. The utilization of these two data structures will ensure low memory usage and high lookup speed. The results of our evaluation show that BF-QF FIB can guarantee high search rate and offer perfect scalability to large FIB tables.

Since Internet of Things (IoT) communications can enjoy many advantages brought by content-centric networking (CCN) in nature, there is an increasing interest on their integration for better information retrieval and distribution. Nevertheless, different from the conventional multimedia traffic of which contents are hardly changed, IoT data are always transient and updated by their producers according to the actual situation. As a result, if without any effective countermeasures, outdated copies are inevitably stored by CCN routers and then distributed to the associated consumers, degrading both caching efficiency and user experience. In fact, most of related policies take little account of information freshness for cached contents, and how to tackle transient IoT data in CCN is still an ignored but crucial issue required for further explorations. Therefore, in this article, we propose an efficient popularity-based cache consistency management scheme, which aims to guarantee freshness of IoT data returned by on-path routers and avoid heavy signalling costs introduced at the same time. Extensive simulations were performed under both real-world scare-free and binary-tree topologies, and corresponding results have proved the efficiency of the proposed scheme in timely evictions of outdated IoT data stored by CCN in-network caching.

Content Centric Networking (CCN), a future Internet architecture, brings new challenges in maintaining the Quality of Experience (QoE) for video streaming. Because of the universal caching capability of CCN routers, streaming from multiple sources will be common, and switching between content sources might affect QoE by inducing delays and consequently stalls in video playback. This paper proposes a new QoE-aware multi-source video streaming scheme for CCN. First, the content distributions of video files among CCN nodes for different caching methods are studied. Second, an adaptive video streaming with distributed caching (ASDC) algorithm is designed to guarantee QoE during the switching between content sources. The ASDC algorithm considers the delivery of scalable video streams. It automatically adapts the layers in a video stream when there is source switching, based on a QoE model that characterizes the effect of stalling. Experimental results show that the ASDC algorithm outperforms dynamic adaptive streaming over HTTP (DASH) in the CCN platform in terms of the QoE obtained from human subjective tests.

The Content Centric Networking (CCN) architectural framework is designed with the central abstraction of content distribution rather than host-to-host connectivity. CCN has several advantages such as inherent router caching, lower content retrieval time and network load reduction. However, it also faces various challenges such as scalability, deployment and storage issues. In particular, the routing state information that needs to be maintained in the CCN routers leads to very high memory requirements that might not be met using current technologies. If the routing state information stored in the routers is reduced, it leads to flooding of interest packets increasing congestion in the network. The objective of this paper is to propose techniques that avoid congestion due to interest flooding in CCN while having low router memory requirements. We have proposed three different algorithms to address this problem and present their performance using discrete-event simulation models.

Content Centric Networking (CCN) is an emerging next-generation network infrastructure around content dissemination and retrieval, shifting from physical locations to named data. The built-in caching capacity of CCN, termed as in-network caching, promises to enable fast and effective content distribution at a global scale. Because of the in-network caching, the caching strategy of content location potentially affects how to make content searching decisions, while content searching in return decides in which routers content are stored. The relationship between content caching location and content searching has not been fully exploited in CCN or further used for the whole network performance improvement. This paper exploits the content caching location and content searching mechanism of CCN, and proposes a Popularity-driven content Caching Location and Searching scheme (P-CLS) in CCN. P-CLS leverages content access popularity to realize diverse content distribution and reduce content caching redundancy, which also overcomes the oscillation and frequent replacement phenomenon in the existing content caching and searching (CLS) scheme. Extensive simulations via hierarchical and arbitrary caching topologies show that the proposed scheme outperforms the existing caching algorithms.

Content-centric network (CCN) is a new Internet architecture in which content is treated as the primitive of communication. In CCN, routers are equipped with content stores at the content level, which act as caches for frequently requested content. Based on this design, the Internet is available to provide content distribution services without any application-layer support. In addition, as caches are integrated into routers, the overall performance of CCN will be deeply affected by the caching efficiency. In this paper, our aim is to gain some insights on how caches should be designed to maintain a high performance in a cost-efficient way. We try to model the two-layer cache hierarchy composed of CCN routers using a two-dimensional discrete-time Markov chain, and develop an efficient algorithm to calculate the hit ratios of these caches. Simulations validate the accuracy of our modeling method, and convey some meaningful information which can help us better understand the caching mechanism of CCN.

In this work, we study the caching performance of Content Centric Networking (CCN), with special emphasis on the size of individual CCN router caches. Specifically, we consider several graph-related centrality metrics (e.g., betweenness, closeness, stress, graph, eccentricity and degree centralities) to allocate content store space heterogeneously across the CCN network, and contrast the performance to that of an homogeneous allocation.

Content-Centric Networking (CCN) is a recently proposed Internet paradigm that focuses on scalable, secure and efficient content distribution. The main abstraction is named and addressable content. A consumer requests desired named content by generating a so-called interest, which is then routed by the network towards an in-network cached copy, or the authoritative producer, of that content. Since all CCN content must be signed by its producer, consumers and routers can cryptographically verify its correctness, authenticity, and integrity. Thus, in principle, attacks that introduce fake (poisoned) content can be detected. However, verifying content signatures is optional for CCN routers, detection of fake content only implies presence of a malicious upstream entity. A major outstanding problem in CCN is how to react to such attacks, determine their source(s), and re-route interests accordingly.,,,,In this work, we construct a technique based on efficient per-hop packet integrity checks. Routers share secrets with neighboring routers and use them to verify and generate efficient per-hop packet authenticators. An on-path attacker that tampers with content in transit is quickly detected by downstream routers. Moreover, an on-path attacker that hijacks a namespace is discoverable. Our experimental assessment indicates that the proposed technique incurs very low per-packet overhead. Furthermore, since our approach is not CCN-specific, it can be applied to IP-based networks as well.