Content-Centric Networking Router Research Articles

Efficient Cache Consistency Management for Transient IoT Data in Content-Centric Networking

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 As a result, if without any effective countermeasures, outdated copies are inevitably stored by CCN routers and then distributed to the associated consumers, degrading both caching efficiency and user experience.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topologies, and corresponding results have proved the efficiency of the proposed scheme in timely evictions of outdated IoT data stored by CCN in-network caching.

Designing Cuckoo Based Pending Interest Table for CCN Networks

<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>

Bloom-Quotient Based Name Matching Technique in Content Centric Networks

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.

QoE-Aware Multi-Source Video Streaming in Content Centric Networks

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.

Intelligent data cache based on content popularity and user location for Content Centric Networks

Content cache as well as data cache is vital to Content Centric Network (CCN). A sophisticated cache scheme is necessary but unsatisfied currently. Existing content cache scheme wastes router’s cache capacity due to redundant replica data in CCN routers. The paper presents an intelligent data cache scheme, viz content popularity and user location (CPUL) scheme. It tackles the cache problem of CCN routers for pursuing better hit rate and storage utilization. The proposed CPUL scheme not only considers the location where user sends request but also classifies data into popular and normal content with correspond to different cache policies. Simulation results showed that the CPUL scheme yields the highest cache hit rate and the lowest total size of cache data with compared to the original cache scheme in CCN and the Most Popular Content (MPC) scheme. The CPUL scheme is superior to both compared schemes in terms of around 8% to 13% higher hit rate and around 4% to 16% lower cache size. In addition, the CPUL scheme achieves more than 20% and 10% higher cache utilization when the released cache size increases and the categories of requested data increases, respectively.

Inapproximability results and suboptimal algorithms for minimum delay cache placement in campus networks with content-centric network routers

We consider the cache placement problem in campus networks where routers have heterogeneous cache capacity and the objective is to minimize the total delay of all requests. We prove that the problem is NP-hard to approximate to within any factor less than $$n/m^{\epsilon }+\hbox{poly}(m)$$ , where n is the number of routers, m is the number of contents, $$\epsilon$$ is any fixed positive constant, and $$\hbox{poly}(m)$$ is any polynomial function of m. We propose (exponential-time) exact algorithms based on integer linear programming and propose techniques to decompose the network and remove redundant variables for speeding up the computation. By relaxing the integer linear programs, we also propose three (polynomial-time) heuristic algorithms. Numerical results show that the proposed algorithms give a shorter delay than existing cache decision algorithms for content-centric networks.

Optimal Content Caching in Content-Centric Networks

Content-Centric Networking (CCN) is a novel architecture that is shifting host-centric communication to a content-centric infrastructure. In recent years, in-network caching in CCNs has received significant attention from research community. To improve the cache hit ratio, most of the existing schemes store the content at maximum number of routers along the downloading path of content from source. While this helps in increased cache hits and reduction in delay and server load, the unnecessary caching significantly increases the network cost, bandwidth utilization, and storage consumption. To address the limitations in existing schemes, we propose an optimization based in-network caching policy, named as opt-Cache, which makes more efficient use of available cache resources, in order to reduce overall network utilization with reduced latency. Unlike existing schemes that mostly focus on a single factor to improve the cache performance, we intend to optimize the caching process by simultaneously considering various factors, e.g., content popularity, bandwidth, and latency, under a given set of constraints, e.g., available cache space, content availability, and careful eviction of existing contents in the cache. Our scheme determines optimized set of content to be cached at each node towards the edge based on content popularity and content distance from the content source. The contents that have less frequent requests have their popularity decreased with time. The optimal placement of contents across the CCN routers allows the overall reduction in bandwidth and latency. The proposed scheme is compared with the existing schemes and depicts better performance in terms of bandwidth consumption and latency while using less network resources.

Improving the transmission control efficiency in Content Centric Networks

The current Internet is facing a lot of challenges, including the transmission inefficiency due to the popularity of content-delivery applications. Content-Centric Networking (CCN) solves this problem by name-oriented routing and in-network caching. However, the existing transmission control approaches are not applicable in CCN.In this paper, we propose Flow-Aware Congestion Estimation (FACE) for congestion control in CCN. FACE predicts the future occupancy of the forwarding queue of the CCN router by historical flow information. Based on the current queue utilization, FACE estimates whether the congestion occurs more accurately. The Pending Interest Table (PIT), as a core component of the CCN router, is also crucial for the transmission control efficiency. Therefore, we then propose RTT-Aware PIT (RAPIT) for more precise transmission control. RAPIT measures the Round-Trip Time (RTT) between a CCN router and a content publisher, and sets PIT entry residence time dynamically based on the measured RTT. The evaluations show that FACE and RAPIT improve the PIT utilization and transmission control efficiency of CCN greatly.

On-line popularity monitoring method based on bloom filters and hash tables for differentiated traffic

Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking (CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters (SBF) and Counting Bloom filters (CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.

Hierarchical caches in content-centric networks: modeling and analysis

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.

콘텐트 중심 네트워크에서 정규표현식을 활용한 캐시친화적인 적응형 스트리밍 프레임워크

인터넷을 이용하는 사용자의 관점이 호스트 중심에서 콘텐트 중심으로 변화하면서 콘텐트 중심 네트워크 (Content Centric Network, 이하 CCN)라는 새로운 패러다임이 소개되었다. 한편, 최근 비디오 스트리밍에 대한 수요가 급증하고 있으며 더 높은 사용자의 만족도를 위한 적응형 스트리밍이 소개되면서 많은 연구가 진행 중에 있다. 따라서 CCN에서도 사용자의 수요에 따라 적응형 스트리밍을 고려할 필요성이 있다. 하지만 CCN에서 기존의 네트워크 구조에서와 동일한 방식으로 적응형 비디오 스트리밍 서비스를 할 경우 CCN 라우터 내 캐시를 (CS) 충분히 활용하지 못한다는 한계점이 있으며 또한 단말의 달라지는 요구 사항을 캐시 활용에 반영할 수 없는 문제점도 있다. 따라서 본 논문에서는 정규표현식을 활용한 콘텐트 네이밍 방식을 적용하여 기존 적응형 스트리밍 비트레이트 선택 알고리즘의 캐시활용도를 높이면서도 CCN의 기본 프로토콜에 적합한 프레임워크를 제시하고, 단말의 상태에 따라 동적인 표현식 기술 전략 및 선택 알고리즘을 통하여 비디오 스트리밍 품질을 개선하고자 한다. Content Centric Network (CCN) has been introduced as a new paradigm due to a shift of users's perspective of using Internet from host-centric to content-centric. On the other hand, a demand for video streaming has been increasing. Thus, Adaptive streaming has been introduced and researched for achieving higher user's satisfaction. If an architecture of Internet is replaced with CCN architecture, it is necessary to consider adaptive video streaming in CCN according to the demand of users. However, if the same rate decision algorithm used in Internet is deployed in CCN, there are a limitation of utilizing content store (CS) in CCN router and a problem of reflecting dynamic requirements. Therefore, this paper presents a framework adequate to CCN protocol and cache utilization, adapting content naming method of exploiting regular expression to the rate decision algorithm of the existing adaptive streaming. In addition, it also improves the quality of video streaming and verifies the performance through dynamic expression strategies and selection algorithm of the strategies.

A Traffic Aware Routing Protocol for Congestion Avoidance in Content-Centric Network

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 of resource 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.

A Traffic Aware Routing Protocol for Congestion Avoidance in Content-Centric Network

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 of resource 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.

Cache capacity-aware content centric networking under flash crowds

Content-centric networking (CCN) is a new networking paradigm to resolve the explosion of data traffic on the Internet caused by the rapid increase in file sharing and video streaming traffic. Networks with CCN avoid repeatedly delivering the same content of a link every time it is requested, as the content can be stored and transferred by CCN router caches. Two major features that are currently considered in CCN are in-network caching and content-aware routing. Even though both aspects are important, there is little comprehensive work on the interaction between them. In this paper, we propose a cache capacity-aware CCN that consists of selective caching and cache-aware routing methods that interact with each other to encompass cache management and cache-aware request forwarding. The main motivation of the proposed scheme is to utilize the network caches evenly and redirect a content request based on the previous forwarding of the desired contents (or chunks). To enable this function, we utilize a cache capacity metric based on recent cache memory consumption and reflect it to content replication according to the popularity information on the content server. We evaluate the proposed scheme with respect to existing cache replication algorithms and show that it leads to significant performance improvements and a better utilization of network caches.

Exploring hits-based content provisioning mechanism in Content-Centric Networking

In-network caching and Interest packets aggregation are two important features of Content-Centric Networking (CCN). CCN routers can directly respond to the Interest request by Content Store (CS) and aggregate the same Interest packets by Pending Interest Table (PIT). In this way, most popular content requests will not reach the origin content server. Thus, content providers will be unaware of the actual usages of their contents in network. This new network paradigm presents content providers with unprecedented challenge. It will bring a great impact on existing mature business model of content providers, such as advertising revenue model based on hits amount. To leverage the advantages of CCN and the realistic business needs of content providers, we explore the hits-based content provisioning mechanism in CCN. The proposed approaches can avoid the unprecedented impact on content providers' existing business model and promote content providers to embrace the real deployment of CCN network.

Approximate models for CCN data transfer in general topology

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.

Virtual Content-Centric Networking

Data-centric networking has recently been gaining attention. A representative design for data-centric networking is Content-Centric Networking (CCN), which routes packets based on content identifiers. CCN is basically designed to be open because ease of data reuse is one of the greatest advantages of data-centric networking. However, for real-world networking, completely open data-centric networking is not sufficient; it is necessary to allow for private communication within a group of users. In this paper, we propose Virtual Content-Centric Networking (VCCN), which realizes private communication within a group of users through CCN router virtualization. We present four building blocks of VCCN: extension of the content identifier, CCN router virtualization, packet transport between virtualized CCN routers, and Social Network Services cooperative user/group identification. We have implemented VCCN’s basic features by extending the CCNx software and have conducted a preliminary performance evaluation of our VCCN implementation.

Cache Performance Analysis of Virtualized Router on Virtual Content-Centric Networks

Content-centric networking (CCN) is one of the major proposals for realizing information-centric networking. CCN routers cache forwarded data in a buffer memory called the ContentStore (CS). Virtual content-centric networking (VCCN), which enables the construction of multiple virtual networks (called VCCN slices) on a content-centric network, has been recently proposed. When multiple VCCN slices are constructed, the performance of each VCCN slice and that of the entire network are strongly affected by the CCN routers' CS allocation to VCCN router instances in VCCN slices. In this paper, we analyze the effects of CS allocation methods and content request patterns in VCCN slices on the performance of each VCCN slice and that of the entire network. Through several numerical examples, we show that when content request patterns are heterogeneous, a hybrid resource allocation method is effective in terms of both network fairness for VCCN slices and overall network performance.

SVC-based Adaptive Video Streaming over Content-Centric Networking

In recent years, HTTP adaptive streaming (HAS) has attracted considerable attention as the state-of-the-art technology for video transport. HAS dynamically adjusts the quality of video streaming according to the network bandwidth and device capability of users. Content-Centric Networking (CCN) has also emerged as a future Internet architecture, which is a novel communication paradigm that integrates content delivery as a native network primitive. These trends have led to the new research issue of harmonizing HAS with the in-network caching provided by CCN routers. Previous research has shown that the performance of HAS can be improved by using the H.264/SVC(scalable video codec) in the in-network caching environments. However, the previous study did not address the misbehavior that causes video freeze when overestimating the available network bandwidth, which is attributable to the high cache hit rate. Thus, we propose a new SVC-based adaptation algorithm that utilizes a drop timer. Our approach aims to stop the downloading of additional enhancement layers that are not cached in the local CCN routers in a timely manner, thereby preventing excessive consumption of the video buffer. We implemented our algorithm in the SVC-HAS client and deployed a testbed that could run Smooth-Streaming, which is one of the most popular HAS solutions, over CCNx, which is the reference implementation of CCN. Our experimental results showed that the proposed scheme (SLA) could avoid video freeze in an effective manner, but without reducing the high hit rate on the CCN routers or affecting the high video quality on the SVC-HAS client.

Fast convergence caching replacement algorithm based on dynamic classification for content-centric networks

One of the key research fields of content-centric networking (CCN) is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used (LRU) and recent usage frequency (RUF) in cache hit rate and resiliency when content popularity in the network varies.