Content-Centric Networking Research Articles

Explicit traffic shaping scheme in content centric networking

Content centric networking (CCN) is considered as the prominent future internet architecture. CCN packets are routed based on content name itself, not on IP address and has two kinds of packets such as interest and data. CCN has a security model to secure content pieces, not to secure a transmission session. However, CCN has not widely taken the side effect to the occurrence of network congestion. So, this paper proposes the traffic control scheme in CCN environment to reduce high communication overhead, long content retrieval time, and high resource consumption. The proposed traffic shaping scheme for data packets tries to delay the transmission of data packets during network congestion.

An Adaptive Video Transmission Mechanism over MEC‐Based Content‐Centric Networks

The rapid growth of video traffic poses serious challenges to the current Internet. Content‐Centric Networking (CCN) as a promising candidate has been proposed to reengineer the Internet architecture. The in‐network caching and named content communication model of CCN can enhance the video streaming applications and reduce the network workload. Due to the bandwidth‐consuming characteristic of video streaming, the aggressive transmission of video data will cause a reduction of overall network efficiency. In this paper, we present an adaptive video transmission mechanism over Mobile Edge Computing‐ (MEC‐) based CCN. The computation and storage resources of the MEC server are utilized to facilitate the video delivery. Our mechanism adopts a scalable video coding scheme to adaptively control transmission rate to cope with the network condition variation. To analyse the equilibrium property of the proposed mechanism, an analytical model is deduced by using network utility function and convex programming. We also take into account the packet loss in wired and wireless links and present a MEC assistant loss recovery algorithm. The experiment results demonstrate the performance improvement of our proposed mechanism.

Position-related content acquisition for CCM

The Content-Centric Networking (CCN) depends on reverse paths and limited broadcast to achieve content acquisition, but the reverse-path disruption due to node mobility leads to content acquisition...

Heterogeneous CCN Cache Allocation Strategy With Collaboration Support

Content-Centric Networking (CCN) is regarded as a promising network architecture which has received the distinct interest from many global research communities thanks to its friendly structure, especially its caching technology has attracted the most widespread attention. However, the current caching strategies have some limitations, such as redundant content copies, low cache utilization rate and unbalanced node load. In order to further optimize cache, this paper investigates the classical cache allocation problem, i.e., distributing the cache capacity across some Content Routers (CRs) under a constrained and fixed total cache budget. At first, both topology information and traffic characteristics as two factors to determine the importance of CR, where the evaluation of network topology depends on degree centrality, betweenness centrality and closeness centrality while that of traffic characteristics depends on node load and interest preference. In particular, given the data redundancy due to the high-dimensional feature, increasing the complexity of computation, t-distributed Stochastic Neighbor Embedding (t-SNE) is used to reduce the dimensions of data. Then, for the CR with cache capacity, its Content Store (CS) is divided into collaborative region and non-collaborative region by a heuristic algorithm to facilitate the optimal performance, and the CS with collaboration needs to interact the cached information with its neighborhoods. Finally, the performance evaluation is driven by the real dataset over GTS-CE topology. The experimental results reveal that the proposed collaboration-supported cache allocation strategy is more efficient than two baselines, i.e., increasing cache hit ratio by 7.79%, increasing cache utilization rate by 11.31%, decreasing routing delay by 49.38% and decreasing load balance by 50.98%.

Position-related content acquisition for CCM

The Content-Centric Networking (CCN) depends on reverse paths and limited broadcast to achieve content acquisition, but the reverse-path disruption due to node mobility leads to content acquisition failures and flooding results in considerable content acquisition costs. In this paper, we propose a Unicast-based content acquisition scheme for Content-Centric MANET (UCCM) to reduce content acquisition costs and improve success rates. UCCM employs the address-centric unicast instead of the content-centric broadcast to achieve the content acquisition, so the content acquisition cost is lowered. Moreover, a requester acquires the content from the nearest provider in the address-centric unicast way, so the content is returned to a requester based on the requester's address rather than the reverse paths. UCCM is evaluated, and the analysis results show that UCCM reduces the content acquisition cost by nearly 63.8% and improve the success rate by nearly 5.9%.

Fast Content Delivery Using a Testbed-Based Information-Centric Network

Key requirements for a better performance of multimedia applications typically include lower latency, improved security, faster content retrieval, and adjustability to the traffic load. However, the current Internet often fails to meet the requirements due to the drawbacks of the host-oriented communication architecture. Those drawbacks can be overcome by a well-recognized networking paradigm, called Information-Centric Networking (ICN), that offers name-based and information-centric communication rather than host-oriented communication. This paradigm uses an in-network caching policy and may provide enhanced security along with user mobility. Therefore, the ICN architecture can outperform the current Internet in many aspects, including, but not limited to, content transfer time, traffic load control, mobility support, and efficient network management. Most of the existing research validating the ICN paradigm’s superior performance compared to the current Internet is based on simulation. In this paper, we propose a novel ICN-based testbed, where we used several modified functions for naming, routing, and caching and developed two new functions that provide mobility support and auto-playing of the retrieved content so that the performance of the ICN network is enhanced even more in terms of content delivery time or response time. The proposed testbed architecture is based on Content-Centric Networking (CCN), a prominent branch of the ICN concept. We present the testbed development procedures and the functions in detail and demonstrate that the testbed-based architecture outperforms the current Internet architecture and the basic CCN-based environment.

Node Value and Content Popularity‐Based Caching Strategy for Massive VANETs

The high‐speed dynamic environment and massive information transmitted via wireless communications in the vehicular ad hoc networks (VANETs) pose a great challenge to privacy and security. To overcome this issue, use of the content‐centric networking (CCN) provides a potential and practical solution. In‐network caching is a main feature for future smart cities, in which the content is mainly placed in network nodes. Therefore, how to effectively select the cache locality and cache content is essential to improve the overall network performance, which is an inevitable trend. With these observations, this article proposes a caching strategy based on the node value and content popularity (NVCP) for the massive VANET scenario. In the proposed NVCP scheme, different from the traditional caching strategies, we evaluate the node value from three aspects: the connectivity, intermediary, and eigenvector centralities, synthetically, since the content with different types of popularity is placed in nodes with different values, resulting in the redundancy deterioration and diversity improvement for the content. The proposed caching strategy is evaluated by the stochastic network topology with multifactors, which provides different impacts on the system performance. Simulation results show that the NVCP outperforms the traditional cache strategies for 6G‐CCN in terms of the cache hit ratio, average hop count, and transmission latency. Moreover, placing the content in the neighbor nodes is also introduced to further improve the utilization of the cache space and achieve better cache performance.

Scaling Performance Analysis and Optimization Based on the Node Spatial Distribution in Mobile Content‐Centric Networks

Content‐centric networks (CCNs) have become a promising technology for relieving the increasing wireless traffic demands. In this paper, we explore the scaling performance of mobile content‐centric networks based on the nonuniform spatial distribution of nodes, where each node moves around its own home point and requests the desired content according to a Zipf distribution. We assume each mobile node is equipped with a finite local cache, which is applied to cache contents following a static cache allocation scheme. According to the nonuniform spatial distribution of cache‐enabled nodes, we introduce two kinds of clustered models, i.e., the clustered grid model and the clustered random model. In each clustered model, we analyze throughput and delay performance when the number of nodes goes infinity by means of the proposed cell‐partition scheduling scheme and the distributed multihop routing scheme. We show that the node mobility degree and the clustering behavior play the fundamental roles in the aforementioned asymptotic performance. Finally, we study the optimal cache allocation problem in the two kinds of clustered models. Our findings provide a guidance for developing the optimal caching scheme. We further perform the numerical simulations to validate the theoretical scaling laws.

Sticky Policies: A Survey

In the digital age, where the Internet connects things across the globe and individuals are constantly online, data security and privacy are becoming key drivers (and barriers) of change for adoption of innovative solutions. Traditional approaches, whereby communication links are secured by means of encryption, and access control is run in a static way by a centralized authority, are showing their limits when applied to massive-scale, interconnected and distributed systems. Regulations, while still fragmented, are moving to adapt to changes in technology and society, with the aim to protect confidential information by governments, businesses, and individual citizens. In this landscape, proper mechanisms should be defined to allow a strict control over the data life-cycle and to guarantee the privacy and the application of specific regulations on personal information's disclosure, usage and access. Sticky policies represent one approach to improve owners' control over their data. In such an approach, machine-readable policies are attached to data. They are called 'sticky' in that they travel together with data, as data travels across multiple administrative domains. In this article we survey the state-of-the-art in sticky policies, discussing limitations, open issues, applications and research challenges, with a specific focus on their applicability to Internet of Things, cloud computing, and Content Centric Networking.

Convergence of ICN and MEC for 5G: Opportunities and Challenges

Information-centric networking (ICN) builds on a content-centric network architecture to overcome the shortcomings of host-centric routing/operation and realize efficient pervasive and ubiquitous networking. Similarly, multi-access edge computing (MEC) is another key technology to fulfill the stringent requirements of 5G to offer anytime-anywhere connected services for massive numbers of devices with ultra-low delay and very large bandwidths. The amalgamation of the ICN paradigm with MEC opens up new opportunities as well some challenges to realize 5G vision and advance beyond 5G systems. The key motivation of this article is to discuss and elaborate the convergence of ICN and MEC for better future networks, and to identify the current standardization efforts. Moreover, the article renders the key use cases and identifies potential research directions with the coexistence of ICN and MEC.

REF: A Novel Forwarding Strategy in Wireless NDN

Named Data Networking (NDN), an emerging communication model in the content centric networks, has recently presented a solid framework for the future Internet. The NDN exploits content name instead of host name (IP address) and content caching. These features make NDN particularly efficient in networks with intermittent connectivity and dynamic topologies such as mobile ad hoc networks (MANETs). Due to the structure of NDN nodes, design of forwarding strategies has a vital impact on the network performance. In this paper, we propose a new forwarding strategy: redundancy elimination forwarding (REF). In REF, the NDN node structure and the operation of the data structures are modified. These modifications improve network performance in terms of throughput, overhead and resource requirements. REF strategy is simulated in different scenarios based on ndnSIM and the results demonstrate that it provides robust performance for various environments.

Replacement based content popularity and cache gain for 6G Content-Centric network

In Content-Centric network (CCN), the capacity of router nodes caches the contents to satisfy the requests from subsequent consumers, and reduce the network overhead. Considering the limited cache capacity, the update of cached contents becomes a key element affecting the caching performance for the future 6G network. In this paper, a replacement strategy based content popularity and cache gain (PGR) is proposed for 6G-CCN. In the proposed scheme, the popularity of contents in the current cycle is determined according to the time interval and frequency of consumers’ requests. In addition, the distance between the router node and consumer affects the gain of caching. Further considering the dynamic popularity of content and gain of caching, a realistic content value function is provided. When the cache space reaches the upper bound, for the router node, the existing content with lower value will be replaced by newly arrived content with a higher value. Simulation results show that, compared with the conventional least frequently used (LFU) and least recently used (LRU), the proposed replacement strategy can effectively improve the space utilization and cache hit rate of router nodes, as well as reduce the average hops of consumers’ content acquisition for 6G-CCN.

A PERFORMANCE IMPROVEMENT SCHEME OF CONTENT CENTRIC NETWORKING OVER MULTI-SOURCE CONTENT DISTRIBUTION

Nowadays, Content Centric Networking (CCN) becomes one of the important technologies for enabling future network. In CCN, the contents are cached along the reverse path from the producer to the consumer, and they may be reused for many times without fetched from the original producer. In such kind of operation, the CCN improves network performance by reducing redundant transmissions of popular contents. However, the volume of the content store (CS) located in the gateway/router is constrained, and much smaller than the size of existing Internet contents which would go through the gateway/router, when rich media applications are considered. In order to solve this issue, this paper proposes a novel Multi-Source Content Centric Networking (MS-CCN) scheme by leveraging the concept of Multi-Source Mobile Streaming (MS2). In the MS-CCN model, the caching of each content is not limited in the single server anymore as in conventional CCN model, instead, each content is fragmented and distributed to multiple servers over a large scale network. After experiencing disjoint multi-paths, various content fragments are concatenated at client side. The OPNET Modeler simulation results show that the MS-CCN scheme significantly outperforms the original CCN scheme in terms of network utilization and user's Quality of Experiment (QoE).

Faster Data Forwarding in Content-Centric Network via Overlaid Packet Authentication Architecture

Content-Centric Networking (CCN) is one of the emerging paradigms for the future Internet, which shifts the communication paradigm from host-centric to data-centric. In CCN, contents are delivered by their unique names, and a public-key-based signature is built into data packets to verify the authenticity and integrity of the contents. To date, research has tried to accelerate the validation of the given data packets, but existing techniques were designed to improve the performance of content verification from the requester’s viewpoint. However, we need to efficiently verify the validity of data packets in each forwarding engine, since the transmission of invalid packets influences not only security but also performance, which can lead to a DDoS (Distributed Denial of Service) attack on CCN. For example, an adversary can inject a number of meaningless packets into CCN to consume the forwarding engines’ cache and network bandwidth. In this paper, a novel authentication architecture is introduced, which can support faster forwarding by accelerating the performance of data validation in forwarding engines. Since all forwarding engines verify data packets, our authentication architecture can eliminate invalid packets before they are injected into other CCN nodes. The architecture utilizes public-key based authentication algorithms to support public verifiability and non-repudiation, but a novel technique is proposed in this paper to reduce the overhead from using PKI for verifying public keys used by forwarding engines and end-users in the architecture. The main merit of this work is in improving the performance of data-forwarding in CCN regardless of the underlying public-key validation mechanism, such as PKI, by reducing the number of accesses to the mechanism. Differently from existing approaches that forgive some useful features of the Naive CCN for higher performance, the proposed technique is the only architecture which can support all useful features given by the Naive CCN.

Improving Network Throughput by Hardware Realization of a Dynamic Content Caching Scheme for Information-Centric Networking (ICN)

Caching popular content at storage enabled routers or small-cell base stations (SBSs) is a key technology for future communication systems. Primarily limited to wired backbone systems, content-caching techniques are useful to offload mobile data traffic too. Several protocols have been developed towards realization of content-caching, namely, information-centric networking (ICN), content-centric networking, and named data networking. Studies have revealed that incorporating ICN caching schemes at SBSs could significantly enhance the user level performance, i.e., the lesser download delay and the higher throughput. However, smaller coverage area of a SBS would make the communication prone to high handover probability. Therefore, the implementation of ICN caching schemes at SBS requires extremely low processing delay, i.e., delay to search if the requested content is available at the cache, and accordingly make decision to serve the content request or forward it to the content server. In this article, a configurable hardware add-on has been developed to incorporate content caching features in a traditional SBS that can serve the user with extremely low processing delay while optimizing a combination of various network and hardware metrics. Using extensive results being generated from simulations, the usefulness of content caching has been demonstrated, and the effect of several hardware parameters over the latency performance has been studied too. In addition, the caching hardware accelerator has the ability to adapt dynamically to the optimal caching policy required by the prevailing network conditions as well as hardware requirements. An improvement upto 53% in network delay and 15% in handover probability due to the support of hardware-based caching is observed that incurs a negligible $$0.07\,{\hbox {mm}}^2$$ and up to only 11.1 mW energy overhead while operating in the range of 690–910 MHz.

A Novel Weighted Clustering Algorithm Supported by a Distributed Architecture for D2D Enabled Content-Centric Networks.

Next generation cellular systems need efficient content-distribution schemes. Content-sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach for alleviating the burden on the cellular network. In this article, we utilize Content-Centric Networking and Network Virtualization to propose a distributed architecture, that supports efficient content delivery. We propose to use clustering at the user level for content-distribution. A weighted multifactor clustering algorithm is proposed for grouping the D2D User Equipment (DUEs) sharing a common interest. The proposed algorithm is evaluated in terms of energy efficiency, area spectral efficiency, and throughput. The effect of the number of clusters on these performance parameters is also discussed. The proposed algorithm has been further modified to allow for a tradeoff between fairness and other performance parameters. A comprehensive simulation study demonstrates that the proposed clustering algorithm is more flexible and outperforms several classical and state-of-the-art algorithms.

An efficient content placement scheme based on normalized node degree in content centric networking

Content-centric networking (CCN) becomes an imminent Internet architecture that emphasizes the data-centric approach for information retrieval instead of searching for the hosts in the network. CCN offers data (content) caching and its distribution capabilities to reduce average latency, the load of data servers, and improve network bandwidth utilization during content delivery. In this direction, the performance of node degree centrality and distance-based autonomous caching strategies have been investigated. Then, a novel content caching strategy called content placement based on normalized node degree and distance (CPNDD) is proposed. The CPNDD scheme considers content provider distance and node degree centrality parameters together to select the optimal cache locations for comprehensive utilization of the available caching capacities and a further reduction in average latency during content retrieval. The weights for these caching parameters have been determined via widespread simulations on the Abilene networks. The proposed caching scheme is implemented and tested in the simulated environment of ndnSIM and compared with peer competing schemes in CCN. The execution outcomes are examined for different caching capacities (50 and 100), Zipf popularity skewness factors (0.7 and 1.0) and request rates (50/s and 100/s). The simulation executions illustrate that CPNDD caching strategy escalates the cache hit probability and hop-reduction ratio up-to $$8\%$$ and $$9\%$$ as compared to existing schemes. Hence, the proposed content placement scheme improves the performance of CCN networks considerably and makes it suitable for the applications of Industry 4.0.

Content-Centric Framework over the Internet Environments

In recent years, content delivery accounts for a large proportion of the Internet traffic, but end-to-end communications used in the Internet mismatch content-centric delivery and lead to considerable delivery costs and latency. Taking the advantages of content-centric networking into account, we are motivated to employ the name-based mechanism to achieve content communications in the Internet and propose a content-centric framework in the Internet environment (CCFI). CCFI proposes a mapping mechanism between a unicast address and a name so that it can employ the name-based mechanism to achieve the following two objectives: (1) forward a content request to the nearest server in a unicast way; (2) support content sharing among multiple sources. Finally, CCFI is analyzed and evaluated, and the data show that it effectively reduce the content communication costs and latency.

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.

Fog-Assisted Content-Centric Healthcare IoT

Remote and automated healthcare monitoring systems aim to detect patient health emergencies and symptoms early enough in order to take timely and effective treatments. The technological advancements in the Internet of Things (IoT) have created opportunities for implementing such healthcare monitoring systems where rapid patient data retrieval is vital. However, due to limited computation and storage resources of IoT nodes, the prerequisite for rapid patient data retrieval is to resolve the resource restraint problem. Compared to IoT nodes, fog nodes in fog computing have powerful computing and abundant storage resources that can process, cache and provide data efficiently. Hence, we are motivated to exploit fog computing to overcome resource limitations of IoT nodes, and propose a fog-assisted healthcare IoT system. To achieve rapid patient data retrieval, this system exploits the in-network caching and request aggregation of the content-centric networking to shorten patient data retrieval latency. Finally, the proposed system is quantitatively evaluated. According to the experimental results, our system reduces the patient data retrieval latency by nearly 28.5 percent compared with the IoT-based healthcare system.