Information-Centric Networking Research Articles

Adaptive distributed SDN controllers: Application to Content-Centric Delivery Networks

This paper aims to propose a deployment solution for Content-Centric Delivery Networks (C-CDN) based on the SDN technology in an IoT-like environment. To meet today’s network requirements in terms of reliability, scalability and performance and to match the specific IoT needs, the SDN architecture needs to be physically-distributed, but logically-centralized. The key idea is to consider the knowledge plane natively provided by the SDN controllers to build Information-Centric Networking (ICN) applications (e.g. Video distribution services). To achieve this, we put forward an adaptive and continuous consistency model for the distributed SDN controllers in large-scale deployments. More specifically, we propose to turn the standard replication technique into a scalable and intelligent replication strategy following Quorum-replicated consistency. That strategy uses the read and write Quorum parameters as adjustable control knobs for a fine-grained consistency level tuning. The main purpose is to find at run-time appropriate partial Quorum configurations that achieve, under changing network and workload conditions, balanced trade-offs between the SDN application’s continuous performance and consistency requirements. When compared to ONOS’s static consistency model, our approach which was implemented for a Content-Centric Delivery Network (C-CDN) application that we designed on top of ONOS, proved efficient in minimizing the application’s inter-controller overhead, while satisfying the SLA-style application requirements.

Efficient Coded-Block Delivery and Caching in Information-Centric Networking

Information-centric networking (ICN) provides request aggregation and caching strategies that can improve network performance by reducing content server loads and network traffic. Incorporating network coding into ICN can offer several benefits, but a consumer may receive the same coded block from multiple content routers since the coded block may be cached by any of the content routers on its forwarding path. In this paper, we introduce a request-specific coded-block scheme to avoid linear dependency of blocks that are utilizing in-network caching. Additionally, a non-cooperative coded caching and replacement strategy is designed to guarantee that the cached blocks can be reused. Our experimental results show that the proposed scheme has superior performance to conventional CCN and two network coding-based ICN schemes.

The Collective Advantage for Advancing Communications and Intelligence

The fifth-generation cellular networks (5G) have boosted the unprecedented convergence between the information world and physical world. On the other hand, empowered with the enormous amount of data and information, AI has been universally applied and pervasive AI is believed to be an integral part of 6G. Consequently, benefiting from the advancement in communication technology and AI, we boldly argue that the conditions for collective intelligence (CI) will be mature in the 6G era and CI will emerge among the widely connected beings and things. Afterward, we highlight the potential huge impact of CI on both communications and intelligence. In particular, we introduce a regular language (i.e., the information economy metalanguage) supporting the future collective communications to augment human intelligence and explain its potential applications in naming Internet information and pushing information centric networks forward. Meanwhile, we propose a stigmergy-based federated collective intelligence and demonstrate its achievement in a simulated scenario where the agents collectively work together to form a pattern through simple indirect communications. In a word, CI could advance both communications and intelligence.

MWBS: An Efficient Many-to-Many Wireless Big Data Delivery Scheme

Wireless big data raises the demands on the networking schemes to support the efficient group data sharing over heterogeneous wireless technologies, which take many-to-many data delivery as the foundation. Information-centric networking (ICN) approach is a promising networking technology to support big data delivery, which has the potential to establish the harmony between networking and wireless big data sharing. However, the existing ICN schemes have not carefully addressed the many-to-many communications. To address this issue, we propose an efficient and secure many-to-many wireless big data delivery scheme (MWBS) to provide group-based data dissemination and retrieval with name-integrated forwarding. In MWBS, a bi-directional tree is securely constructed for each group through the procedures of group initiation, join, leave, publication, and multi-level inter-zone routing. Especially, Designated Forwarding and Cacheable Nodes (DFCNs) are introduced to act as the roots for the construction of such bi-directional trees. The implementation details of MWBS are provided for function verifications. To effectively deploy MWBS, we investigate the impacts to the MWBS performance from the number and locations of DFCNs, which show that the optimized number of DFCNs can reduce the total traffic cost and the DFCN close to users is preferred to be selected for a group. Finally, simulations are performed to evaluate the performance of MWBS, which show that MWBS can reduce the control packet overhead and the state storage overhead compared to the existing ICN schemes.

Multi-attribute Probability Caching Algorithm in Named Data Network

Since entering the new century, Internet technology has developed rapidly and has become an important infrastructure in today’s society. In recent years, with the popularization of optical fiber applications, the network bandwidth has been greatly improved, and the growth rate of network traffic has also shown explosive growth. The traditional TCP/IP network has exposed many serious problems in the face of increasing traffic. In particular, the issues of scalability, reliability, security, flexibility and mobility are more prominent. In order to solve the shortcomings of the existing Internet architecture, the current domestic and international schemes mainly include "improvement" and "revolution". Improvement is the gradual improvement of the deficiencies of the existing Internet system. However, this method cannot essentially solve these deficiencies, and it is difficult to meet the needs of future network development. The revolution is to redesign the information-centric network as the Internet system structure, completely changing the existing Internet system in terms of scalability, security and mobility, in order to adapt to the needs of future social development. Named-Data Networking (NDN) in many information-centric network architectures is a network architecture with excellent research and development. This article focuses on the research of NDN network caching technology. In terms of caching decisions, a multi-attribute probabilistic caching algorithm is proposed, which can effectively reduce the cache of redundant data in routing nodes in NDN networks and improve the utilization of routing node cache space, reduce network delay, increase the cache hit rate of routing nodes, and improve the overall performance of the NDN network.

Performance Requirements Evaluation of Network functions in Information-Centric Networking based Wireless Sensor Network

Performance Requirements Evaluation of Network functions in Information-Centric Networking based Wireless Sensor Network

Nova Genesis - An Advanced Architecture for Internet of Things

The Internet has become the most important medium for information exchange and the core communication environment for business relations as well as for social inter- actions. The current internet architecture itself might become the limiting factor of Internet growth and deployment of new applications including 5G and future internet. Architectural limitations of internet include weak security, lack of efficient storage and caching, data distribution and traceability issues, lack of interoperability and so on. The proposed system overcomes these limitations by an alternate architecture for internet called NovaGenesis. This architecture integrates the concepts of Infor- mation Centric Networking (ICN), Service Oriented Architecture (SOA), network caching and name based routing. ICN evolve internet from a host-centric model to a content-centric model through efficient data exchange, storage and processing. SOA enables software-control/management of network devices based on service requirements. Network caching improves performance in terms of throughput, network traffic and retrieval delay. Name based routing is for discovering and delivering of data. The framework proposed increases the scalability and reliability of the delivery of IoT data for services.

Two Optimization Algorithms for Name-Resolution Server Placement in Information-Centric Networking

Information-centric networking (ICN) is an emerging network architecture that has the potential to address demands related to transmission latency and reliability in fifth-generation (5G) communication technology and the Internet of Things (IoT). As an essential component of ICN, name resolution provides the capability to translate identifiers into locators. Applications have different demands on name-resolution latency. To meet the demands, deploying name-resolution servers at the edge of the network by dividing it into multilayer overlay networks is effective. Moreover, optimization of the deployment of distributed name-resolution servers in such networks to minimize deployment costs is significant. In this paper, we first study the placement problem of the name-resolution server in ICN. Then, two algorithms called IIT-DOWN and IIT-UP are developed based on the heuristic ideas of inter-layer information transfer (IIT) and server reuse. They transfer server placement information and latency information between adjacent layers from different directions. Finally, experiments are conducted on both simulation networks and a real-world dataset. The experimental results reveal that the proposed algorithms outperform state-of-the-art algorithms such as the latency-aware hierarchical elastic area partitioning (LHP) algorithm in finding more cost-efficient solutions with a shorter execution time.

An Efficient Delay Tolerant Networks Routing Protocol for Information-Centric Networking

Delay tolerant networks (DTN) is a good candidate for delivering information-centric networking (ICN) messages in fragmented networks due to disaster. In order to efficiently deliver ICN messages in DTN, the characteristics of multiple requester nodes for the same content and multiple provider nodes for the same request should be used efficiently. In this paper, we propose an efficient DTN routing protocol for ICN. In the proposed protocol, requester information for request packet, which is called an Interest in ICN, is shared by exchanging status table with requested Data ID, requester ID, and satisfaction flag, where satisfaction flag is defined to show the delivery status of Data, so that unnecessary forwarding of Data is avoided. Data is forwarded to a more probable node by comparing average delivery predictability to a set of requesters. Performance of the proposed protocol was evaluated using simulation from the aspect of Data delivery probability and Data overhead, for varying buffer sizes, number of relay nodes, and time-to-live (TTL) of Data. The results show that the proposed protocol has better Data delivery probability, compared to content distribution and retrieval framework in disaster networks for public protection (CIDOR) and opportunistic forwarding (OF) protocols, although there is a tradeoff from the aspect of Data overhead for varying buffer sizes and number of relay nodes.

A Lightweight Caching Decision Strategy Based on Node Edge-Degree for Information Centric Networking

In-network caching as a core function in ICN can greatly improve the content distribution efficiency and reduce redundant network traffic. It is a challenge to design caching strategies in ICN to improve the performance of in-network caching. Traditional lightweight strategies are inefficient due to problems such as edge caching pollution and slow diffusion speed. Current caching strategy with popularity prediction does not fully consider the content capacity of ICN network. They usually have huge computation overhead and cannot meet line-speed requirement. This paper focuses on the research of lightweight on-path caching. Our caching strategy is proposed according to the edge-degree of routers along the forwarding path. This strategy can quickly form a hierarchical content placement with little overhead. A large number of experiments are conducted to examine the performance of our strategy in different topologies and workloads. The simulation result reveals that our caching strategy can reduce the average download latency by 10.2% and increase the cache hit ratio by 9.6% at most compared with other lightweight strategies.

FuRL: fuzzy RBM learning framework to detect and mitigate network anomalies in Information Centric Network

Information Centric Network (ICN) is a promising next-generation internet architecture in which the network focuses on retrieving the content by employing open in-network caching scheme to provide an efficient content distribution to users. However, such open in-network caching is vulnerable to network anomalies. In particular, cache pollution attack disrupts the smooth working of in-network caching by flooding unpopular contents. Hence, the in-network caching malfunctions and legitimate consumer requests are dropped. To address this problem, a secure framework based on Fuzzy Restricted Boltzmann Machine has been proposed to detect the anomalies and defend against such pollution attacks in ICN. Further, a reward-based cache replacement (ReBac) algorithm that is capable of avoiding cache pollution attack has also been proposed. The experimental results obtained while testing the proposed framework show better detection rate compared with the state-of-art solution and the proposed framework shows better cache rate.

An Effective Fairness Scheme for Named Data Networking

Named data networking (NDN) is a revolutionary approach to cater for modern and future Internet usage trends. The advancements in web services, social networks and cloud computing have shifted Internet utilization towards information delivery. Information-centric networking (ICN) enables content-awareness in the network layer and adopts name-based routing through the NDN architecture. Data delivery in NDN is receiver-driven pull-based and governed by requests (interests) sent out by the receiver. The ever-increasing share of high-volume media streams traversing the Internet due to the popularity and availability of video-streaming services can put a strain on network resources and lead to congestion. Since most congestion control techniques proposed for NDN are receiver-based and rely on the users to adjust their interest rates, a fairness scheme needs to be implemented at the intermediate network nodes to ensure that “rogue” users do not monopolize the available network resources. This paper proposes a fairness-based active queue management at network routers which performs per-flow interest rate shaping in order to ensure fair allocation of resources. Different congestion scenarios for both single path and multipath network topologies have been simulated to test the effectiveness of the proposed fairness scheme. Performance of the scheme is evaluated using Jain’s fairness index as a fairness metric.

IJNM Special Issue—International Journal of Network Management: QoE‐centric analysis and management of communication networks

IJNM Special Issue—International Journal of Network Management: QoE‐centric analysis and management of communication networks

ICN with edge for 5G: Exploiting in-network caching in ICN-based edge computing for 5G networks

In recent years, edge computing and Information Centric Networking (ICN) have been introduced as emerging technologies for distributing content closer to the end users. The former promises to increase the performance of several applications by using data locality and relieve the core network by addressing the increasing bandwidth demands caused by increased data volume. The latter makes the content directly addressable and routable in the network. Enabling ICN with edge computing in Radio Access Network (RAN) can improve the efficiency of content distribution and communication performance by reducing the distance between users and services. In line with this assertion, in this paper, we propose an ICN-capable RAN architecture for 5G edge computing environments that offers device to device communication and ICN application layer support at base stations. Moreover, ICN and edge caching is only useful for static content-requests for dynamic content have to traverse the core network increasing the latency in 5G networks. To address this issue, we provide a content prefetching strategy based on ICN naming. Experimental results show that our proposed scheme results in high cache hit ratios and lower delays compared to conventional edge systems and prior work on ICN for 5G.

Two-phase algorithm for solving the preference-based multicriteria optimal path problem with reference points

The shortest path problem arises in several contexts like transportation, telecommunication or data analysis. New requirements in solving practical problems (e.g., efficient content delivery for information-centric networks, urban passenger transport system or social network) impose that more than one criterion should be considered. Since the objectives are in conflict, the solution is not unique, rather a set of (efficient) paths is defined as optimal. The most satisfactory path should be selected considering additional preference information. Generally, computing the entire set of efficient solutions is time consuming. In this paper, we apply the reference point method for finding the best path. In a reference point-based approach, non-additive scalarizing function is applied. In this case, the classical optimality principle for the shortest path problem is not valid. To overcome this issue, we propose an equivalent formulation dealing with the constrained shortest path (CSP) problem. The idea is to define a set of constraints guaranteeing that an optimal solution to the problem at hand lies in the feasible region of the defined CSP problem. We propose a two-phase method where, in the first phase, a bound on the optimal solution is computed and used to define the constraints, whereas, in the second phase a labelling algorithm is applied to search for an optimal solution to the defined CSP problem. The method is tested on instances generated from random and grid networks, considering several scenarios. The computational results show that, on average, the proposed solution strategy is competitive with the state-of-the-art approaches and behaves the best on grid networks.

A Fog caching scheme enabled by ICN for IoT environments

The rapid growth in computation and processing power of end-user devices has transitioned network functionalities from the core network to the Fog, thus, reducing response times and ultimately improving user experience. The Information-Centric Networking paradigm aims to transform conventional content caching and delivery approaches by enabling Fog nodes to participate in both forwarding and caching. In this work, a Fog caching design scheme is presented for applications such as Internet-of-Things, which integrates three novel design attributes. Firstly, a Fog cluster-based scheme is proposed that utilises both in-network and end-user devices to cache content closer to the edge network, according to the increasing popularity of the content. Secondly, this work proposes a near-path approach that leverages caching nodes near the content delivery path. Finally, by craftily integrating reactive and proactive caching, congestion during network peak-time is averted. Simulations are conducted in the Icarus environment and evaluated against eight popular benchmark techniques. The results indicate significant improvement in internal link load and path stretch metrics. Finally, the cache hit ratio metric is consistently better than all other benchmarks, while the latency performance of the proposed scheme is competitive when the content distribution is more concentrated.

HAC: Enable High Efficient Access Control for Information-Centric Internet of Things

Information-centric networking (ICN) is regarded as a promising architecture for Internet of Things (ICN-IoT) and access control is one of the critical problems to enable secure ICN-IoT. This article proposes high efficient access control (HAC), a high efficient access control system for ICN-IoT. Specifically, HAC enables access control via an elaborate designed hierarchical key tree (HKT) mechanism based on the hierarchical naming scheme of ICN. The proposed HKT contains the hierarchical authority information and allow users to locally derive the key according to their needs, thus greatly decreasing the overhead in IoT’s many-to-many communication scenario. To ensure the security and efficiency of HKT, we further propose a level-oriented ciphertext policy attribute-based encryption (LOCP-ABE) algorithm such that users can only obtain the authority level according to their attributes, and also utilize the ICN’s receiver-driven model and the in-network caching mechanism to speed up the distribution efficiency. Moreover, an attribute-based command verification mechanism is used to improve the efficiency of command verification for resource-constrained and isolated IoT edge. We evaluate the proposed HAC by theoretical security analysis and real-world experiments. The theoretical analysis proves that the proposed HAC is secure and experiment results show that HAC can greatly improve the access control efficiency in ICN-IoT compared with the state of the art.

A multi-stage resource-constrained spectrum access mechanism for cognitive radio IoT networks: Time-spectrum block utilization

Extravagant demands for wireless communications have resulted in the shortage of spectrum, such that unlicensed spectrum bands are overcrowded, whereas licensed bands are not utilized efficiently. Moreover, content discovery and retrieval using the traditional host-centric approach of IP-based networks adds more burden on the wireless spectrum, such that, each time a request is initiated by the mobile service requester, a new routing path is discovered to retrieve the service from the service provider. Cognitive radio (CR) technology has been proposed to enable efficient and opportunistic spectrum band usage through the utilization of vacant licensed channels. This can offer huge spectrum to enable efficient large-scale deployment for IoT networks. Moreover, Information Centric Networking (ICN) has been proposed to decouple the service requester from the provider such that in-network content caching is used to allow for the retrieval of services within a mobile node’s proximity. The integration of CR and ICN will be essential for enabling envisioned IoT services within smart cities. In this article, we consider the multi-user single-transceiver coordinated spectrum access problem in CR-IoT networks under the overlay spectrum sharing model. We formulate the spectrum access problem as a multi-stage rate/channel assignment optimization problem. The objective is to maximize the overall network throughput by maximizing the achieved sum-rate over all contending CR-IoT devices. Specifically, we propose a novel resource-constrained channel assignment policy that provides a proper utilization of the available time–frequency units. The proposed policy also exploits the packet fragmentation capability to further enhance network throughput. Moreover, we envision a scenario where our proposed solution can be adapted to information-centric cognitive radio-based networking for IoT smart city applications. We showcase the significant improvement achieved by our proposed solution over state-of-the-art schemes through simulation results.

Game theory based cooperative caching strategy in information‐centric networking

Information‐centric networking (ICN) has received much attention from the governments and researcher in recent years thanks to its in‐network caching feature. In this paper, a cooperative ICN caching scheme based on game theory is proposed, where the ICN topology has been partitioned into some domains. For each piece of content in the individual domain, the caching value degree for the local domain as well as the neighboring domains is computed and it is regarded as the key factor of caching decision. In particular, the caching decision aims at minimizing the average delay of obtaining contents. The experimental results show that the novel cooperative caching scheme has higher cache hit rate and lower delay compared with two benchmarks.

Aggregate in my way: Privacy-preserving data aggregation without trusted authority in ICN

Information-Centric Networking (ICN) is a novel future network architecture which in contrast to IP-based networks relies on content and its name. It separates the physical location of data from the discovery and forwarding process and solely relies on the content itself. For the Internet of Thing (IoT) networks, stripping the location information may provide privacy, but this does not translate to operational privacy. Attackers can infer user behavior patterns through operational privacy, by eavesdropping on meaningful information. The content name and designed signature in ICN can associate content with the identity of the provider, even if the IP address is hidden. Although several research efforts focus on the privacy protection of ICN, they do not consider the privacy implications of data aggregation. Most existing privacy-preserving data aggregation protocols are designed for special operations, such as sum, average, variance, max or min, and they cannot support arbitrary aggregation operations in the ciphertexts domain. Besides, the need for trusted authority (TA) restricts the use of existing protocols in the real world. In this paper, we propose a practical and privacy-preserving data aggregation scheme that can compute arbitrary aggregation functions without a TA. On one hand, our scheme can ensure users’ anonymity and privacy protection, while on the other, the scheme is efficient in enabling participants to join or leave the system dynamically. Security analysis shows that the proposed scheme can achieve the desired security properties, while experimental results demonstrate its effectiveness and efficiency.