Information-Centric Networking Research Articles

Handling Producer and Consumer Mobility in IoT Publish–Subscribe Named Data Networks

In recent years, the Internet of Things (IoT) has become a standard facet of modern communications, and information-centric networks have been pointed as an alternative to bypass the restrictions imposed by the traditional Internet protocol networks regarding the mobility of its network elements. However, the improvements imposed by this new paradigm fall short in large scale mobile wireless distributed environments inherent to IoT, due to high node mobility, dynamic topologies and intermittent connectivity. To tackle these issues, we present a named data network (NDN)-based publish–subscribe mechanism with support for both Consumer and Producer mobility. This approach handles the Producer mobility by combining the Data packets with infrastructure specific information, fixing the broken paths between the Producer and the Consumer; and the Consumer mobility by monitoring and anticipating mobile node trajectories while compelling the infrastructure to adjust to new paths. Simulation results, assuming a smart city use case and using real traces of vehicular mobility, have shown that the proposed solution far surpasses the native NDN workflow and traditional publish–subscribe solutions. With respect to the Producer mobility, the proposed solution delivers 79% of Data packets against 14% with the Native implementation, when using 25 mobile Producers; regarding the Consumer mobility, results have shown that our solution achieves almost the same Consumer satisfaction ratio as previous implementations but reducing substantially the network overhead related with the transmission of Interest packets.

QoSA-ICN: An information-centric approach to QoS in vehicular environments

Heterogeneous content-based traffic distribution motivates Information-Centric Networking (ICN), where content delivery is of primary interest as a prominent solution. However, current work does not address Quality of Service (QoS) provisioning for prioritized traffic, which is required for different applications and content types. This paper extends ICN with data delivery deadline awareness and shapes the forwarding decisions to ensure prioritized packet treatment. The proposed QoS Aware-ICN (QoSA-ICN) classifies requests' priority with their QoS requirements by codifying a QoSInfo object in interest/data packets. QoSA-ICN also extends the existing NDN transmission mode to a converged best route with multi-hop multi-route forwarding, to avoid the overhead of pre-building routes in rapidly changing and dynamic environments. Furthermore, this work expands the network traffic control mechanism to optimally manage the potential impact of QoS on network congestion control. Extensive simulations results show a 3.5x and 1.2x improvement in data delivery time; and 13.5x and 4.6x reduction in packet loss when compared to DRSC-based native IP and NDN approaches, in networks of different sizes. Through simulations, we also found that QoSA-ICN reduces overall content retrieval time and packet loss while achieving a high ratio of successfully-received priority packets as compared to the existing techniques T-Move, MAP-Me and pNDN.

Pro NDN : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking

Named data networking (NDN), as a specific architecture design of information-centric networking (ICN), has quickly became a promising candidate for future Internet architecture, where communications are driven by data names instead of IP addresses. To realize the NDN communication paradigm in the future Internet, two important features, stateful forwarding and in-network caching, have been proposed to cope with drawbacks of host-based communication protocols. The stateful forwarding is designed to maintain the state of pending Interest packets to guide Data packets back to requesting consumers, while the in-network caching is used to reduce both network traffic and data access delay to improve the overall performance of data access. However, the conventional stateful forwarding approach is not adaptive and responsive to diverse network conditions because it fails to consider multiple network metrics to make Interest forwarding decision. In addition, the default in-network caching strategy relies on storing each received Data packet regardless of various caching constraints and criteria, which causes the routers in the vicinity of data producers to suffer from excessive caching overhead. In this paper, we propose the Pro NDN , a novel stateful forwarding and in-network caching strategy for NDN networks. The Pro NDN consists of multicriteria decision-making (MCDM) based interest forwarding and cooperative data caching. The basic idea of the MCDM-based interest forwarding is to employ Technique for Order Performance by Similarity to Idea Solution (TOPSIS) to dynamically evaluate outgoing interface alternatives based on multiple network metrics and objectively select an optimal outgoing interface to forward the Interest packet. In addition, the cooperative data caching consists of two schemes: CacheData, which caches the data, and CacheFace, which caches the outgoing interface. We conduct extensive simulation experiments for performance evaluation and comparison with prior schemes. The simulation results show that the Pro NDN can improve Interest satisfaction ratio and Interest satisfaction latency as well as reduce hop count and Content Store utilization ratio.

ICN‐driven group psychology visualization analysis mechanism using reinforcement learning

Reinforcement Learning (RL) has been widely considered as a robust method to complete the large‐scale data analysis with high computation efficiency, learning ability, and stability, and it has been applied into many fields, such as transaction detection, trajectory identification, behavior recognition and so on. With the rapid progress of human society, people's psychological pressure gradually becomes heavier and heavier. In order to avoid the social tragedy, it is certainly worth doing the group psychology analysis. Therefore, this paper uses RL to achieve the group psychology visualization analysis instead of the abstract data presentation. In other words, this paper also handles the analyzed data results on the group psychology behaviors by the visualization method. In addition, in order to accelerate the process of data visualization under the large‐scale environment, this paper also introduces the concept of Information‐Centric Networking (ICN) paradigm to support the name‐based community detection by separating IP addresses. The experiments include two parts. On one hand, RL‐based group psychology analysis method is evaluated. On the other hand, ICN‐based visualization method is evaluated. The results prove that the integrated group psychology visualization analysis mechanism is acceptable.

Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review.

In recent years, information-centric networks (ICNs) have gained attention from the research and industry communities as an efficient and reliable content distribution network paradigm, especially to address content-centric and bandwidth-needed applications together with the heterogeneous requirements of emergent networks, such as the Internet of Things (IoT), Vehicular Ad-hoc NETwork (VANET) and Mobile Edge Computing (MEC). In-network caching is an essential part of ICN architecture design, and the performance of the overall network relies on caching policy efficiency. Therefore, a large number of cache replacement strategies have been proposed to suit the needs of different networks. The literature extensively presents studies on the performance of the replacement schemes in different contexts. The evaluations may present different variations of context characteristics leading to different impacts on the performance of the policies or different results of most suitable policies. Conversely, there is a lack of research efforts to understand how the context characteristics influence policy performance. In this direction, we conducted an extensive study of the ICN literature through a Systematic Literature Review (SLR) process to map reported evidence of different aspects of context regarding the cache replacement schemes. Our main findings contribute to the understanding of what is a context from the perspective of cache replacement policies and the context characteristics that influence cache behavior. We also provide a helpful classification of policies based on context dimensions used to determine the relevance of contents. Further, we contribute with a set of cache-enabled networks and their respective context characteristics that enhance the cache eviction process.

Leveraging Software-Defined Networking Approach for Future Information-Centric Networking Enhancement

Information-centric networking (ICN) has been developed as a potential candidate for future networks. In this model, users are provided with content rather than communication channels between the different hosts. The ICN network has several problems such as scalability issues and bandwidth consumption. However, software-defined networking (SDN) has been proposed to improve the networking architectures. The goal of our paper is to propose a new approach to named-data networking (NDN) based on the paradigm of SDN. Our work introduces various research studies carried out in the SDN and ICN contexts. We first present the SDN architecture. Then, we focus on work that combines ICN and SDN architectures. Finally, we show the effects of using the SDN architecture on the named-data network (NDN). Our experimental results show that the use of the SDN architecture has a positive effect on NDN network performance.

Toward long-range adaptive communication via information centric networking

As Internet of Things (IoT) applications become more prevalent and grow in their use, a limited number ofwireless communication methods may be unable to enable dependable, robust delivery of information. It is necessary to enable adaptive communication and interoperability over a variety of wireless communication media to meet the requirements of large-scale IoT applications. This paper utilizes Named Data Networking (NDN), an up-and-coming Information-Centric Network architecture, to interconnect differing communication links via the network layer, and implements dynamic forwarding strategies and routing mechanisms which aid in the efficient dissemination of information. This work targets the creation of an interface technique to allow NDN to be transported via LoRa. This is acheived via the coupling of LoRa and WiFi using the NDN Forwarding Daemon (NFD) to create a universal ad hoc network. This network has the capacity for high range and multi-hop Device-to-Device (D2D) communication together with compatibility with other network communication media. Testing of the system in a real environment has shown that the newly created ad hoc network is capable of communicating over a several kilometer radius, while making use of the features provided by NDN to capitalize upon various links available to enable the efficient dissemination of data. Furthermore, the newly created network leverages NDN features to enable content-based routing within the LoRa network and utilize content-based routing techniques.

정보중심네트워크에서 생산자 이동성 조사 및 분석

정보 중심 네트워킹(ICN)과 그 결실인 명명된 데이터 네트워킹(NDN)은 호스트 중심 주소 기반 통신 아키텍처에서 컨텐츠 중심 이름 기반 통신 아키텍처로 패러다임의 전환을 제안하고 있다. NDN은 풀 기반 통신 모델을 따르고, 중간 노드의 포워딩 상태를 유지함으로써 소비자(최종 사용자) 모빌리티를 기본적으로 지원한다. 반면에 생산자(콘텐츠 생성자) 이동성은 NDN의 원래 아키텍처 설계에서 초기에 지원되지 않았었다. 따라서, 모바일 생산자 노드에서 발생하는 성능 저하 문제를 효율적으로 해결하기 위해, 최근 몇 년 동안 다수의 생산자 이동성 계획이 제안되어 왔다. 본 논문에서는 문헌에서 제안된 기존의 연구 노력(생산자 이동성의 맥락에서)에 대한 간략한 조사를 제공했다. 본 논문은 이동성 제도를 1) 유선 네트워크에서의 생산자 이동성과 2) 무선 네트워크에서의 생산자 이동성으로 분류하였다. 무선 네트워크에 대한 생산자 이동 체계는 VANETs(Vehicular AdHoc Networks)의 맥락에서 개략적으로 설명된다. 또한 NDN의 효율적인 생산자 이동성과 관련된 향후 연구 방향과 과제를 조명했다.

Secure crowd-sensing protocol for fog-based vehicular cloud

The new paradigm of fog computing was extended from conventional cloud computing to provide computing and storage capabilities at the edge of the network. Applied to vehicular networks, fog-enabled vehicular computing is expected to become a core feature that can accelerate a multitude of services including crowd-sensing. Accordingly, the security and privacy of vehicles joining the crowd-sensing system have become important issues for cyber defense and smart policing. In addition, to satisfy the demand of crowd-sensing data users, fine-grained access control is required. In this paper, we propose a secure and privacy-preserving crowd-sensing scheme for fog-enabled vehicular computing. The proposed architecture is made by a double layer of fog nodes that is used to generate crowd-sensing tasks for vehicles, then collect, aggregate and analyze the data based on user specifications. To ensure data confidentiality and fined-grained access control, we make use of ciphertext-policy attribute-based encryption with access update policy (CP-ABE-UP), which is a well-known one-to-many encryption technique. The policy update algorithm allows the fog nodes to outsource the crowd-sensing data to other fog nodes or to data users directly. We also adopted the ID-based signature tied to pseudonymous techniques to guarantee the authentication and privacy-preservation of the entities in the system. From the upper fog layer to the data user, we show that an information-centric networking (ICN) approach can be applied to maximize the network resources and enhance the security by avoiding unauthorized and unauthenticated data owners. The security analysis confirms that our approach is secure against known attacks, whereas the simulation results show its efficiency in terms of communication with little computational overhead.

An Enhanced Replica Selection Approach Based on Distance Constraint in ICN

Fifth generation (5G) networks have a high requirement for low latency of data delivery. Information-centric networking (ICN) adopts the paradigm of separation of the identifier and locator. It is efficient in content distribution by supporting in-network caching and has the potential to satisfy the low latency requirement in 5G. Replica selection is a key problem to retrieving content in ICN. Prior research usually utilizes the nearest replica. However, using the nearest replica cannot guarantee the smallest content download delay. To exploit in-network caching better, we propose an enhanced replica selection approach, called ERS. ERS first uses a distance-constrained-based name resolution system to discover the nearby replicas. Then, the most appropriate replica is chosen according to a local state table that maintains the state of replica nodes within a limited domain. In addition to network distance and replica node load, ERS innovatively introduces the path congestion degree between requester and replica nodes to assist replica selection. With extensive simulations, the proposed approach shows better performance than the state-of-the-art methods in terms of average content download delay. Finally, the overhead of the proposed method is analyzed.

Adaptive content seeding for information-centric networking under high topology dynamics

High-fidelity content distribution and other emerging applications of 5G and beyond-5G mobile broadband networking can put massive load on the core and radio access network (RAN). To address this, direct device-to-device (D2D) communication has recently become a first-class citizen of these networks. While information-centric vehicular networking (ICVN) based on fog computing can exploit such D2D links to alleviate the load on the RAN by proactively seeding content in the network, it has been shown that such seeding can cause even more load if performed where not needed. In addition, trying to determine where to seed content often causes additional load, negating the benefit of seeding. Therefore, in this work, we propose to adaptively seed fog nodes based on a purely virtual clustering approach. Here, vehicles are unaware of clustering decisions, so that an explicit exchange of control messages is no longer required. We show that the benefit of such an adaptive approach goes beyond simply being able to flexibly trade off one performance metric for another; in fact, it can consistently lower the load on the RAN link. We also demonstrate that this property holds even if the only available node location information is as coarsely grained as macroscale grid cells.

Information-Centric Wireless Sensor Networking Scheme With Water-Depth-Awareness Content Caching for Underwater IoT

The existing Underwater Internet of Things (UIoT) is based on the IP architecture, which is not conducive to the efficient storage and distribution of huge amounts of content generated in underwater. Actively pushing all content to users causes much unnecessary resource consumption in the UIoT. The information-centric networking (ICN) architecture opens new horizons up for these challenges. However, the slowness of underwater propagation speed makes traditional ICN not suitable for UIoT, especially considering about delay time. In this article, we propose an information-centric wireless sensor networking scheme with water-depth-aware content caching (ICWSN-WDA) to solve the above challenges. First, we design a naming scheme and a hybrid communication mode suitable for ICWSN-WDA. The communication mode in underwater we design is divided into push and pull traffic, which balances energy consumption and delay time. Second, we define a push level to decide which water depth the content actively pushes to, finding a suitable junction point of two modes. Third, as the water depth is deeper, it becomes more difficult to replace the sensor battery. To save energy consumption of deep-water sensors, the water-depth-aware caching mechanism is proposed based on water depth, popularity, and senor energy. Our extensive evaluation confirms the effectiveness of our proposed scheme, and it balances energy consumption constraints and latency.

What do information centric networks, trusted execution environments, and digital watermarking have to do with privacy, the data economy, and their future?

What if instead of having to implement controversial user tracking techniques, Internet advertising & marketing companies asked explicitly to be granted access to user data by name and category, such as Alice→Mobility→05-11-2020? The technology for implementing this already exists, and is none other than the Information Centric Networks (ICN), developed for over a decade in the framework of Next Generation Internet (NGI) initiatives. Beyond named access to personal data, ICN's in-network storage capability can be used as a substrate for retrieving aggregated, anonymized data, or even for executing complex analytics within the network, with no personal data leaking outside. In this opinion article we discuss how ICNs combined with trusted execution environments and digital watermarking, can be combined to build a personal data overlay inter-network in which users will be able to control who gets access to their personal data, know where each copy of said data is, negotiate payments in exchange for data, and even claim ownership, and establish accountability for data leakages due to malfunctions or malice. Of course, coming up with concrete designs about how to achieve all the above will require a huge effort from a dedicated community willing to change how personal data are handled on the Internet. Our hope is that this opinion article can plant some initial seeds towards this direction.

정보 중심 지연 허용 네트워크에서 우선순위 기반 메시지 전달 기법

정보 중심 지연 허용 네트워크는 노드 간 안정된 연결성이 보장되지 않는 네트워크 환경에서 지연 허용 네트워크 기술을 통해 이름 기반 정보 중심 네트워크 메시지를 효과적으로 전달하는 네트워크이다. 정보 중심지연 허용 네트워크에서는 노드 간 기회적 접촉을 통해 메시지를 전달하는데 짧은 접촉 시간 및 제한된 전송속도로 인해 버퍼에 저장된 메시지를 접촉 노드에게 충분히 전달하는데 한계가 있다. 이러한 문제를 해결하기 위해 본 논문에서는 접촉 시 전달 예측률, 인기도, 긴급성 우선순위의 가중합으로 정의된 전달 우선순위에 기반하여 메시지를 전달하는 우선순위 기반 메시지 전달 기법을 제안한다. 시뮬레이션을 통한 성능 분석 결과 제안 기법은 전달 우선순위를 사용하지 않고 메시지를 전달하는 기존 기법에 비해 부하율은 증가하지만 최대 19%의 향상된 가중 평균 전달률을 가지는 것을 알 수 있다.

Name Space Analysis: Verification of Named Data Network Data Planes

Named Data Networking (NDN) has many forwarding behaviors, strategies, and protocols to enable the benefits of Information-Centric Networking. This additional functionality introduces complexity, motivating the need for a tool to help reason about and verify that basic properties of an NDN data plane are guaranteed. This paper proposes Name Space Analysis (NSA), a network verification framework to model and analyze NDN data planes. NSA can take as input one or more snapshots, each representing a state of the data plane. It then provides the verification result against specified properties. NSA builds on the theory of Header Space Analysis, and extends it in a number of ways, e.g., supporting variable-sized headers with flexible formats, introduction of name space functions, allowing for name-based properties such as content reachability and name leakage-freedom, and multi-snapshot verification such as equivalence checks. These important additions reflect the behavior and requirements of NDN, requiring modeling and verification foundations fundamentally different from those of traditional host-centric networks. As a case study, we show how NSA can detect name space conflicts in NDN, which can be often hard to catch. Leveraging the learning from this study, we outline a conflict detection and resolution protocol and a name space registry to avoid such conflicts. We have implemented NSA and identified a number of optimizations to enhance the efficiency of verification. Results from our evaluations, using snapshots from various synthetic test cases and the real-world NDN testbed, show how NSA is effective, in finding errors, has good performance, and is scalable.

A softwarized and MEC-enabled protocol architecture supporting consumer mobility in Information-Centric Networks

Information-Centric Networking emerged as a powerful enabling technology for the provisioning of scalable and efficient real-time services in Future Internet, mobile architectures, and multi-hop wireless mesh networks. To serve mobile consumers, most of scientific contributions suggest to extend the information-centric communication primitives by means of a pull-based methodology, according to which the mobile consumer issues pending requests every time it reaches a new network attachment point. This approach, however, generates two important shortcomings. First, the requests delivered before the handover will generate stale paths with wrong forwarding information in their network routers. As a consequence, some new contents will be delivered also to previous locations, thus wasting bandwidth. Second, during handovers, mobile consumers may miss some contents released in real-time and lose the synchronization with the remote producer. In order to solve these issues, this work conceives a novel protocol architecture that successfully integrates and properly customizes the key functionalities of Information-Centric Networking, Multi-access Edge Computing, and Software Defined Networking paradigms. Specifically, the designed approach envisages that (1) Multi-access Edge Computing assists mobile consumers in retrieving data, while transparently managing the information-centric communication primitives and recovering the synchronization with the remote producer after the handover, (2) Software-Defined Controllers dynamically configure forwarding functionalities, and (3) Information-Centric Networking enables efficient data dissemination and delivers network control instructions. The impact of the devised protocol architecture on the communication overhead is analytically formulated and evaluated in scenarios with different topology, mobility, application settings, and number of mobile consumers. The comparison with respect to the pure Information-Centric Networking deployment demonstrates that the proposed solution ensures a reduction of the communication overhead up to 99.99% on the data plane, an overall bandwidth saving up to 99.93%, and a not negligible memory saving in intermediary routers. At the same time, the adoption of information-centric communication primitives for the control plane achieves an overhead reduction ranging from 29.36% to 51.13% with respect to an implementation based on the conventional OpenFlow protocol.

A Novel Hybrid Optimization for Cluster‐Based Routing Protocol in Information-Centric Wireless Sensor Networks for IoT Based Mobile Edge Computing

In present days, the utilization of mobile edge computing (MEC) and Internet of Things (IoT) in mobile networks offers a bottleneck in the evolving technological requirements. Wireless Sensors Network (WSN) become an important component of the IoT and is the major source of big data. In IoT enabled WSN, a massive amount of data collection generated from a resource-limited network is a tedious process, posing several challenging issues. Traditional networking protocols offer unfeasible mechanisms for large-scaled networks and might be applied to IoT platform without any modifications. Information-Centric Networking (ICN) is a revolutionary archetype which that can resolve those big data gathering challenges. Employing the ICN architecture for resource-limited WSN enabled IoT networks may additionally enhance the data access mechanism, reliability challenges in case of a mobility event, and maximum delay under multihop communication. In this view, this paper proposes an IoT enabled cluster based routing (CBR) protocol for information centric wireless sensor networks (ICWSN), named CBR-ICWSN. The proposed model undergoes a black widow optimization (BWO) based clustering technique to select the optimal set of cluster heads (CHs) effectively. Besides, the CBR-ICWSN technique involves an oppositional artificial bee colony (OABC) based routing process for optimal selection of paths. A series of simulations take place to verify the performance of the CBR-ICWSN technique and the results are examined under several aspects. The experimental outcome of the CBR-ICWSN technique has outperformed the compared methods interms of network lifetime and energy efficiency.

Towards reliable and efficient data retrieving in ICN-based satellite networks

Building a reliable and efficient network layer for large-volume content delivery over satellite is extremely challenging due to space circumstances of unreliable connectivity, long propagation delay and high dynamics. In this paper, we address those challenges in satellite networking and propose an information-centric data retrieval scheme to provide disruption-tolerant, low-delay and highly efficient content delivery. Our design, namely Coding-enabled Adaptive-Pull (CAP) scheme, is rooted in the concept of information-centric networking, transferring named contents rather than maintaining unreliable end-to-end connections in space. CAP retrieves data in one-to-many request-response model and adaptively adjusts the retrieval expectation according to network states. Meanwhile, the data retrieval scheme embeds with fountain-style erasure coding over its named packets for reliable transmission to reduce the needs of packet retransmission and utilizes in-network caching to tolerate possible link disruption. Evaluation results show that our scheme reduces delivery delay in most cases of unreliable links by nearly 82% and 75% compared with IP and NDN, respectively, and by 72% compared to delay-tolerant networking technique in a space-oriented scenario, with outstanding performance in tolerating delays and disruptions.

ICN-Based Enhanced Cooperative Caching for Multimedia Streaming in Resource Constrained Vehicular Environment

Today, with the worldwide offer and rapid increment in multimedia applications on the web, the demands of users to get them accessed are also increasing prominently. The users in vehicular environment too expect efficient multimedia streaming while travelling on the road. However, the high mobility of vehicles as well as the limited transmission range of infrastructure components in IP based network provides low performance by offering high delay and additional network overhead. To provide better Quality of Experience (QoE) with high performance, Information Centric Networking (ICN) is blended with vehicular environment. Caching the content inside network nodes is inherent feature of ICN with various associated benefits such as low content retrieval delay, less network traffic, path reduction and so on. However, challenges still exists for caching the content due to resource constrained network environment (such as limited cache capacity, node battery) as well as for secure delivery of cached data. To solve these challenges and to enhance network performance, we propose a cooperative caching scheme in hierarchical network architecture that jointly considers cache location as well as combined content popularity and predicted future rating score while making caching decision. The proposed approach uses two layer hierarchical architecture where nodes in edge layer are divided into clusters. The proposed scheme uses modified Weighted Clustering Algorithms (WCA) for selection of cluster heads which are then used to decide cache location. A probability matrix is used to compute content caching probability which considers both popularity and predicted future rating of content. The proposed approach dynamically predict the user's preferences using non-negative matrix factorization (NMF) - a machine learning technique which eventually provides prediction of future rating. Based on the selection of both cache location and content to cache, the proposed scheme can effectively cache the content in the network. Further, to deal with the secure delivery of cached content, this work supports legitimate user authorization at edge nodes. The performance of the proposed scheme is evaluated in MATLAB parallel computing toolkit. The results prove significant caching improvement in terms of cache hit, hop reduction and average delay using our proposed scheme.

Path Segmentation-Based Hybrid Caching in Information-Centric Networks

Information-centric networks (ICNs) have received wide interest from researchers, and in-network caching is an important characteristic of ICN. The management and placement of contents are essential due to cache nodes’ limited cache space and the huge Internet traffic. This paper focuses on coordinating two cache metrics, namely user access latency and network resource utilization, and proposes a hybrid caching scheme called the path segmentation-based hybrid caching scheme (PSBC). We temporarily divide each data transmit path into a user-edge area and non-edge area. The user-edge area adopts a heuristic caching scheme to reduce user access latency. In contrast, the non-edge area implements caching network content migration and optimization to improve network resource utilization. The simulation results show that the proposed method positively affects both the cache hit ratio and access latency.