On Sharing an FIB Table in Named Data Networking

Mun, Ju Hyoung; Lim, Hyesook

doi:10.3390/app9153178

Cited by 9 publications

(3 citation statements)

References 26 publications

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“…The mechanism, auxiliary forwarding set (AFS), considers mobility factors to identify and select forwarding nodes. The authors of [105] proposed a new method using Bloom filters which combine routing of network connectivity with a building and forwarding engine. A fuzzy interest forwarding approach that exploits semantic similarities between the names carried in interest packets and the names of potentially matching data in CS and entries in FIB is proposed in [106].…”

Section: Intelligent Forwarding and Routing For Iiovmentioning

confidence: 99%

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

et al. 2022

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Recently the Internet of Vehicles (IoV) has become a promising research area in the field of the Internet of Things (IoT), which enables vehicles to communicate and exchange real-time information with each other, as well as with infrastructure, people, and other sensors and actuators through various communication interfaces. The realization of IoV networks faces various communication and networking challenges to meet stringent requirements of low latency, dynamic topology, high data-rate connectivity, resource allocation, multiple access, and QoS. Advances in information-centric networks (ICN), edge computing (EC), and artificial intelligence (AI) will transform and help to realize the Intelligent Internet of Vehicles (IIoV). Information-centric networks have emerged as a paradigm promising to cope with the limitations of the current host-based network architecture (TCP/IP-based networks) by providing mobility support, efficient content distribution, scalability and security based on content names, regardless of their location. Edge computing (EC), on the other hand, is a key paradigm to provide computation, storage and other cloud services in close proximity to where they are requested, thus enabling the support of real-time services. It is promising for computation-intensive applications, such as autonomous and cooperative driving, and to alleviate storage burdens (by caching). AI has recently emerged as a powerful tool to break through obstacles in various research areas including that of intelligent transport systems (ITS). ITS are smart enough to make decisions based on the status of a great variety of inputs. The convergence of ICN and EC with AI empowerment will bring new opportunities while also raising not-yet-explored obstacles to realize Intelligent IoV. In this paper, we discuss the applicability of AI techniques in solving challenging vehicular problems and enhancing the learning capacity of edge devices and ICN networks. A comprehensive review is provided of utilizing intelligence in EC and ICN to address current challenges in their application to IIoV. In particular, we focus on intelligent edge computing and networking, offloading, intelligent mobility-aware caching and forwarding and overall network performance. Furthermore, we discuss potential solutions to the presented issues. Finally, we highlight potential research directions which may illuminate efforts to develop new intelligent IoV applications.

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Section: Intelligent Forwarding and Routing For Iiovmentioning

confidence: 99%

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

et al. 2022

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“…Therefore, the NDN uses a receiver-driven and pull mechanism. Different from traditional IP networks, NDN nodes or routers support caching, and each node maintains three modules, which are content storage (CS), pending interest table (PIT), and forwarding information base (FIB) [15]. After receiving the Interest packet, the router first checks whether the corresponding content is cached in the CS, if there is, it will reply directly to the data packet, if not, it will find the PIT, if the PIT has a corresponding entry, it will only record the interface that received the Interest packet without forwarding it If not, forward it according to FIB and forwarding strategy, and add corresponding PIT entry, or discard Interest packet according to relevant information.…”

Section: Theoretical Supportmentioning

confidence: 99%

An Accelerating Approach for Blockchain Information Transmission Based on NDN

Yang

Lü²,

Gao

et al. 2021

Future Internet

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Blockchain is becoming more and more popular in various fields. Since the information transmission mode of the blockchain is data broadcasting, the traditional TCP/IP network cannot support the blockchain system well, but the Named-Data Networking (NDN) could be a good choice because of its multi-path forwarding and intra-network caching functions. In this article, we propose a new blockchain information transmission acceleration strategy (AITS) combining with graph theory and probability theory based on the NDN architecture. We select some more important nodes in the network as “secondary nodes”, and give them more bandwidth and cache space to assist the NDN network in data transmission. In order to select the correct node as the secondary node, we present a method to calculate the number of secondary nodes, and give the function to calculate the importance of each node. The simulation results show that in complex networks, the proposed method has superior performance in accelerating information transmission and reducing data overhead.

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“…The caching node stores a list of caching objects in its CS. In a radio access network (RAN), the caching node has a PIT that monitors and forwards the state of interest packets for the content object [40]. Similarly, the node enlists all the possible next-hops for forwarding interest packets to the provider in FIB [41].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Stretch Optimization in Information Centric Networking-Based Tactile Internet Applications

et al. 2021

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The fifth-generation (5G) mobile network services are currently being made available for different use case scenarios like enhanced mobile broadband, ultra-reliable and low latency communication, and massive machine-type communication. The ever-increasing data requests from the users have shifted the communication paradigm to be based on the type of the requested data content or the so-called information-centric networking (ICN). The ICN primarily aims to enhance the performance of the network infrastructure in terms of the stretch to opt for the best routing path. Reduction in stretch merely reduces the end-to-end (E2E) latency to ensure the requirements of the 5G-enabled tactile internet (TI) services. The foremost challenge tackled by the ICN-based system is to minimize the stretch while selecting an optimal routing path. Therefore, in this work, a reinforcement learning-based intelligent stretch optimization (ISO) strategy has been proposed to reduce stretch and obtain an optimal routing path in ICN-based systems for the realization of 5G-enabled TI services. A Q-learning algorithm is utilized to explore and exploit the different routing paths within the ICN infrastructure. The problem is designed as a Markov decision process and solved with the help of the Q-learning algorithm. The simulation results indicate that the proposed strategy finds the optimal routing path for the delay-sensitive haptic-driven services of 5G-enabled TI based upon their stretch profile over ICN, such as the augmented reality /virtual reality applications. Moreover, we compare and evaluate the simulation results of propsoed ISO strategy with random routing strategy and history aware routing protocol (HARP). The proposed ISO strategy reduces 33.33% and 33.69% delay as compared to random routing and HARP, respectively. Thus, the proposed strategy suggests an optimal routing path with lesser stretch to minimize the E2E latency.

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On Sharing an FIB Table in Named Data Networking

Cited by 9 publications

References 26 publications

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions

An Accelerating Approach for Blockchain Information Transmission Based on NDN

Intelligent Stretch Optimization in Information Centric Networking-Based Tactile Internet Applications

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