Investigating Route Cache in Named Data Networking

Named data networking (NDN) is a future Internet architecture that directly emphasizes accessible content by assigning each piece of content a unique name. Data transmission in NDN is realized via name-based routing and forwarding. Name-based forwarding information base (FIB) usually has much more and longer prefixes than IP-based ones, and therefore, name-based forwarding brings more challenges on the NDN router in terms of high forwarding throughput, low memory consumption, and fast FIB update. In this paper, we present an index data structure called BFAST for the name-based FIB. BFAST is designed based on a basic hash table, it employs a counting Bloom filter to balance the load among hash table slots, so that the number of items in each non-empty slot is close to 1, leading to low searching time in each slot. Meanwhile, the first-rank-indexed scheme is proposed to effectively reduce the massive memory consumption required by the pointers in all the hash table slots. Evaluation results show that, for the longest prefix match FIB lookup, BFAST achieves a speed of 2.14 MS/S using one thread, and meanwhile, the memory consumption is reasonably low. By leveraging the parallelism of today’s multi-core CPU, BFAST arrives at an FIB lookup speed of 33.64 MS/S using 24 threads, and the latency is around $0.71~\mu s$ .

Named Data Networking (NDN) is a future Internet architecture that replaces IP addresses with namespaces of contents that are searchable at the network layer. A challenging task for NDN routers is to manage forwarding-information bases (FIBs) that store next-hop routes to contents using their stored usually long names or name prefixes. In this paper, we propose FCTree, a compressed FIB data structure that significantly reduces the required storage space at the router and can efficiently meet the demands of having routes that are orders of magnitude larger than IP-based ones in conventional routing tables. FCTree employs a localized front-coding compression to buckets containing partitions of the routes. The top routes in these buckets are then organized in B-ary self-balancing trees. By adjusting the size of the buckets, the router can reach an optimal tradeoff between the latency of the longest prefix matching (LPM) operation and the FIB storage space. In addition, in contrast to existing hash and bloom-filter based solutions, the proposed FCTree structure can significantly reduce the latency required for range and wildcard searches (e.g., for latency sensitive streaming applications or network-layer search engines) where up to k routes are returned if they are prefixed by a requested name. Performance evaluation results demonstrate the significant space savings achieved by FCTree compared to traditional hash-based FIBs.

Named Data Networking (NDN) is a new network architecture derived from the success of the Internet. Specifically, NDN addresses and identifies data by naming. Source and destination host addresses are not required for data communication in the NDN because the data is uniquely named instead. In the NDN network, the Forwarding Information Base (FIB) table is responsible for data forwarding, the Pending Interest Table (PIT) is liable for holding the state of data forwarding process, and the Content Store (CS) is used to stock data chunks within the network to optimize the forwarding time to the data without contacting to the content producer. All these data structures consume the memory of devices existing in the Named Data Networking of Things (NDNoT). Accordingly, the size of the FIB, PIT and CS needs to be carefully adjusted in NDNoT environments for performance tuning and Quality of Service (QoS) provisioning. In this study, we explore the issues of FIB sizing on average and maximum occupancy, reliability and maximum delay for constant bit rate (CBR) traffic where each content producer is addressed with a prefix name in the Cooja simulator environment. The results indicate that FIB table size has an impact on the reliability and maximum delay. During the number of records in FIB outpaces the count of nodes in the network, the reliability decreases gradually. Therefore, in constrained NDNoT environment careful allocation of the memory among FIB, PIT and CS becomes an important issue. According to our knowledge so far, this work is the first study showing the effect of FIB table on the performance in an NDNoT environment.

Named data networking (NDN) supports receiver-driven content retrieval with stateful forwarding (pending interest table (PIT)/forwarding information base) and in-network caching, yet many deployments still rely on classical cryptography that may be undermined by quantum-capable adversaries. Despite NDN’s built-in data authenticity via producer signatures, quantum-enabled attacks become plausible once RSA/ECC-based trust anchors are weakened by Shor-type attacks. Existing quantum-security efforts for NDN largely focus on post-quantum replacements of signatures or key exchange, but do not address the tension between confidentiality-preserving payload protection and NDN’s in-network processing (forwarding/caching decisions) in a quantum setting. This paper presents a quantum-enhanced NDN architecture that preserves NDN’s content-centric semantics—naming, PIT-driven forwarding, and cache-assisted dissemination of verifiable control objects—while delivering privacy-sensitive payloads as quantum homomorphic encryption (QHE)-encrypted quantum states over an underlying quantum network. QHE provides end-to-end confidentiality and enables authorized operations on encrypted quantum payloads without exposing plaintext. To make the design compatible with NDN forwarding, the proposed protocol encrypts the payload while keeping name-based forwarding semantics intact, and supports ciphertext-domain processing for selected policy functions. To protect provenance and integrity of NDN metadata, routing instructions, and session state, we incorporate quantum digital signatures (QDS) bound to NDN names and session identifiers. The main contributions are: (i) a QHE+QDS layered protection model tailored to NDN’s Interest and Data exchange; (ii) a session workflow that couples proactive entanglement distribution with NDN-style stateful signaling for efficient establishment and recovery; and (iii) a security analysis clarifying the achieved guarantees and the remaining trust assumptions. Security analysis indicates robustness against quantum man-in-the-middle and tampering attacks, with modest overhead on NDN control traffic.

This paper proposes an IP forwarding information base (FIB) encoding leveraging an emerging data structure called a learned index , which uses machine learning to associate key-position pairs in a key-value store. A learned index for FIB lookups is expected to yield a more compact representation and faster lookups compared to existing FIBs based on tries or hash tables, at the cost of efficient FIB updates, which is difficult to support with a learned index. We optimize our implementation for lookup speed, exploiting that for efficient FIB lookups it is enough to approximate the key-position pairs with a piece-wise linear function, instead of having to learn the key-position pairs. The experiments using real BGP routing information snapshots suggest that the size of the proposed FIB is compact and lookup speed is sufficiently fast regardless of the length of matched prefixes.

This paper investigates the issue of multi-hop forwarding in Vehicular Ad hoc Networks (VANETs), which is suffering from rapidly changing topology, short-lived and intermittent connectivity. Designed to replace TCP/IP using named data, Named Data Networking (NDN) has natural advantages to greatly overcome those challenges because of its multi-source and in-network caching characteristics. However, in the wireless environment the Interest and Data, proposed in NDN, are usually flooded because of the absence of Forwarding Information Base (FIB). To tackle this problem, we propose HVNDN, a hybrid forwarding strategy through NDN. More specifically, HVNDN introduces opportunistic and probabilistic forwarding strategy for location-dependent and location-independent information, respectively, which takes full advantage of geographic information and the characteristics of named data in VANETs. To make Vehicle-to-Vehicle (V2V) communication more effective and reliable, we design elaborate Interest and Data packets formats, retransmission and acknowledgement mechanism in HVNDN. Simulation results from NS-3 demonstrate that the proposed forwarding strategy outperforms the state-of-art scheme with less end-to-end delay and overhead.

In Named Data Networking (NDN), there is a need for routing protocols to populate Forwarding Information Base (FIB) tables so that the Interest messages can be forwarded. To populate FIBs, clients and routers require some routing information. One method to obtain this information is that network nodes exchange routing information by each node advertising the available content objects. Bloom Filter-based Routing approaches like BFR [1], use Bloom Filters (BFs) to advertise all provided content objects, which consumes valuable bandwidth and storage resources. This strategy is inefficient as clients request only a small number of the provided content objects and they do not need the content advertisement information for all provided content objects. In this paper, we propose a novel routing algorithm for NDN called pull-based BFR in which servers only advertise the demanded file names. We compare the performance of pull-based BFR with original BFR and with a flooding-assisted routing protocol. Our experimental evaluations show that pull-based BFR outperforms original BFR in terms of communication overhead needed for content advertisements, average roundtrip delay, memory resources needed for storing content advertisements at clients and routers, and the impact of false positive reports on routing. The comparisons also show that pull-based BFR outperforms flooding-assisted routing in terms of average round-trip delay.

Blockchain can be used to ensure trust in a decentralized environment in which no trusted authority is available. Its original idea is to collect transactions in a block, and to chain the blocks together in such a way that attackers cannot forge the chain if the majority of the network is honest. Since its creation in 2008, blockchain technology has been used broadly in Internet to support decentralized payments, cloud computing, publishing, etc. This work focuses on public permissionless blockchain which neither guards against bad actors nor enforces access control. Named data networking (NDN) uses name-based routing and in-networking caching to support efficient content delivery, making it a promising future Internet architecture as well as a great network technology which can improve blockchain data delivery. Therefore, it is a very necessary task to enable deployment of blockchain applications over NDN. However, NDN is not immediately compatible with typical blockchain, since (permissionless) blockchain applications usually require broadcasting transactions and blocks in real time, which is not supported by the “pull” design of NDN. In this work, we propose BoNDN which enables blockchain applications over NDN. Unlike previous work, BoNDN follows the core design of NDN. We treat each type of blockchain data needed to be broadcast individually. Specifically, we rely on Interest broadcasting to support real-time broadcasting of blockchain transactions, which is small in size and can be brought by an Interest packet. In addition, we propose a subscription-push approach to support broadcasting of blockchain blocks, in which each miner performs subscription, and once a block is generated, the subscribed miner will receive the block.

Named data networking (NDN) has emerged as a future networking architecture having the potential to replace the Internet. In order to do so, the NDN needs to cope with inherent problems of the Internet, such as attacks that cause information leakage from an enterprise. Since NDN has not yet been deployed on a large scale, it is currently unknown how such attacks can occur, let alone what countermeasures can be taken against them. In this paper, we first show that information leakage in NDN can be caused by malware inside an enterprise, which uses steganography to produce malicious interest names encoding confidential information. We investigate such attacks by utilizing a content name dataset based on uniform resource locators (URLs) collected by a Web crawler. Our main contribution is a name filter based on anomaly detection that takes the dataset as input and classifies a name in the Interest as legitimate or not. Our evaluation shows that the malware can exploit the path part in the URL-based NDN name to create malicious names, thus, information leakage in the NDN cannot be prevented completely. However, we show for the first time that our filter can dramatically choke the leakage throughput causing the malware to be 137 times less efficient at leaking information. This finding opens up an interesting avenue of research that could result in a safer future networking architecture.

The Named Data Network (NDN) is a future network architecture to transit conventional host-centric networks into data-centric networks. A routing attack, represented by Interest Flooding Attack (IFA), is a major security concern in NDNs. IFAs seriously harm NDNs by sending excessive fallacious Interest packets to overwhelm the routers to serve legitimate users. It is easy to launch, but difficult to defend, especially when legitimate Interest packets are blended with the IFAs as bIFAs. In this paper, we propose an accurate approach to detect and mitigate IFAs and bIFAs, named Accurate Detection and Mitigation of Blended Interest Flooding Attacks (ADMBIFA). It utilizes fuzzy logic to detect IFAs and bIFAs. And then it identifies malicious Interest prefixes with K-means. Finally, it restrains attackers to mitigate the damage to the networks. The simulation results show that the ADMBIFA is very sensitive to detect attacks with an ability to mitigate IFAs and bIFAs. And it can effectively reduce the negative impacts on NDNs.

Named Data Networking (NDN) is an implementation of Information-Centric Networking (ICN) that has emerged as a promising candidate for the Future Internet Architecture (FIA). In contrast to traditional networking protocols, NDN’s focus is on content, rather than the source of the content. NDN enables name-based routing and location-independent data retrieval, which gives NDN the ability to support the highly dynamic nature of mobile networks. Among other important features, NDN integrates security mechanisms and prioritizes protecting content over communication channels through cryptographic signatures. However, the data verification process that NDN employs may cause significant delays, especially in mobile networks and vehicular networks. This aspect makes it unsuitable for time-critical and sensitive applications such as the sharing of safety messages. Therefore, in this work, we propose NDN-BDA, a blockchain-based decentralized mechanism that provides a faster and more efficient data authenticity mechanism for NDN-based vehicular networks.

Named data networking (NDN) is one representation and implementation of information-centric networking (ICN) and is considered to be among the most promising designs for the next generation of network architecture. The introduction of NDN into vehicular ad-hoc networks (VANETs) and utilization of its content-centric characteristic to improve data transmission and distribution in VANETs has become a research hotspot in recent years. However, research on mobility support of NDN-based VANETs still faces many challenges. To solve the issue of data transmission path breaking due to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Consumer</i> mobility in NDN-based VANETs, this article proposes a novel vehicle tracking-based <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packet forwarding scheme (VTDF) to improve the successful delivery rate of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packets in mobile environments. In this approach, the urban road structure is divided into complex multi-junction and straight lane scenarios and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Data</i> packets are forwarded according to vehicle movement information. Simulations indicated that this vehicle tracking scheme provides a lower average data transmission delay, shorter handover delay between roadside units, and higher data delivery rate for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Consumers</i> compared to the standard methods.

International audience

The Internet of Things (IoT) is a diverse technology that primarily utilizes TCP/IP protocols in IoT environments. However, it is often argued that the existing IP protocol stack is insufficient to support data sharing and storage capabilities for mobile IoT applications. Named Data Networking (NDN) has gained significant attention over time as a solution to the limitations of host-centric services in traditional IP networks. The key advantages of NDN include name-based routing and network caching, along with mobility support in wireless networks. The integration of NDN and IoT can address issues related to frequent node mobility, name-based routing, and storage constraints on resource-limited devices. IoT devices are frequently in mobility, creating routing challenges when transitioning from one domain to another. Interest packets remain unsatisfied until the producer reconnects to a new Point of Attachment (PoA) and updates its location. Despite these reconnections, challenges such as interest and data packet losses, increased latency, and suboptimal routing paths persist during communication. Consequently, managing producer mobility remains difficult during the frequent movement of nodes across different IoT domains. This paper proposes a novel Zone-Based Producer Mobility Management (ZBP-MM) protocol for NDN-based IoT environments. The proposed technique is evaluated and compared against the OPMSS scheme using the ndnSIM simulator. Results demonstrated that the proposed scheme achieves better hop count and cache hit ratio, with minimized interest satisfaction delay and handover delay, compared to the OPMSS technique during producer mobility scenarios in intra- and inter-zones.

Named Data Networking (NDN) as a promising future network architecture has been attracted a lot of attention. In NDN, to keep fairness between flows and avoid congestion, one of the most important issues is the traffic control. Although some works have been done to solve the traffic control problem by controlling the sending/forwarding of Interest, to the best of our knowledge, the cooperation between traffic control and forwarding strategy is largely ignored. Therefore, to fill this gap, we propose an effective traffic control mechanism named Multi-path Flow Control(MFC) in this paper. Our proposal is the first to combine traffic control with multi-path forwarding strategy. In contrast with other traffic control mechanisms, MFC performs better in supplying different flows with fair service rates, enhancing network throughput and avoiding “Waiting Interest”, which is a unique problem in NDN. Finally, numerical simulation results based on ndnSIM platform are illustrated to show the performance of the proposed scheme.