Benchmarking Network Performance in Named Data Networking (NDN)

Named Data Networking (NDN) proposes a contentcentric rather than a host-centric approach to data retrieval. Data packets with unique and immutable names are retrieved from a content store (CS) using Interest packets. The current NDN architecture relies on forwarding strategies that are dependent upon on-path caching and is therefore inefficient. This approach reduces data transfer efficiency by ignoring the cached content available on the adjacent off-path routers in the network. In this paper, we propose a novel distributed multipath (D-MP) forwarding strategy and enhancements to the NDN Interest forwarding pipeline. Furthermore, we develop a centralized SDNenabled control for the multipath forwarding strategy (S-MP) that distributes Interests efficiently by using the global knowledge of the NDN network states. We perform extensive evaluations of our proposed methods on an at-scale WAN testbed spanning six geographically separated sites. Our solutions outperform the existing NDN forwarding strategies by a significant margin. We show that the D-MP strategy results in performance gains ranging between 10.4x to 12.5x over the default NDN implementation without in-network caching, and gains of 12.2x to 18.4x with in-network caching. In addition, for the S-MP case, we demonstrate a performance improvement of 10.6x to 12.6x, and 12.9x to 18.5x, for with- and without in-network caching respectively.

An on-demand off-path cache exploration based multipath forwarding strategy

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.

In this paper we explore congestion control solutions in a network running the Named Data Networking (NDN) protocol. Since requested data can be retrieved from either original producers or in-network caches, the end-to-end connection oriented TCP congestion control solutions, such as BBR (Bottleneck Bandwidth and Round-trip propagation time) do not work well for NDN transport, especially in wireless networks. We propose a BBR-guided congestion control, BBR-CD, for bulk data fetching by a group of users. BBR-CD applies RTT filtering and interest scheduling to improve BBR's efficiency in NDN. Our evaluation shows that BBR-CD achieves much higher application goodput compared with ndncatchunks which implements the TCP AIMD and CUBIC congestion control algorithms. Moreover, compared with one-flow-per-file SIRC, an NDN congestion control algorithm that paces interests based on inter-data-gap, BBR-CD provides better fairness and bandwidth utilization. Finally, BBR-CD outperforms a direct adoption of the original BBR to NDN, suggesting that our changes to BBR are effective.

Named-Data Networking (NDN) is a novel clean-slate architecture for Future Internet. It has been designed to take into account a new use of the Internet and especially accessing content for a large number of users, and it integrates several features such as in-network caching, security or multipath. As NDN relies on content names instead of host address, it cannot rely on traditional Internet routing, and it is therefore essential to propose a routing scheme adapted for NDN. To this end, in this paper, we present SRSC, our SDN-based Routing Scheme for CCN/NDN and its implementation. SRSC relies on the SDN paradigm. A controller is responsible to forward decisions and to set up rules into NDN nodes. We implement SRSC into NDNx and we also deploy an NDN testbed within a virtual environment and real ISP topology in order to evaluate the performances of our proposal with real-world experiments. We demonstrate the feasibility of SRSC and its ability to forward Interest messages in a fully deployed NDN environment, while keeping low overhead and computation time and high caching performances.

In Named Data Networking (NDN), content can be retrieved from multiple sources through multiple path, which makes the traditional end-to-end congestion control mechanisms unsuitable for NDN. A lot of works have been done to achieve the congestion control by limiting the transmission rate of interest packets, but most of them overlooked the intelligent forwarding feature in NDN. In this paper, we propose a ratebased, multipath-aware congestion control algorithm MNRCP, which is inspired by Rate Control Protocol (RCP). MNRCP calculates the transmission rate for every flow and feedbacks it to the consumer to control the sending rate of interest packets. In order to fully exploit the features of multiple data sources, in-network caching and multipath forwarding and adapt to the practical scenarios that interest packets requesting the same data can arrive from different interfaces, we propose a novel multipath forwarding strategy and a multipath feedback mechanism to achieve fairness and network utilization. In addition, simulation results of our algorithm in ndnSIM2.3 show that compared with other congestion control mechanisms, MNRCP can achieve higher total throughput while ensuring fairness. According to the available bandwidth of the path, MNRCP also can achieve the optimal traffic split ratio, and thus performs better in load balancing.

In-network caching and multipath forwarding are prominent features of Named Data Networking (NDN). Network coding enabled NDN (NC-NDN) coordinates the in-network caching and multipath forwarding to improve content delivery performance. However, the existing NC-NDN lacks the considerations on the incorporation with caching schemes. It basically adopts the caching scheme of Caching Everything Everywhere (CEE) leading to cache redundancy and unnecessary and frequent cache replacement. On the other hand, the existing caching schemes for native NDN do not make use of the characteristic of network coded Data packets. To address these problems, this paper proposes a demand and responsiveness-based caching strategy specific to NC-NDN to enable cost-effective caching for network coded Data packets. In our proposed caching strategy, the caching decision at a caching node takes into account three factors, its present demand on the network coded Data packets of the requested generation of content, its distance to the original content provider, and its potential responsiveness to the future requests for the same generation based on the number of network coded Data packets locally cached and that would return for the requested generation. It commits to cache network coded Data packets of a generation of content at more valuable nodes along the transmission path. Our experimental studies show that the proposed caching strategy offers high-performance content delivery and reduces the caching overhead as compared to the existing strategies.

Named Data Networking (NDN) is a newly proposed next-generation Internet architecture that uses the name of data to forward and route packets. As a potential candidate for future Internet architecture, it is crucial to address the security and privacy issues in NDN. NDN is vulnerable to a new type of Distributed Denial of Service (DDoS) attacks called Interest Flooding Attacks (IFAs). The attackers can send a massive amount of Interest requests to overwhelm the Pending Interest Table (PIT) at routers resulting in network disruption for legitimate users. In this paper, we propose a Binary Tree-Based Interest Flooding Attack Detection and Mitigation Scheme (BTIFADMS) to protect NDNs. The proposed scheme allows each NDN router to use binary trees to detect IFAs and mitigates IFAs by limiting the number of Interest requests forwarded from the contaminated routers. The simulation evaluation shows that BTIFADMS can quickly and accurately identify and respond to the IFAs in the NDNs.

Two intrinsic features of Named Data Networking(NDN), in-network caching and multipath communication, offer the potential for fast and reliable big data transmissions via multisource content delivery. Network coding has recently been utilized to achieve efficient multisource content delivery in NDN. On the other hand, request pipelining is essential for efficient multisource content delivery in network coding enabled NDN. However, it is a challenge to simultaneously support network coding and request pipelining in NDN in a cost-effective way. To address this problem, we propose NCP-NDN, a network coding and request pipelining enabled named data networking architecture. NCP-NDN supports reasonably efficient Interest aggregation when enabling request pipelining without undermining the privacy of content retrieval by extending each Interest with a session and generation oriented requester identifier. Besides, NCP-NDN provides consumers with linearly independent blocks while request pipelining is enabled by combining rank-based matching, one forwarding of each block for per requester and face, and recoding the matching cached blocks before replying an Interest. Our experimental studies illustrate that NCP-NDN improves the performance of content delivery and reduces the overhead of big data transmissions as compared to the existing schemes.

The explosive growth of mobile data traffic demands scalable, resilient, and energy-efficient solutions for content dissemination, particularly at the network edge. In this context, 5G networks can rely on Outband Device-to-Device (O-D2D) communications, using technologies such as Wi-Fi Direct, to offload infrastructure, enhance coverage at the cell edge, and enable proximity-based services. However, O-D2D communications face critical challenges related to peer discovery, reliable data retrieval over lossy wireless links, and energy efficiency constraints. In this paper, we propose a novel framework that integrates Named Data Networking (NDN) and Chinese Remainder Theorem (CRT)-based fragmentation to support autonomous O-D2D content delivery. By leveraging name-based forwarding and in-network caching, NDN facilitates distributed content retrieval, making it inherently suited for dynamic and infrastructure-less D2D environments. CRT-based fragmentation, on the other hand, enhances reliability and energy efficiency by allowing data reconstruction from partial fragment sets, mitigating the effects of packet losses typical of wireless links. We implement the proposed architecture in ndnSIM v2.9, extending the NDN forwarding plane to support CRT-based multi-source data retrieval. Simulation results demonstrate that our solution significantly improves content delivery and energy efficiency compared to existing NDN retrieval schemes, particularly under lossy wireless conditions.

Named data networking (NDN) is a new Internet architecture that replaces today’s focus on where – addresses and hosts with what – the content that users and applications care about. One of NDN’s prominent advantages is scalable and efficient content distribution due to its native support of caching and multicast in the network. However, at the last hop to wireless users, often the WiFi link, current NDN implementation still treats the communication as multiple unicast sessions, which will cause duplicate packets and waste of bandwidth when multiple users request for the same popular content. WiFi’s built-in broadcast mechanism can alleviate this problem, but it suffers from packet loss since there is no MAC-layer acknowledgement as in unicast. In this paper, we develop a new NDN-based cross-layer approach called NLB for efficient and scalable live video streaming over wireless LAN. The core ideas are: using WiFi’s broadcast channel to deliver content from the access point to the users, a leader-based mechanism to suppress duplicate requests from users, and receiver-driven rate control and loss recovery. The design is implemented and evaluated in a physical testbed comprised of one software AP and 20 Raspberry Pi-based WiFi clients. While NDN with multiple unicast sessions or plain broadcast can support no more than ten concurrent viewers of a 1Mbps streaming video, NDN plus NLB supports all 20 viewers, and Received December 29, 2015; accepted April 28, 2016 E-mail: zhxp@tsinghua.edu.cn can likely support much more when present.

A blockchain-based architecture for secure vehicular Named Data Networks

Internet of Things (IoT) evolution calls for stringent communication demands, including low delay and reliability. At the same time, wireless mesh technology is used to extend the communication range of IoT deployments, in a multi-hop manner. However, Wireless Mesh Networks (WMNs) are facing link failures due to unstable topologies, resulting in unsatisfied IoT requirements. Named-Data Networking (NDN) can enhance WMNs to meet such IoT requirements, thanks to the content naming scheme and in-network caching, but necessitates adaptability to the challenging conditions of WMNs.In this work, we argue that Software-Defined Networking (SDN) is an ideal solution to fill this gap and introduce an integrated SDN-NDN deployment over WMNs involving: (i) global view of the network in real-time; (ii) centralized decision making; and (iii) dynamic NDN adaptation to network changes. The proposed system is deployed and evaluated over the wiLab.1 Fed4FIRE+ test-bed. The proof-of-concept results validate that the centralized control of SDN effectively supports the NDN operation in unstable topologies with frequent dynamic changes, such as the WMNs.

NDN (Named Data Networking, NDN) which is one of the next generation network architectures based on named-data, uses in-network caching. Cache has limited capacity, so the cache replacement policy determines which content is evicted when the cache space is full. This paper analyzes some cache replacement strategies in NDN, and puts forword a cache replacement strategy based on hierarchical popularity, then compares the effect of different cache replacement strategies to the cache performance through simulation experiments. Cache performance is evaluated in provision of cache hit ratio.

As a promising architectural design for future Internet, named data networking (NDN) relies on in-network caching to efficiently deliver name-based content. However, the in-network caching is vulnerable to cache pollution attacks (CPA), which can reduce cache hits by violating cache locality and significantly degrade the overall performance of NDN. To defend against CPA attacks, the most effective way is to first detect the attacks and then throttle them. Since the CPA attack itself has already imposed a huge burden on victims, to avoid exhausting the remaining resources on the victims for detection purpose, we expect a lightweight detection solution. We thus propose ELDA, an Efficient and Lightweight Detection scheme against cache pollution Attacks, in which we design a Lightweight Flajolet-Martin (LFM) sketch to monitor the interest traffic. Our analysis and simulations demonstrate that, by consuming a few computation and memory resources, ELDA can effectively and efficiently detect CPA attacks.