A Cache Replacement Strategy Based on Hierarchical Popularity in NDN

NDN (Named Data Networking) as one approach of the Content-Centric Networking (CCN) architecture, proposed by Jacobson, 2006, conceptually, has some advantages compares to the current Internet technology which build based on host-to-host TCP/IP protocol stack. However, technically, we have to examine the NDN approach, beside to prove the concept, also to get as much as able the opportunities of improvement the concept before implementation stage. In this work, it has been compared two kinds of cache replacement policy. The policies that compared are the Least Recency Used (LRU) and Least Recency/Frequency Used (LRFU). In the first stage both of these policies implemented and then the performance comparison has been investigated. Based on the experiment, the LRFU policy outperform LRU policy with a limited cache size. As a consequence the LRFU has a time complexity higher than LRU. Finally, based on the simulation can be concluded that LRFU should be considered as cache replacement strategy on NDN instead of basic NDN cache policy, named as caching everything everywhere (CEE)

This article describes how the named data networking (NDN) has recently received a lot of attention as a potential information-centric networking (ICN) architecture for the future Internet. The NDN paradigm has a great potential to efficiently address and solve the current seminal IP-based IoT architecture issues and requirements. NDN can be used with different sets of caching algorithms and caching replacement policies. The authors investigate the most suitable combination of these two features to be implemented in an IoT environment. For this purpose, the authors first reviewed the current research and development progress in ICN, then they conduct a qualitative comparative study of the relevant ICN proposals and discuss the suitability of the NDN as a promising architecture for IoT. Finally, they evaluate the performance of NDN in an IoT environment with different caching algorithms and replacement policies. The obtained results show that the consumer-cache caching algorithm used with the Random Replacement (RR) policy significantly improve NDN content validity in an IoT 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.

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.

Internet of Things (IoT) and named data network (NDN) are innovative technologies to meet up the future Internet requirements. NDN is considered as an enabling approach to improving data dissemination in IoT scenarios. NDN delivers in-network caching, which is the most prominent feature to provide fast data dissemination as compared to Internet protocol (IP)-based communication. The proper integration of caching placement strategies and replacement policies is the most suitable approach to support IoT networks. It can improve multicast communication which minimizes the delay in responding to IoT-based environments. Besides, these approaches are playing a most significant role in increasing the overall performance of NDN-based IoT networks. To this end, in this article, the challenges of NDN-IoT caching are identified with the aim to develop a new hybrid strategy for efficient data delivery. The proposed strategy is comparatively and extensively studied with NDN-IoT caching strategies through an extensive simulation in terms of average latency, cache hit ratio, and average stretch ratio. From the simulation findings, it is observed that the proposed hybrid strategy outperformed to achieve a higher caching performance of NDN-based IoT scenarios.

Enhancing NDN feasibility via dedicated routing and caching

Named Data Networking is one of the most promising future Internet architectures with many advanced characteristics that are lacking in the existing TCP/IP-based Internet architecture. NDN features named content, built-in security, in-network caching, adaptive traffic routing, and multi-path forwarding. NDN can be used to mitigate traffic congestion and prioritize critical messages in both wired and wireless networks. It has particular advantages to deliver traffic over a disrupted and highly dynamic network environment because of its delay-tolerant and content-centric features. However, very few works have shown the real-world capacity of NDN over different types of network links. In this work, we benchmark the performance of NDN in various real network settings and make side-by-side comparisons with TCP/IP based approaches. We also demonstrate the strong capabilities of flexible forwarding strategies through prioritizing critical traffic over the network.

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.

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.

With information becoming a first-class citizen on the Internet, information-centric networking (ICN) is considered as a promising direction for the future Internet. Named data networking (NDN) is a prominent example of emerging ICN architectures. Unfortunately, NDN is vulnerable to various attacks targeting its in-network caching mechanism. In this paper, we focus on the false-locality pollution attack, in which an adversary repeatedly requests a number of unpopular data objects to waste the precious cache space on the NDN router and to reduce normal users’ hit ratios. With simulation experiments, we show that such an attack can cause considerable damage to the NDN network. To detect and mitigate such an attack, we introduce an algorithm that exploits the diversity of the Interest traversing paths within an Internet service provider’s point-of-presence network. We also propose inexpensive methodologies based on the probabilistic counting and Bloom filter techniques to implement the algorithm on an NDN router. The experimental results indicate that our proposed algorithm is effective in thwarting false-locality pollution. We also experiment with strategies that the adversary may utilize against our antipollution algorithm and demonstrate that such strategies are either ineffective or impractical in the real world.

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.

An efficient and social-aware distributed in-network caching scheme in named data networks using matching theory

As the Internet has become a more central aspect for information technology, so have concerns with supplying enough bandwidth and serving web requests to end users in an appropriate time frame. Web caching was introduced in the 1990s to help decrease network traffic, lessen user perceived lag, and reduce loads on origin servers by storing copies of web objects on servers closer to end users as opposed to forwarding all requests to the origin servers. Since web caches have limited space, web caches must effectively decide which objects are worth caching or replacing for other objects. This problem is known as cache replacement. We used neural networks to solve this problem and proposed the Neural Network Proxy Cache Replacement (NNPCR) method. The goal of this research is to implement NNPCR in a real environment like Squid proxy server. In order to do so, we propose an improved strategy of NNPCR referred to as NNPCR-2. We show how the improved model can be trained with up to twelve times more data and gain a 5–10% increase in Correct Classification Ratio (CCR) than NNPCR. We implemented NNPCR-2 in Squid proxy server and compared it with four other cache replacement strategies. In this paper, we use 84 times more data than NNPCR was tested against and present exhaustive test results for NNPCR-2 with different trace files and neural network structures. Our results demonstrate that NNPCR-2 made important, balanced decisions in relation to the hit rate and byte hit rate; the two performance metrics most commonly used to measure the performance of web proxy caches.

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

One challenge to the retrieval process of Named Data Network (NDN) is to take advantage of largely distributed copies in in-network caches. Potential based routing (PBR) uses a potential field defined in the network to facilitate routing data packet towards a desired location is an effective solution. But due to the characteristics of “Volatilize and Dynamic Update” on caches, there exist problems of high request failure rate and transmission delay in real applications. This paper proposes a novel distributed PBR scheme with prioritized connection probability of the nodes calculated by the popularity and similarity. It mapped the nodes into a hyperbolic plane according to the sequence of the caching time, and utilized radial coordinates and angular coordinates to represent the popularity and similarity, which will be used for the function of Fermi-Dirac distribution to calculate connection probability. The connection probability will be prioritized as the weight of the nodes for construction of potential fields. The simulation results show that our proposed scheme can not only significantly improves cache hit and utilization ratio, but also effectively controls network delay and overhead.