REF: A Novel Forwarding Strategy in Wireless NDN

Software Defined Networking (SDN) is the more reliable and flexible networking architecture. Due to its programmable nature, it is getting more popular in every research domain of Computing. Moreover, Named Data Networking (NDN) architecture is also more beneficial and emerging technology of Internet. NDN focuses on the content name instead of its location and replaces the usage of IP addresses. Lot of research has been made to integrate SDN and NDN due to their benefits of better management-ability, flexibility, less complexity, centralized control, decoupled control and data planes etc. Mobile Ad Hoc Network (MANET) is also getting more popular due to huge advancement in Mobile communication devices. Combining SDN and NDN in MANET will resolve lots of problems (i.e. forwarding, mobility, management etc.) which are difficult to tackle with single architecture. Broadcast Storm is always a challenging issue in Ad Hoc networks like MANET. In this paper, we proposed a Controller based Selective Forwarding (CSF) scheme by merging SDN, NDN and MANET to overcome the Broadcast Storm Problem (BSP) and other issues caused by BSP. CSF is evaluated using different simulation parameters which shows superiority over the Native ND-MANET in reference to BSP.

Named Data Network (NDN) is a next-generation network architecture that shifts the traditional data communications paradigm Unlike conventional networks that rely on IP addresses, NDN delivers content based on data names rather than specific locations. In NDN, consumers express their requests by sending interest packets containing content names. These names are then propagated through the network nodes, which forward them to the appropriate destinations. The forwarding strategy in an NDN network plays a crucial role in ensuring efficient data delivery. This strategy includes a set of rules that determine the next hop for each interest packet. These rules are designed to optimize the forwarding process, minimizing delays and improving network efficiency. However, if the forwarding strategy is implemented without accurately identifying the appropriate face (i.e., the network interface) to forward interests toward the producer or the nearest cache node, it can lead to significant delays and packet drops. This, in turn, negatively impacts Quality of Service (QoS) parameters and the overall performance of the NDN network. This study applies supervised learning to classify consumer-requested interests to overcome this issue. This technique leverages several related variables to accurately classify these interests. The outcomes of the conducted research demonstrated that raw data from the mini-NDN output can be processed and transformed into a usable dataset. This data is then utilized to train a classification model with supervised learning. In a scenario with 9 NDN nodes and varying numbers of interests, distributed both uniformly and according to Zipf's law, the Random Forest model performs effectively, achieving an accuracy rate of 86.2% with an error rate of 14.8%.

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.

At this time forwarding strategy became the center of attention of researchers in area named data networking (NDN). This is because the forwarding strategy is responsible for managing every packet of interest received by the NDN router, then the characteristics of forwarding strategies will have a significant impact on NDN performance. Therefore this study aims to perform analysis using a large approach in forwarding strategy that is broadcast approach. It is expected that the results of this study can be utilized by researchers in the field of NDN to determine the direction of research. Parameter of study in this research is delay in observation time interval. A forwarding strategy using a broadcast approach is simulated in order to understand the NDN delay characteristics within the observation interval. The simulation of the research was conducted on the NDNSim simulator with several scenarios. From the simulation results obtained that cumulatively delay broadcast forwarding strategy in multi producer scenario there is no difference between fulldelay and lastdelay. However, in the single producer scenario there is a difference between fulldelay and lastdelay this can be influenced by the large number of consumers who send interest to the producer and also based on the flooding method of the interest package in order to find the nearest NDN router containing the expected content as soon as possible, So that it can overload the network performance and effects overhead.

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.

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.

Content-Centric Networking (CCN) is a communication paradigm that emphasizes content distribution. Named-Data Networking (NDN) is an instantiation of CCN, a candidate Future Internet Architecture. NDN supports human-readable content naming and router-based content caching which lends itself to efficient, secure, and scalable content distribution. Because of NDN's fundamental requirement that each content object must be signed by its producer, fragmentation has been considered incompatible with NDN since it precludes authentication of individual content fragments by routers. The alternative is to perform hop-by-hop reassembly, which incurs prohibitive delays. In this paper, we show that secure and efficient content fragmentation is both possible and even advantageous in NDN and similar content-centric network architectures that involve signed content. We design a concrete technique that facilitates efficient and secure content fragmentation in NDN, discuss its security guarantees and assess performance. We also describe a prototype implementation and compare performance of cut-through with hop-by-hop fragmentation and reassembly.

Named Data Network (NDN) is the future internet network that data-centric and adaptive to consumer requirement. Routing and forwarding systems on the NDN networks are different from IP networks due to the use of cache at each node on the network. The implementation of the Loop Free Inport-Dependent (LFID) routing protocol on NDN networks aims to eliminate loops on the network by eliminating the preferred routes or inefficient next hops. Forwarding strategies that can be implemented are Best Route, Access, Random, and Multicast. Therefore, machine learning technology is needed with various classification methods that can be implemented in machine learning so the output gives the recommendations that can be used to maximize the performance of the NDN network. The final result of this study recommends that the forwarding strategies of Best Route and Access provide good delay values, which in the range of 150 ms to 300 ms. Random forwarding strategy with a payload size> = 3072 kbps still provides a good delay value to the network, which in the 150 to 300 ms range. All forwarding strategies of Best Route, Access, Random, and Multicast provide delay values with a very good category of delay values, which is below 150 ms if the type of interest (data) that requested to the network is a popular interest. Keywords : Named Data Network , Routing, Forwarding, Machine Learning. DOI : http://doi.org/10.5281/zenodo.4320264

Among the distinctive features of the Named Data Networking (NDN) paradigm, in-network caching plays a crucial role in improving data delivery performance. At the network edge, the benefits of in-network caching can be remarkable in terms of reduced network traffic and user-perceived access latency. Multiple strategies have been designed for caching static Internet contents in NDN routers, while less attention has been devoted to transient Internet of Things (IoT) data, which expire after a certain amount of time. In this work, we introduce a novel distributed and autonomous caching strategy where NDN nodes take decisions by considering the popularity of IoT data and their lifetime. The target is to cache the most popular data with the highest residual lifetime in order to maximize the cache hit ratio at the edge. Performance evaluation assessed with the ndnSIM network simulator shows that the proposed solution outperforms existing schemes available in the literature by guaranteeing, among others, the highest cache hit ratio and the shortest content retrieval time.

Content Centric Networking (CCN) [1] is a new network paradigm designed to satisfy user needs considering the growth of data demand. Named Data Networking (NDN) [2] is a research project that is developing the future Internet architecture using the principles behind CCN. In this novel architecture, the contents are addressed by their name and not by their location. Thus, the attention is shifted from user to content, resulting in a caching network that is more efficient and flexible than an IP network for content distribution and management with beneficial effects on timely delivery. In NDN, the content objects are divided into chunks, each digitally signed by its producer, and most papers assume that verification is made only by the content consumer. In order to perform signature verification, a node needs the signer’s key, which can be easily retrieved by issuing a standard interest message. Although content verification at the end node prevents disruptive attacks in which false data is delivered to applications, the verification of key validity is also necessary. Otherwise, false data would be cached and forwarded instead of correct data resulting in a denial of service and paving the way for more sophisticated attacks.

Named data networking (NDN) has been considered as a promising networking architecture for vehicular ad-hoc networks (VANETs). However, interest forwarding in NDN suffers severe issues in vehicular environment. Broadcast storms result in much packet loss and huge transmission overhead. Also, link disconnection caused by highly dynamic topology leads to low packet delivery ratio and extreme long delay in data retrieval. Thus, an efficient NDN forwarding strategy to retrieve data is urgently required. In this paper, we propose the density-aware delay-tolerant (DADT) interest forwarding strategy to retrieve traffic data in vehicular NDN. DADT specifically addresses data retrieval during network disruptions using delay tolerant networking (DTN). It makes retransmission decisions based on directional network density. Also, DADT mitigates broadcast storms by using a rebroadcast deferring timer. We compared DADT against other strategies through simulation and the results show that it can achieve a higher satisfaction ratio while maintaining low transmission overhead.

Boosting named data networking for data dissemination in urban VANET scenarios

A Lightweight Forwarding Strategy for Named Data Networking in Low-end IoT

The growth of internet has shown the limitation TCP/IP architecture and has enforced the practitioners to invent a new architecture that are more capable to support large scale implementation of content based distribution. Today, Named Data Networking (NDN) has become a breakthrough alternative solution and a potential choice for next generation internet architecture. In this paper, we perform investigation to which extend existing forwarding strategies capable to support context information networking and increase service quality. We test this scenario to handle various types of user applications such as VoIP, multimedia streaming, and widely used application data delivery protocols, with specific requests (contexts), then find out which parts of the app prerequisites are consistent with the current strategy. We used NS3 with ndnSIM 2.0 to simulate and evaluate. This research mainly focused on the implementation of HTTP protocol alongside with the NDN. The experiment results show that Stochastic Adaptive Forwarding strategy provides excellent performance in different experiment scenarios.

Content-Centric Networking (CCN) focuses on content acquisition rather than end-to-end communication by decoupling content resources from special hosts. CCN does not need maintain stable paths between nodes and is independent of IP addresses, which make CCN convenient and efficient for mobile ad hoc network (MANET). In this paper, we develop an analytical model of content acquisition for Content-Centric MANET (CCM) in two-dimensional case, which considers in-network caching and nodes mobility. Closed-form expressions for round trip time and throughput are derived as functions of miss probabilities. From the expressions, we can obtain the relationship among the round trip time, cache size and content popularity. Simulations show that our model can be used as a guide to design CCM and to evaluate its performance.