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This paper addresses the limitations of existing interest forwarding strategies in Named Data Networks (NDN) over Low-power and Lossy Networks (LLNs). While current strategies utilize listening periods to minimize duplicate retransmissions, they suffer from indiscriminately propagating interests across the network, resulting in excessive retransmissions. Conversely, strategies with propagation control often neglect challenges posed by producer mobility. In response, we propose an efficient forwarding strategy that not only mitigates duplicate retransmissions but also governs interest propagation through the integration of probabilities and estimated distances to data producers. Additionally, the strategy adeptly manages producer mobility through judicious flooding control. In contrast to prior studies primarily benchmarking against Blind Flooding (BF) and Deferred Blind Flooding (DBF), our work presents the first comprehensive evaluation of the new forwarding scheme against six established strategies. Through extensive simulations, we demonstrate the superiority of our proposed forwarding solution across key performance metrics, including sent packets, retrieval latency, success rate, and energy consumption in various scenarios. [ABSTRACT FROM AUTHOR]

This study's main goal is to provide a novel assault detection model with two phases. The features such node, distribution, pattern, frequency, and run time are extracted in the first phase. The Deep Convolutional Neural Network (CNN) is then used to detect cache pollution attacks (also known as content poisoning attacks), which include interest flooding for existing data, interest flooding for non-existing data, hijacking incoming interest packets, and signing data with the incorrect key. Similar to the first phase, the second phase involves extracting the aforementioned attributes and feeding them into a fuzzy decision tree (FDT) in order to identify an interest flooding attack. For accurate attack detection, this paper aims to optimise both DCNN and FDT classifiers. This work provided a fresh Decision Oriented Rider Optimisation Algorithm (DO-ROA), an enhancement of the traditional ROA, to address the optimisation problem. With regard to specific Type I and Type II performance measures, the suggested DO-ROA algorithm's performance is compared to that of other traditional models, demonstrating the superiority of the presented work. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth review of software-defined named data networking (SD-NDN), a transformative approach in network architectures poised to deliver substantial benefits. By addressing the limitations inherent in traditional host-centric network architectures, SD-NDN offers improvements in network performance, scalability, and efficiency. The paper commences with an overview of named data networking (NDN) and software-defined networking (SDN), the two fundamental building blocks of SD-NDN. It then explores the specifics of integrating NDN with SDN, illustrating examples of various SD-NDN models. These models are designed to leverage SDN for NDN routing, caching, and forwarding. The paper concludes by proposing potential strategies for further integration of SDN and NDN and some open research questions. These proposed strategies aim to stimulate further exploration and innovation in the field of SD-NDN. [ABSTRACT FROM AUTHOR]

Connected devices in IoT continuously generate monitoring and measurement data to be delivered to application servers or end-users. Transmitting IoT data through networks would lead to congestion and long delays. NDN is an emerging network paradigm based on name-identified data known to be an appropriate architecture for supporting IoT networks. In-network caching is one of the main advantages of NDN, a major issue discussed in many studies. One of the significant challenges for some IoT data is the transiency nature, making the data caching mechanism different. IoT data such as ambient monitoring in urban areas and tracking current traffic conditions are often transient, which means these data have a limited lifetime and then expire. In the proposed approach, data placement is decided upon based on the data lifetime and node position. Data lifetime is an essential property that must be involved in caching methods; consequently, the data are classified based on the data lifetime, and specific nodes are selected for caching according to defined classes and nodes' positions in topology. Based on the proposed scheme, the nodes with the highest outgoing interface count or the edge nodes are selected for data caching. By considering both data lifetime and node location, we determine the suitable caching location for each data class separately. In addition, we remove data that has a short lifetime and is not suitable for caching from the caching mechanism of NDN nodes. By considering both the cache and data placements for transient data, a more comprehensive view is grasped in improving the caching performance. This issue, which has not been addressed in the available studies run on IoT data caching, can lead to the appropriate use of available storage and reduce redundancy. Eventually, the simulation results performed by the ndnSIM simulator show the proposed method could improve the cache mechanism efficiency in terms of both delay and hit ratio. Comparison results of the proposed method with CE2 and Btw indicate that this method can provide a reduction in average delay and an increase in cache hit ratio. [ABSTRACT FROM AUTHOR]

In recent years, most internet communications have focused on accessing content such as video, web services, and audio. Conversely, traditional Internet communications are inefficient because they are primarily designed for data transfer between hosts. In response, Information-Centric Networking (ICN) has emerged as a content-oriented networking model. The impact of ICN in reducing the location dependency of data and its high compatibility with ad hoc networks has led to research on realizing Information-Centric ad hoc Networks (ICANET). There has also been extensive research into caching content in the network, which is one of the features of ICN. In static networks, methods have been proposed to cache highly popular content in nodes that are more likely to be used for shortest paths. However, in dynamic networks, content with high popularity should be cached on nodes that are more likely to reach all nodes, as missing nodes need to be taken into account. In this study, we propose a cache control scheme for content caching in ICANET that utilizes both content popularity and the closeness centrality of nodes within the ad hoc network as indicators. To realise the proposed method, a new packet flow based on the Pending Interest Table (PIT) and Content Store (CS) was implemented in the forwarding strategy of ICN. The experiments used ndnSIM, a protocol implementation of NDN based on Network Simulator3, which is widely used in wireless network research. The experimental results showed that the cache hit rate could be increased by up to 4.5% in situations with low content bias. In the same situation, the response delay was also reduced by up to 28.3%. [ABSTRACT FROM AUTHOR]

The performance of named data networking (NDN) depends on the caching efficiency of routers. Cache pollution attack (CPA) refers to colonization of unpopular contents in the content store (CS) of an NDN router, which leads to declined quality of service (QoS) in NDN. CPA has very few solutions proposed for its mitigation. Most of these solutions are based on the statistics of the router itself. However, an attacker can influence these statistics by requesting unpopular contents repeatedly. This article proposes a new parameter for the detection of CPA, which is based on the number of distinct users requesting interest packets for a content over a period of time. The local popularity of the attackers' content does not affect the proposed approach. The results show that the proposed approach consumes less storage, reduces processing time, and more effectively mitigates the CPA, as compared to the other existing approaches. Compared with the previous approaches, the proposed approach exhibits an improvement of approximately 28.14% to 36.80%. [ABSTRACT FROM AUTHOR]

Fog computing is today considered a promising candidate to improve the user experience in dynamic on-demand computing services. However, its ubiquitous application would require support for this service in wireless multi-hop mesh systems, where the use of conventional IP-based solutions is challenging. As a complementary solution, in this paper, we consider a Named-Data Networking (NDN) approach to enable fog computing services in autonomous dynamic mesh formations. In particular, we jointly implement two critical mechanisms required to extend the NDN-based fog computing architecture to wireless mesh systems. These are (i) dynamic face management systems and (ii) a learning-based route discovery strategy. The former makes it possible to solve NDN issues related to an inability to operate over a broadcast medium. Also, it improves the data-link layer reliability by enabling unicast communications between mesh nodes. The learning-based forwarding strategy, on the other hand, efficiently reduces the amount of overhead needed to find routes in the dynamically changing mesh networks. Our numerical results show that, for static wireless meshes, our proposal makes it possible to fully benefit from the computing resources sporadically available up to several hops away from the consumer. Additionally, we investigate the impacts of various traffic types and NDN caching capabilities, revealing that the latter result in much better system performance while the popularity of the compute service contributes to additional performance gains. [ABSTRACT FROM AUTHOR]

VNDN integrates the principles of Named Data Networking (NDN) into the VANET paradigm. NDN provides name-based and content-centric routing, which is better suited for vehicle mobility challenge compared to the traditional host-centric TCP/IP architecture. NDN names data instead of hosts and allows stateful forwarding based on content names, which eliminates the dependency on end-host locations and enhances reliability. This makes mobility management and content retrieval much simpler in VNDN compared to IP-based VANETs. High speed vehicle mobility in VNDN causes issues like network disconnections, and failed content delivery. Therefore, accurately tracking the real-time location of vehicles in VNDN is a crucial issue for seamless and reliable content retrieval during mobility. In this paper, we compare and analyze legacy vehicle tracking-based mobility management techniques in VNDN, in order to provide preliminary knowledge for future incoming researches on vehicle tracking-based mobility management in the VNDN environment [ABSTRACT FROM AUTHOR]

The IoT encompasses objects, sensors, and everyday items not typically considered computers. IoT devices are subject to severe energy, memory, and computation power constraints. Employing NDN for the IoT is a recent approach to accommodate these issues. To gain a deeper insight into how different network parameters affect energy consumption, analyzing a range of parameters using hyperparameter optimization seems reasonable. The experiments from this work's ndnSIM-based hyperparameter setup indicate that the data packet size has the most significant impact on energy consumption, followed by the caching scheme, caching strategy, and finally, the forwarding strategy. The energy footprint of these parameters is orders of magnitude apart. Surprisingly, the packet request sequence influences the caching parameters' energy footprint more than the graph size and topology. Regarding energy consumption, the results indicate that data compression may be more relevant than expected, and caching may be more significant than the forwarding strategy. The framework for ndnSIM developed in this work can be used to simulate NDN networks more efficiently. Furthermore, the work presents a valuable basis for further research on the effect of specific parameter combinations not examined before. [ABSTRACT FROM AUTHOR]

Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including 'request rates' and 'past popularity'. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as 'distance cost,' 'delivery time,' and the specific 'status of the requested content'. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth review of software-defined named data networking (SD-NDN), a transformative approach in network architectures poised to deliver substantial benefits. By addressing the limitations inherent in traditional host-centric network architectures, SD-NDN offers improvements in network performance, scalability, and efficiency. The paper commences with an overview of named data networking (NDN) and software-defined networking (SDN), the two fundamental building blocks of SD-NDN. It then explores the specifics of integrating NDN with SDN, illustrating examples of various SD-NDN models. These models are designed to leverage SDN for NDN routing, caching, and forwarding. The paper concludes by proposing potential strategies for further integration of SDN and NDN and some open research questions. These proposed strategies aim to stimulate further exploration and innovation in the field of SD-NDN.

Named Data Networking (NDN) has emerged as a promising network architecture for content delivery in edge infrastructures, primarily due to its name-based routing and integrated in-network caching. Despite these advantages, sub-optimal performance often results from the decentralized decision-making processes of caching devices. This article introduces a paradigm shift by implementing a Software Defined Networking (SDN) controller to optimize the placement of highly popular content in NDN nodes. The optimization process considers critical networking factors, including network congestion, security, topology modification, and flowrules alterations, which are essential for shaping content caching strategies. The article presents a novel content caching framework, Popularity-aware Caching in Popular Programmable NDN nodes (PaCPn). Employing a multi-variant vector autoregression (VAR) model driven by an SDN controller, PaCPn periodically updates content popularity based on time-series data, including ‘request rates’ and ‘past popularity’. It also introduces a controller-driven heuristic algorithm that evaluates the proximity of caching points to consumers, considering factors such as ‘distance cost,’ ‘delivery time,’ and the specific ‘status of the requested content’. PaCPn utilizes customized DATA named packets to ensure the source stores content with a valid residual freshness period while preventing intermediate nodes from caching it. The experimental results demonstrate significant improvements achieved by the proposed technique PaCPn compared to existing schemes. Specifically, the technique enhances cache hit rates by 20% across various metrics, including cache size, Zipf parameter, and exchanged traffic within edge infrastructure. Moreover, it reduces content retrieval delays by 28%, considering metrics such as cache capacity, the number of consumers, and network throughput. This research advances NDN content caching and offers potential optimizations for edge infrastructures.

AbstractInformation-Centric Networks (ICNs) have become a promising paradigm for the future Internet instead of host-based communication. In this network, content-oriented data and in-network caching are two key properties, which have brought tremendous benefits to many challenging networks by improving the distribution and retrieval of content. The content is cached along the reversed delivery path, on-path caching and off-path caching. Generally, the existing caching approaches in Information-Centric Networks mainly consider the key characteristics of the content (to decide which content is to be cached), the network (to determine the appropriate time for caching), the nodes (to determine where content should reside), etc. This paper presents a comprehensive survey of in-network caching of ICN schemes (also known as ICN-based caching) in many network applications. Thus, a detailed analysis of the existing caching approaches in several network applications, such as MANET, VANET, IoT, and WSN, is given. This survey also provides a taxonomy for caching policies according to some feature-based approaches and highlights the trends and evaluation problems in these areas. Finally, the challenging research directions in different applications are also pointed out in this subject.

The vehicular named data networking (VNDN) is gaining more attention as a future vehicular networking (VN) model. The VNDN's fundamental principles of data naming, data-centric forwarding, and in-network caching make it inherently capable of mitigating the challenges in traditional VN. However, broadcast communication for content discovery and delivery causes VNDN to face challenges such as overhead due to packets redundancy, collision, and retransmission. In this paper, we introduce an Interest-Data-flow tracking-based forwarding scheme (IDTracS) for VNDN. IDTracS aims to improve VNDN performance by prioritizing the potential best forwarders and addressing Interest and Data packet broadcast issues. IDTracS is a receiver- and time-contention-based forwarding scheme that controls both Interest and Data packets forwarding. IDTracS uses the node's degree of centrality to the Interest/Data flow and the node's geo-distance closeness from the last Interest/Data forwarder for the requested content name-prefix. Accordingly, it computes an Interest/Data forwarding delay timer for prioritizing Interest/Data among nodes. The simulation findings reveal that the proposed IDTracS achieves an enhanced Interest satisfaction ratio, delivery delay and network transmission overhead compared to related geo-position- and distance-based protocols. [ABSTRACT FROM AUTHOR]

The hypothalamus regulates fundamental aspects of physiological homeostasis and behavior, including stress response, reproduction, growth, sleep, and feeding, several of which are affected in patients with Prader–Willi (PWS) and Schaaf–Yang syndrome (SYS). PWS is caused by paternal deletion, maternal uniparental disomy, or imprinting defects that lead to loss of expression of a maternally imprinted region of chromosome 15 encompassing non-coding RNAs and five protein-coding genes; SYS patients have a mutation in one of them, MAGEL2. Throughout life, PWS and SYS patients suffer from musculoskeletal deficiencies, intellectual disabilities, and hormonal abnormalities, which lead to compulsive behaviors like hyperphagia and temper outbursts. Management of PWS and SYS is mostly symptomatic and cures for these debilitating disorders do not exist, highlighting a clear, unmet medical need. Research over several decades into the molecular and cellular roles of PWS genes has uncovered that several impinge on the neuroendocrine system. In this review, we will discuss the expression and molecular functions of PWS genes, connecting them with hormonal imbalances in patients and animal models. Besides the observed hormonal imbalances, we will describe the recent findings about how the loss of individual genes, particularly MAGEL2, affects the molecular mechanisms of hormone secretion. These results suggest that MAGEL2 evolved as a mammalian-specific regulator of hypothalamic neuroendocrine function. [ABSTRACT FROM AUTHOR]

The Named Data Network (NDN) enables efficient content dissemination through interest-based retrieval, name-based routing, and content caching. In the industrial Internet architecture based on NDN, device identity distribution, identification, resolution, and routing rely on identification resolution technology. However, this approach presents challenges such as cache poisoning, interest packet flood attacks, and black hole attacks. Existing security schemes primarily focused on routing forwarding and verification fail to address critical concerns, including routing environment credibility and data leakage, while exhibiting poor time and space efficiency. To address these challenges, this paper proposes a lightweight behavior auditing scheme using blockchain technology. The scheme utilizes an improved Bloom filter to compress behavioral information like interest and data packets during the identification transmission process. The compressed data are subsequently uploaded to a blockchain for auditing, achieving efficient space and time utilization while maintaining feasibility. [ABSTRACT FROM AUTHOR]

It has been forty years since the TCP/IP protocol blueprint, which is the core of the modern worldwide Internet, was published. Over this long period, technology has made rapid progress. These advancements are slowly putting pressure and new demands on the underlying network architecture design. Therefore, there was a need for innovations that could handle the increasing demands of new technologies like IoT while ensuring secrecy and privacy. It is how named data networking (NDN) came into the picture. NDN enables robust data distribution with interest-based content retrieval and a leave-copy-everywhere caching policy. Even though NDN has surfaced as a future envisioned and decisive machinery for data distribution in IoT, it suffers from new data security challenges like content poisoning attacks. In this attack, an attacker attempts to introduce poisoned content with an invalid signature into the network. Given the circumstances, there is a need for a cost-effective signature scheme, requiring inexpensive computing resources and fast when implemented. An identity-based signature scheme (IBS) is the natural choice to address this problem. Herein, we present an IBS, namely Mul-IBS relying on multivariate public key cryptography (MPKC), which leads the race among the post-quantum cryptography contenders. A 5-pass identification scheme accompanying a safe and secure signature scheme based on MPKC works as key ingredients of our design. Our Mul-IBS attains optimal master public key size, master secret key size, and user's secret key size in the context of multivariate identity-based signatures. The proposed scheme Mul-IBS is proven to be secure in the model, existential unforgeability under chosen-message and chosen identity attack (uf-cma), contingent upon the fact that Multivariate Quadratic (MQ) problem is NP-hard. The proposed design Mul-IBS can be utilized as a crucial cryptographic building block to build a robust and resilient IoT-based NDN architecture. [ABSTRACT FROM AUTHOR]

Named-Data Transport (NDT) is introduced to provide efficient content delivery by name  over the existing IP Internet. NDT consists of the integration of three end-to-end architectural components:   The first connection-free reliable transport protocol, the Named-Data Transport Protocol (NDTP); minor extensions to  the Domain Name System (DNS) to include records containing manifests describing content; and transparent caches that track pending requests for content. NDT uses receiver-driven requests (Interests) to request content and NDT proxies that provide transparent  caching of content  while enforcing privacy.  The performance of NDT,  the Transmission Control Protocol (TCP), and Named-Data Networking (NDN) is compared using off-the-shelf implementations in the ns-3 simulator. The results demonstrate that  NDT  outperforms TCP and  is  as efficient as NDN, but  without making any changes to the existing Internet routing infrastructure.

The Internet of Things (IoT) aims to efficiently connect various entities, including humans, machines, smart devices, physical environments, and others, so they can communicate and exchange data in real time. However, due to the massive amount of data transferred, the presence of devices with limited resources, heterogeneity, and mobility support would make it difficult to create a robust network with respect to performance in an IoT context. In order to efficiently disseminate the enormous volume of automated data, Named Data Networking (NDN), a viable networking design for the future Internet, has been proposed. NDN has shown great potential for IoT because it has built-in support for naming, caching, mobility, and security. Forwarding strategies play an important role in the successful deployment of NDN-based IoT. In this article, we introduce NDN-based IoT forwarding emphasizing on IoT characteristics and requirements. We classify NDN-based IoT forwarding strategies and then discuss in detail certain exemplary schemes. Additionally, we compare several aspects of current forwarding methods that are now in use, including the types of forwarding strategy, particular issues, type of solution, assessment metrics, and simulation platform. We wrap up our contribution by outlining the major open research issues that can guide future investigations in this area. We anticipate that this survey will help the community of NDN-based IoT researchers’ understanding of forwarding strategies in IoT environments.

High mobility and intermittent connectivity of nodes are the main characteristics of Vehicular Ad-Hoc Networks (VANETs). These two aspects cause problems in traditional IP networking. Named Data Networking (NDN) is presented as one of the most promising paradigms for the future Internet. NDN is a data-centric architecture. It relies on data names instead of the host’s location to make forwarding decisions. In NDN, any node can be a candidate for supplying the desired content. This feature makes the NDN architecture appealing for VANET scenarios (V-NDN). This paper presents a strategy for applying NDN to VANETs with support for geographical-based forwarding. For this purpose, an additional layer called Vehicular Adaptation Layer (VAL), is proposed to illustrate how this can be performed without altering the NDN primitives and core structure. VAL provides: 1) a mechanism to bind NDN data names to the producers’ and consumers’ geographic areas; 2) a discovery mechanism to find producers’ areas and 3) the capability of implementing, in a plug-and-play manner, geo-forwarding algorithms capable of guiding Interests towards data producers and Data packets towards data consumers.

Wireless Multimedia Sensor Network (WMSN) is a wirelessly connected sensor network featuring multimedia devices such as cameras and microphones that can retrieve video and audio streams, photographs, and scalar sensor data. Because of the low cost of cameras and microphones, in addition to significant advances in distributed signal processing and multimedia data coding approaches, WMSNs can offer multimedia content. Moreover, the most critical difficulty in the implementation of WMSN is to improve the efficiency and lifetime of the network. The Named-Data Network (NDN) technique is used in WMSNs to increase communication and transmission mechanisms efficiency. NDN is thought to be one of the most demanding Internet architectures in the future. Unlike host-centric techniques that focus on the location of the content, NDN focuses on providing the content. In this paper, we propose a novel accumulative Interest-based content-store architecture for NDN-based WMSNs to improve the efficiency of individual nodes as well as the overall network. Furthermore, the proposed solution also controls packet flooding. The proposed scheme is named “Efficient Data Retrieval and Forwarding (E-DRAFT)”. Moreover, the ndnSIM simulator is used to run comprehensive simulations. Compared to existing methodologies, the simulation results reveal that the proposed approach stops additional packet flooding and effectively stores and retrieves Data packets with enhanced processing efficiency.

As a future internet candidate, named Data Network (NDN) provides more efficient communication than TCP/IP network. Unlike TCP/IP, consumer requests in NDN are sent based on content, not the address. The previous study evaluated the NDN performance using a simulator. In this research, we modeled the system using virtual NDN nodes, making the model more relevant to the real NDN. As an essential component in every NDN router, the content store (CS) has a function to keep the data. We use First In First Out (FIFO) and Least Recetly Used (LRU) in our nodes as cache replacement algorithms. The in-depth exploration is done using various scenarios. The result shows that the cache hit ratio (CHR) increases if the size of the CS, the number of interests, and the number of consumers increases. CHR decreases as the number of producers and the number of prefixes increase. As CHR increases, round trip time (RTT) decreases. LRU provides better performance for all cases: higher CHR of 5-15% and lower RTT of 1-10% than FIFO.

In this paper, the congestion control for named data networking (NDN) is studied. A novel dynamic content store-based congestion control strategy is proposed on account of the characteristic of in-network cache in NDN. A queuing network model is constructed to judge whether congestion occurs. If the network has the tendency of congestion or the congestion happened, the buffer of the output queue is dynamically expanded by borrowing NDN content store (CS), and the forwarding rates of data packets and corresponding interest packets are reduced so as to prevent or alleviate network congestion. In order to reflect fairness, the CS to be borrowed by the data output queue in the port is calculated in terms of the data output queue length and its weight. The simulation results based on ndnSIM show that the given scheme improves the bottleneck link utilization and maintains a low packet loss rate and average flow completion time.

The rapid development of wearable technology has facilitated the collection and sharing of health data, allowing patients to benefit from caretakers and medical research. However, these personal health data often contain sensitive information and it is typically not known in advance with whom the information will be shared. Therefore, messages must be encrypted and shared while adhering to the decoupled communication model. This paper presents NACDA, a secure many-to-many data-sharing service on the Named Data Network (NDN). NACDA uses Identity-Based Encryption with Wildcard Key Derivation (WKD-IBE) to allow naming-based access control, enabling data subjects to share data securely and flexibly regardless of the data processor. In addition, NACDA supplements a decentralized authorization mechanism with blockchain to ensure data subjects' data ownership and enforce access policies. We developed an NDN-based prototype and performed a security analysis to demonstrate NACDA's feasibility. [ABSTRACT FROM AUTHOR]

The tremendous growth in the internet of things (IoT) technology has provided great support for e-healthcare applications. The remote health monitoring of patients at home is gaining popularity with the increase in design of number of IoT enabled wearable devices. The secure and efficient health data retrieval during continuous uploading of huge data on network is a challenge. In addition, another challenge exists due to limited resources available with IoT device to proceed efficient data retrieval. On the other hand, the edge cloud in edge computing technology provide abundant resources to its devices for various computations, storage and processing. The integration of IoT with edge would solve the resource constraint issue. However, efficient retrieval of health data from large pool of data would still be an issue due to IP based solutions offered by IoT. The Named Data Networking (NDN) is a promising solution for efficient delivery of data based on its name based content searching. This paper proposed NDN communication based secure remote healthcare monitoring framework by integrating IoT with edge computing where security to the each individual content is provided through hashing and encryption mechanism. The performance of the proposed framework is evaluated against its companion in Icarus simulator. The results proved the efficiency of our framework for content retrieval delay and cost associated in accessing the required data.

Fog computing is today considered a promising candidate to improve the user experience in dynamic on-demand computing services. However, its ubiquitous application would require support for this service in wireless multi-hop mesh systems, where the use of conventional IP-based solutions is challenging. As a complementary solution, in this paper, we consider a Named-Data Networking (NDN) approach to enable fog computing services in autonomous dynamic mesh formations. In particular, we jointly implement two critical mechanisms required to extend the NDN-based fog computing architecture to wireless mesh systems. These are (i) dynamic face management systems and (ii) a learning-based route discovery strategy. The former makes it possible to solve NDN issues related to an inability to operate over a broadcast medium. Also, it improves the data-link layer reliability by enabling unicast communications between mesh nodes. The learning-based forwarding strategy, on the other hand, efficiently reduces the amount of overhead needed to find routes in the dynamically changing mesh networks. Our numerical results show that, for static wireless meshes, our proposal makes it possible to fully benefit from the computing resources sporadically available up to several hops away from the consumer. Additionally, we investigate the impacts of various traffic types and NDN caching capabilities, revealing that the latter result in much better system performance while the popularity of the compute service contributes to additional performance gains.

The IoT encompasses objects, sensors, and everyday items not typically considered computers. IoT devices are subject to severe energy, memory, and computation power constraints. Employing NDN for the IoT is a recent approach to accommodate these issues. To gain a deeper insight into how different network parameters affect energy consumption, analyzing a range of parameters using hyperparameter optimization seems reasonable. The experiments from this work’s ndnSIM-based hyperparameter setup indicate that the data packet size has the most significant impact on energy consumption, followed by the caching scheme, caching strategy, and finally, the forwarding strategy. The energy footprint of these parameters is orders of magnitude apart. Surprisingly, the packet request sequence influences the caching parameters’ energy footprint more than the graph size and topology. Regarding energy consumption, the results indicate that data compression may be more relevant than expected, and caching may be more significant than the forwarding strategy. The framework for ndnSIM developed in this work can be used to simulate NDN networks more efficiently. Furthermore, the work presents a valuable basis for further research on the effect of specific parameter combinations not examined before.

In this paper, the congestion control for named data networking (NDN) is studied. A novel dynamic content store-based congestion control strategy is proposed on account of the characteristic of in-network cache in NDN. A queuing network model is constructed to judge whether congestion occurs. If the network has the tendency of congestion or the congestion happened, the buffer of the output queue is dynamically expanded by borrowing NDN content store (CS), and the forwarding rates of data packets and corresponding interest packets are reduced so as to prevent or alleviate network congestion. In order to reflect fairness, the CS to be borrowed by the data output queue in the port is calculated in terms of the data output queue length and its weight. The simulation results based on ndnSIM show that the given scheme improves the bottleneck link utilization and maintains a low packet loss rate and average flow completion time. [ABSTRACT FROM AUTHOR]

The traditional Internet architecture provides applications with a stable end-to-end connection between a requester and a source node holding the information. However, in a vehicular environment, this connection is not stable due to the mobility of vehicles that results in location change, from the requester, the source, or both. To overcome these situations, Named Data Networking (NDN) has been proposed as new architecture for data retrieval and mobility support. This new paradigm enhances content access and dissemination by decoupling the content from its original location. In this paper, we introduce the forwarding in NDN-based VANETs and highlight its benefits and limitations. We propose a classification of NDN-based VANETs forwarding strategies, then detail the representative schemes. Furthermore, we provide a review and comparison of existing forwarding strategies in terms of various attributes such as transmission mode, forwarding strategies, changes of NDN architecture, application scenarios, problem addressed, evaluation metrics, simulation platform. Finally, we conclude our contribution by identifying main open research challenges that can be exploited for future works. We believe that this survey will help NDN-based VANETs researchers community to easily understand the forwarding in vehicular environment, overcome some repeated solutions and gives further inspiration to design a new protocols to improve NDN-based VANETs networks in this context for further relevant research works.

Prader–Willi syndrome (PWS) is a multisystemic disorder. Notably, many characteristic symptoms of PWS are correlated with locus coeruleus norepinephrine system (LC-NE) dysfunction, including impairment in arousal, learning, pain modulation, and stress-induced negative affective states. Although electrophysiological experiments in necdin-deficient mice, an established PWS animal model, have revealed decreased spontaneous neuronal firing activity in the LC and impaired excitability, the behavioral phenotypes related to LC-NE dysfunction remain unexplored. In this study, heterozygous necdin-deficient mice (B6.Cg- Ndn tm1ky) were bred from wild-type (WT) females to generate WT (+m/+p) and heterozygous (+m/−p) animals. Compared to WT mice, Ndn + m/−p mice demonstrated impaired visual-spatial memory in the Y-maze test, reduced social interaction, impaired sexual recognition, and shorter falling latency on the Rotarod. Using the open field test (OFT) and elevated plus maze (EPM), we observed similar locomotion activity of Ndn + m/−p and WT mice, but Ndn + m/−p mice were less anxious. After acute restraint, Ndn + m/−p mice exhibited significant impairment in stress-induced anxiety. Additionally, the plasma norepinephrine surge following exposure to acute restraint stress was also impaired. Pretreatment with atomoxetine, a norepinephrine reuptake inhibitor aimed to enhance LC function, restored Ndn + m/−p mice to exhibit a normal response to acute restraint stress. Furthermore, by employing chemogenetic approaches to facilitate LC neuronal firing, post-stress anxious responses were also partially rescued in Ndn + m/−p mice. These data strongly suggest that LC dysfunction is implicated in the pathogenesis of stress-related neuropsychiatric symptoms in PWS. Manipulation of LC activity may hold therapeutic potential for patients with PWS. • Ndn +m/-p mice, a mouse model of Prader-Willi syndrome, exhibit several typical behavioral characteristics of PWS. • Ndn +m/-p mice is less anxious and had impairment of post-stress anxiety. • Atomoxetine and chemogenetic locus coeruleus (LC) neuronal activation restores post-stress anxiety in Ndn +m/-p mice. • LC dysfunction is implicated in the pathogenesis of stress-related neuropsychiatric symptoms in PWS. [ABSTRACT FROM AUTHOR]

The emergence of communication networks has resulted in a system of content-based networks. Therefore, a novel network design called Information-Centric Networking (ICN) promotes the efficient transfer of content objects, whereas Named-Data Networking (NDN) is one of the most promising candidates. While migration from Internet Protocol (IP) to NDN is inevitable, it is prohibitively expensive to replace all routers instantaneously with NDN routers during the transition period. Hence, we propose the dual-channel IP-to-NDN translation gateway to address this problem. The gateway promotes the semantics of the IP protocol to be equal to those of NDN at the network layer by utilizing two unique IP addresses as channels so that it can distinguish an IP packet as either an interest or a data packet. In addition, the proposed gateway uses a name binding mechanism to transmit packets between IP and NDN hosts seamlessly by conducting non-data-payload reading to preserve the privacy of users. Finally, the throughput performance of the dual-channel gateway is examined for two distinct binding strategies, namely static and dynamic prefix-name binding. We analyze the throughput by comparing a throughput-estimation model with an emulation testbed. Especially, we emphasize the relationship between the hit ratio, processing delay, and throughput. According to numerical evaluation, we show that the throughput-estimation model successfully predicts the throughput with an accuracy of about 90% and 85% in static and dynamic prefix-name binding schemes, respectively. Moreover, the results show that an increase in content popularity skewness, $\alpha $ , from 0.7 to 1.5 improved the throughput of the proposed gateway by about 70% when the cache size was 1% of the prefix name count in the static prefix-name binding. Alternatively, the throughput increased ten times when the content popularity skewness increased from 0.7 to 1.5 in the dynamic prefix-name binding.

Low Earth orbit (LEO) satellite constellations are increasingly gaining attention as future global Internet providers. At the same time, named data networking (NDN) is a new data-centric architecture that has been recently proposed to replace the classic TCP/IP architecture since it is particularly well suited to the most common usage of the Internet nowadays as a content delivery network. Certainly, the use of NDN is especially convenient in highly dynamic network environments, such as those of next LEO constellations incorporating inter-satellite links (ISL). Among other native facilities, such as inbuilt security, NDN readily supports the mobility of clients, thus helping to overcome one of the main problems raised in LEO satellite networks. Moreover, thanks to a stateful forwarding plane with support for multicast transmission and inbuilt data caches, NDN is also able to provide a more efficient usage of the installed transmission capacity. In this paper, we propose a new location-based forwarding strategy for LEO satellite networks that takes advantage of the knowledge of the relative position of the satellites and the grid structure formed by the ISLs to perform the forwarding of NDN packets. So, forwarding at each node is done using only local information (node and destination locations), without the need of interchanging information between nodes, as is the case with conventional routing protocols. Using simulation, we show that the proposed forwarding strategy is a good candidate to promote the efficient and effective future use of the NDN architecture in LEO satellite networks. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) allows all entities such as computing devices, machines, objects, people, etc., to interact with each other through their Internet Protocol (IP) addresses without human intervention. Consequently, IP addresses are being exhausted rapidly. Named-Data Networking (NDN) tends to transit the conventional host-centric network into the data-centric network. However, routing attacks such as Interest Flooding Attack (IFA) is a primary security concern. To date, far too little attention has been paid to classify the IFA detection mechanisms and further identify the key points to design an efficient detection technique. This study aimed to conduct a comprehensive survey of state-of-the-art IFA detection mechanisms and analysed the algorithms used. In this paper, we summarize the different types of possible attack models with a specific name with a description in NDN, specifically the PIT-oriented routing attack. Besides, we classified these mechanisms into nine categories with its topology used, analogy metrics and attack focus. Finally, we have highlighted and provide recommendations in some critical pieces of architecture in detection mechanism design as future challenges to secure the IoT data from IFA in NDN. [ABSTRACT FROM AUTHOR]

Aiming at the problems of high content transmission delay, high packet loss rate and low request hit rate in NDN satellite network, a multi-constraint routing algorithm for satellite network based on SDN and NDN was proposed and named SNMcRA (Satellite Networks Multi-constraint Routing Algorithm). Based on SDN’s centralized control and global view, by establishing a multi-constraint routing model, the multi-constraint information of links was combined with ant colony algorithm to solve the least-cost path that meets the multi-constraints of delay, bandwidth and packet loss rate, and the nodes dynamically complete the construction of forwarding table FIB (Forwarding Information Base) and pending request table PIT（Pending Interest Table） in the process of packet forwarding. Experimental results showed that compared with DSP algorithm, this algorithm reduces the time delay by 35%, improves the bandwidth utilization by 29%, reduces the packet loss rate by 17%, and has significant advantages in the request hit rate. [ABSTRACT FROM AUTHOR]