Interest Packets Research Articles

Survey on Content Forwarding and Caching Schemes in Vehicular Named Data Networks

For the past few decades, Vehicular Ad-hoc Networks (VANETs) has been one of the major topics for the industries, academia and researchers. Since the IP based architecture is not able to satisfy the demands of the current technology, researchers have started to explore different extensions for VANETs. Named Data Networking (NDN) and Software Defined Networking (SDN) are the two alternatives strongly focussed by the research fraternity. The NDN architecture provides an edge because of the fundamental working principle, wherein the content is addressed rather than the host. Although, Vehicular Named Data Network (VNDN) is a relatively new field, the advantage it brings about has urged the researchers to explore it further. There are issues such as content/data forwarding, routing strategies, naming schemes, channel constraints and adding security to the content without increasing overhead, creating gateways and standardization. Efficient content forwarding plays an important role in reducing the number of duplicate copies of interest and data packets. Caching the content reduces the path traversed by interest packets. These factors aid in improving the overall network performance. A survey and comparison of content forwarding strategies and caching policies with an aim to help the researchers to select the appropriate content forwarding strategies and caching policies for their research is presented in this paper.

Content delivery enhancement in Vehicular Social Network with better routing and caching mechanism

Vehicular Social Network (VSN) emerges as one meaningful scenario of Mobile Social Network (MSN) and aims at addressing the traffic congestion and security problems in smart cities. However, the current IP based network connection cannot efficiently solve the high mobility and dynamically changing topology issues caused by VSN, which results in long routing latency and low cache hit ratio. In this regard, this work intends to optimize the routing latency and the cache hit ratio by solving the content delivery problem in VSN, during which the concepts of fog/edge computing and Information-Centric Networking (ICN) are introduced, since they can provide a new perspective of network connection in VSN by concentrating on contents instead of IP addresses. Firstly, the ICN routing table structure is expanded for the purpose of providing key routing basis for both interest and data packets. Secondly, the vehicle social information is fully explored from the points of relationship strength and interest degree to offer reliable data foundation for community detection and packet forwarding. Thirdly, the dynamic vehicle communities are constructed based on an improved community overlap propagation algorithm. By monitoring the content popularity and cache distribution in the dynamic communities, this paper proposes the vehicle-adaptive caching scheme which guarantees the cache diversity and improves the packet delivery rate. After that, a vehicle-adaptive interest packet routing scheme is proposed based on relationship strength and interest degree for both inter/intra communities. The experiment results indicate that the proposed mechanism can improve the network performance in terms of the packet delivery rate, the average hop, the average delay and the overhead.

CCJRF-ICN: A Novel Mechanism for Coadjuvant Caching Joint Request Forwarding in Information Centric Networks

Information centric networking (ICN) shifts the focus of existing internet architecture from host-oriented to content-oriented model by enabling in-network caching and content-based forwarding. These ICN features help to increase network performance by decreasing content discovery delay, content server load, and network congestion. To route a content interest inside network such that content can be fetched with minimal time is a challenging task in ICN. The performance of the ICN routing protocol can be significantly improved if the decisions related to content chunk placement and request forwarding are taken in a cooperative fashion. This paper describes a novel strategy for co-operative caching joint request forwarding in ICN, focusing on decreasing content retrieval latency. To do so, the caching strategy leverages the concept of connected dominating set (CDS) for creating a virtual backbone network to eliminate caching redundancy and reduce content discovery delay. It considers content chunk placement and request forwarding tasks as strongly co-related procedures. It exploits the caching information so that the request is forwarded to a content router (CR) with the maximum likelihood of carrying needed data using the betweenness centrality (BC) of CR. The proposed approach also uses the Markov chain-based model to estimate CS hit likelihood and use it as decisional parameter while forwarding the interest packet. This mechanism helps to fetch the content within the shortest possible time duration. The CCJRF-ICN adopts the Dijkstra's shortest path routing and works in collaboration with the CDS-driven caching joint forwarding mechanism. The simulation study of CCJRF-ICN is done inside ns-3 based ndnSIM-2.0 simulator with performance measures like content store (CS) hit ratio, content discovery delay, mean hop distance, network load, and network overhead. The simulation outcomes demonstrate that CCJRF-ICN outperforms the state-of-the-art strategies for realistic topologies (GEANT, US-26, Euro-28) and shows improvement up to 5-35% against stated performance measures.

BSMM: A Broadcast Storm Mitigation Model Based On Distributed Data Clusters and Hybrid Network Architecture in Vehicular Named Data Network

Vehicle networks play a key role in intelligent traffic field. Named Data Networks (NDN) which has characteristics of interest packet driving and content caching is suitable for Vehicle networks. After the technology of NDN is used in vehicle networks, Vehicular Named-data Network (VNDN) is constructed. However, the efficiency of communication is affected by the high-speed movement of vehicles and the changing topology of VNDN. In VNDN, vehicles broadcast interest packets to retrieve required data. It is easier to rise broadcast storm because of the broadcast behaviour. In order to deal with this problem, we firstly propose a hierarchical hybrid network architecture which is consisting of vehicle network and infrastructure network. Secondly, we propose a concept of distributed data named cluster based on the hybrid network architecture. Based on the above, a novel broadcast storm mitigation strategy (BSMS) which includes a real-time route update algorithm and a hierarchical routing request algorithm is proposed to relieve the broadcast storm. At the same time, the proposed model based on distributed data named clusters provides a real-time update data request interface for vehicles. The simulation results show that the proposed model BSMM is able to resist the broadcast storm and improve the efficiency of communication among vehicles in VNDN.

A receiver-forwarding decision scheme based on Bayesian for NDN-VANET

Named Data Network (NDN) has caused wide concerns in VANET community because NDN uses a content-centric mechanism that naming content rather than the host. However, integrating NDN into VANET (NDN-VANET) also faces several challenges including consumer/provider mobile, broadcast storm problem and so on. In this paper, we propose a Bayesian-based Receiver Forwarding Decision (BRFD) scheme to mitigate the broadcast storm problem incurred by interest packets in NDN-VANET. In the BRFD, vehicles received an interest packet are required to make forwarding decisions based on Bayesian decision theory according to current network conditions obtained by neighbor interaction. However, the receiver-forwarding decision in BRFD can also cause a conflict issue because multiple vehicles forward copies of the same packet at the same time. So a back-off mechanism is introduced in BRFD. Experimental results show that the BRFD algorithm has better performance in several aspects in contrast to probability-based forwarding scheme and bread crumb routing.

Achieving High Throughput for Heterogeneous Networks With Consecutive Caching and Adaptive Retrieval

Heterogeneous networks raise the challenge on ubiquitous connections among heterogeneous devices and networking protocols. As a promising approach to meet this challenge, Information-centric networking (ICN) offers a new communication paradigm which can conceal the heterogeneity of underlying networks. However, it suffers from the problem of segmented cached chunks, which results in low throughput caused by high frequency of switching among different nodes holding chunk copies, and the large Interest packet overhead (IPO). Although the studies on in-network caching or Interest pipelining based on delay estimation help to improve ICN performance, they cannot address such problem and further improve ICN performance fundamentally, because of their insufficient considerations on the interplay between caching and transport protocols. We conduct the experiments and observe that 1) data chunks are cached in a distributed manner with ICN, and 2) range-based data retrieval can reduce switch-over frequency and IPO. Based on these observations, we propose the adaptive retrieval with consecutive caching (ARCC) scheme, which is composed of the consecutive data chunk caching (ConCaching) and adaptive data chunk retrieval (ACUR). ARCC bridges the gap between caching and transport, where intermediate nodes on transmission path only cache the consecutive data chunks with the size above a threshold, while users can adjust the range of requested data chunks to maximize the throughput. This way, at most a range of consecutive data chunks can be retrieved by one Interest , and users retrieve data from the small set of nodes with low switch-over frequency. The intensive simulations show that the proposed mechanisms can achieve the objectives of consecutive chunk caching, in terms of substantial reduction in IPO and switch-over frequency and higher throughput compared with the existing pipeline mechanism in ICN.

F-NDN: An Extended Architecture of NDN Supporting Flow Transmission Mode

As a promising candidate for future Internet architecture, Named Data Networking (NDN) can achieve significant potential advantages over current TCP/IP based Internet in content distribution and mobility support, etc. However, the communication mode in NDN that one Interest packet for pulling one data packet is likely to incur Interest packets flooding and to cause extremely large-scale Pending Interest Table (PIT) of the NDN router, which may substantially degrade the performance of NDN. Moreover, the absence of predefined connections also induces another challenge for NDN to manage the successive and concurrent requests from consumers efficiently. In this paper, we propose flow-based NDN ( $f$ -NDN) architecture capable of supporting flow transmission mode for addressing the aforementioned challenges. In the context of $f$ -NDN, a data flow is defined as an aggregate of data packets with the same name prefix, and a flow Interest packet is introduced to pull a data flow rather than a single data packet. The PIT, CS, and FIB are re-designed to enable $f$ -NDN to operate at the granularity of flows. Bitmap structure aided error handling mechanism is further presented for $f$ -NDN to deal with the flow transmission’s uncertain failures. The built-in flow support in $f$ -NDN allows us to conceive a flow-level multi-path transmission regime for balancing the traffic in NDN network and reducing the time consumed for pulling the entire content. Weight-based flow Interest splitting algorithm and optimal rate control algorithm are both proposed for optimizing multi-path transmission. We illustrate the capability of the proposed architecture in supporting flow transmission and multi-path by implementing it in both simulator and prototype systems. The evaluation results are also presented to show its achievable performance.

Towards Improved Vehicular Information-Centric Networks by Efficient Caching Discovery

The number of connected cars and the massive consumption of digital content on the Internet have increased daily. However, the high mobility of the vehicles, coming from patterns’ variation over time, makes efficient large-scale content distribution quite challenging. In light of this, the emerging Vehicular Named Data Network (VNDN) architecture provides support for content-centric network communications and caching capabilities, which allows reliable and larger-scale content delivery over Vehicular Ad-Hoc Networks (VANETs). This notwithstanding, the high number of interest packets in VNDN tends to introduce broadcast storm occurrences during the cache discovery process. Thus, network performance degradation comes up for the influence of both increased packet loss rates and delays on content recovery during communication between vehicles. This work proposes a new cache discOVEry pRoTocol (OVERT VNDN), which combines the computational geometry and degree centrality concepts to tackle the VNDN performance degradation challenges and issues. The main idea behind OVERT VNDN is to choose the most appropriate relay vehicles to engage interest packets’ delivery within the VNDN, seeking to achieve higher network performance by optimizing broadcast storm incidence. The obtained results suggest that OVERT VNDN outperforms its competitor in the following key performance indicators: (i) improving the cache discovery process by 120.47%; (ii) enhancing the content delivery rate by 43%; and (iii) reducing the number of interest packets by 80.99%.

Detecting and Mitigating DDoS Attack in Named Data Networking

Named Data Networking (NDN) is a new and attractive paradigm that got a broad interest in recent researches as a potential alternative for the existing IP-based (host-based) Internet architecture. Security is considered explicitly as one of the most critical issues about NDN. Despite that NDN architecture presents higher resilience against most existing attacks, its architecture, nevertheless, can be exploited to start a DDoS attack. In the DDoS attack, the attacker tries to create and transmit a large number of fake Interest packets to increase network congestion and thus dropping legitimate interests by NDN routers. This paper proposes a new technique to detect and mitigate DDoS attacks in NDN that depends on cooperation among NDN routers with the help of a centralized controller. The functionality of these routers depends on their positions inside the autonomous system (AS). The simulation results show that the suggested technique is effective and precise to detect the fake name prefixes and, it offers better performance comparing with the previously proposed ones.

An SDN-Based Caching Decision Policy for Video Caching in Information-Centric Networking

The considerable increase of multimedia services, such as video-on-demand (VoD) services, is a significant contributor to the total Internet traffic. Software-defined networking (SDN) and information-centric networking (ICN) are two promising technologies that can be combined to facilitate video delivery and to reduce network delays. In this paper, we first formulate the caching decision problem as a 0-1 integer linear programming (ILP) problem. Second, in contrast to existing approaches that solve the formulated ILP problem by assuming all future video requests are known, we consider the impact of the time scale, which transforms the static 0-1 ILP problem into a dynamic problem. By solving the dynamic 0-1 ILP problem, we find more accurate optimal solutions compared to existing approaches. Third, since the formulated 0-1 dynamic ILP problem is NP-hard, we leverage the in-network caching of ICN and the global view of the SDN controller to propose a novel SDN-based caching decision policy. Finally, extensive evaluations are performed, and the results demonstrate that the proposed SDN-based caching decision policy provides solutions that are close to the optimum in substantially less computation time. The SDN-based caching decision policy also outperforms existing practical ICN caching decision policies in terms of the cache hit ratio and the average number of hops, which are directly related to the video delivery latency. Moreover, the SDN-based caching decision policy can substantially reduce the number of generated and broadcasted interest packets, which is a shortcoming of the current ICN.

Quality of Service provisioning in Named Data Networking via PIT entry reservation and PIT replacement policy

Named Data Networking (NDN) is a promising candidate of Future Internet Architecture (FIA) designed to solve many long-standing issues in current IP architecture such as security, mobility, and content distribution inefficiency. Pending Interest Table (PIT) is one of the essential building blocks of NDN, which is used in the successful delivery of data packets to the requesters. It helps to achieve intrinsic advantages such as anonymity, interest aggregation, multi-cast delivery, multi-path forwarding, and security. NFD (NDN Forwarding Daemon) currently does not constrain the size of PIT. Over-allocation of PIT does not contribute to network performance improvement rather helps in performance degradation. Therefore, there is a need to restrict PIT size. However, in the presence of bursty traffic, PIT may turn out to be full, and new incoming Interest packets may get dropped. In this case, NDN faces a new challenge to achieve Quality of Service (QoS) under bursty traffic. This paper presents two simple schemes to solve this problem via PIT entry reservation and PIT entry replacement policy. We present analytical models of both the schemes using Continuous Time Markov Chain (CTMC). We derive blocking and forced termination probability of Interest packets as performance metrics. The accuracy of the models is validated through simulation results.

A novel software-defined networking controlled vehicular named-data networking for trustworthy emergency data dissemination and content retrieval assisted by evolved interest packet

Vehicle ad hoc network is the key technology for a future Internet of vehicles and intelligent transport system. However, involvement of vast number of vehicles in Internet of vehicles limits the performance of vehicle ad hoc network. To tackle this problem, a novel vehicle ad hoc network architecture with two different technologies such as software-defined networking and named-data networking is proposed in this article. In the proposed software-defined networking controlled vehicular named-data networking, IP addressing issue is resolved by named-data networking and global view of the network is attained by software-defined networking. Emergency data dissemination is initiated with packet classification. For packet classification, policy-based bifold classifier is proposed in roadside unit and supported by evolved interest packet. Subsequently, best disseminator selection is carried out by trustworthy weighted graph scheme based on novel weight value, which is computed by considering significant metrics. Content retrieval is accomplished by roadside unit and assisted by a controller. Location of content producer is obtained from a controller and optimal route is selected by roadside unit. Optimal route selection is performed by roadside unit for both content retrieval and vehicle-to-vehicle communication using novel region-based hybrid cuckoo search algorithm. Hybrid algorithm combines cuckoo search and particle swarm optimization algorithm to perform efficient route selection. Involvement of software-defined networking controller supports numerous users by providing a global view of the network, which includes network status and traffic information. Extensive simulation in NS-3 assures better interest satisfaction rate, interest satisfaction delay, forwarder interest packets, average hop count, and gain of scalability in software-defined networking controlled vehicular named-data networking than traditional vehicle ad hoc network.

Interest packets scheduling and size-based flow control mechanism for content-centric networking web servers

Content-Centric Networking (CCN) employs a completely different request/response pull communication model of Interest/Content packets and provides the pervasive in-network caching. Although this communication model effectively satisfy most of the popular static Web content requests, it may bring some new challenges for the dynamic Web request services, especially for the time-sensitive dynamic request. We find that the fair scheduling of Interest packets (i.e. without differentiating the new service requests and those requests being processed) will increase the average expected response time, especially when the Web requests with large-size response pages dominate or when the requests fluctuate greatly over time. To improve the performance of CCN Web servers, we present an effective First-Come-First-Served (FCFS) dynamic service requests scheduling scheme specially designed for CCN Web Servers. Furthermore, we also explore the size-based adaptive pipeline flow control approach for CCN Web servers. To validate the proposed approaches, we developed and incorporated these new functions into the existing CCN Web server implementation (named CCNxTomcat), and tested its performance by simulating the workload of three popular dynamic Web sites in a CCN testbed. Experimental results show that the improved CCNxTomcat is more friendly to the dynamic Web requests with large-size response pages and outperforms the existing CCNxTomcat in terms of mean response time in most cases.

A Responsibility-based Transport Control for Named Data Networking

Transport Control in Named Data Networking (NDN) architecture is a challenging task. The lack of end-to-end communications in this architecture makes traditional, timeout-driven transport control schemes inefficient and wasteful. Hop-by-hop transport control is an alternative solution to tackle this problem that because of the stateful forwarding plan of NDN can be applied more easily than the IP networks. Most existing solutions in this direction assume known link bandwidths and Data packet sizes or require a loop-free multipath forwarding strategy to work well, but these assumptions do not always hold true and there exist no a loop-free multipath forwarding strategy among the existing forwarding strategies for NDN. In this paper, a Responsibility-based Transport Control (RTC) protocol for NDN is proposed. This protocol does not make strong assumptions about the network and avoids looping paths by applying a window-based rate control mechanism and a capacity-aware, multipath forwarding strategy in each face. In RTC, routers maintain a congestion window in each face and decide on accepting or refusing to take responsibility for forwarding of a newly received Interest packet through exchanging three new control packets. These control packets provide reliable information for managing the congestion windows and capacity-aware traffic splitting in routers. They also enable diverse deployment scenarios for NDN such as IP-overly and wireless links. The RTC is implemented in ndnSIM and its capability in managing congestion, achieving high throughput and providing flow fairness are demonstrated through extensive simulations.

AFSndn: A novel adaptive forwarding strategy in named data networking based on Q-learning

Named Data Networking (NDN) is a new network architecture, which employs a new content-centric communication model to replace the traditional host-centric communication model. In TCP/IP network, data packets are forwarded by routers according to routing table established previously. While in NDN, routing nodes can dynamically make forwarding decisions based on network status. By considering this forwarding feature, we proposed a novel adaptive forwarding strategy in Named Data Networking (AFSndn) based on Q-learning to minimize the delivery time. AFSndn is divided into two phases—Exploration phase and Exploitation phase. The Exploration phase aims to collect information, while the Exploitation phase aims to dynamically forward interest packets. Simulation experiment results show that AFSndn has better performance compared to others famous algorithms.

A Reputation Value-Based Early Detection Mechanism Against the Consumer-Provider Collusive Attack in Information-Centric IoT

As the Internet of Things (IoT) has connected large number of devices to the Internet, it is urgently needed to guarantee the low latency, security, scalable content distribution of the IoT network. The benefits of Information-Centric Networking (ICN) in terms of fast and efficient data delivery and improved reliability have raised ICN as a highly promising networking model for IoT environments. However, with the widely spread of the viruses and the explosion of kinds of network devices, the attackers can easily control the devices to form a botnet such as the Mirai. Once the devices are under control, the attackers can launch a consumer-provider collusive attack in the Information-Centric IoT context. In this attack, the malicious clients issue Interest packets that can only be satisfied by the malicious content provider, and the malicious provider replies to the clients just before exceeding the Pending Interest Table entry’s expiration time, to occupy the limited resources. In this paper, we expound the model of the consumer-provider collusive attack and analyze the negative effect of the attack. Then we propose a Reputation Value based Early Detection (RVED) mechanism to relieve the impact of the collusive attack. The method aims to adjust the packet dropping rates of different interfaces based on their reputation value, thus to protect the legitimate packets from being dropped as possible. We implement the consumer-provider collusive model and evaluate our defend mechanism in the simulator, and simulation results verify the feasibility and effectiveness against the collusive attack of the RVED mechanism.

Smart Contract-Based Trusted Content Retrieval Mechanism for NDN

Named Data Networking (NDN) is a new clean-slate architecture for the future Internet. Efficient content retrieval is the original intention of NDN design. The content retrieval process driven by content consumers in NDN includes the following challenges, consumers do not know whether the content exists and whether the content producer is reliable. Invalid interest packets could cause the occupation of limited network resources and DoS attack problem. To ensure the authenticity and integrity of the data packets, consumers need to pre-configure the trust schema, which is centralized and prone to the single point of failure problem. Blockchain has widespread attention to build trust in a distributed way, and Ethereum is a programmable blockchain, a decentralized smart contract platform. To lighten the burden of consumers, we proposed a Smart Contract-based Trusted Content Retrieval Mechanism (SCTCRM) for NDN in this paper. The mechanism contains a trustworthy information base for content and producers based on smart contracts, and provides content retrieval and name resolution services for content consumers. The purpose of this mechanism is to improve the efficiency and security of content retrieval process. We described the framework and the workflow of SCTCRM, and used Colored Petri Nets to create a formal mathematical model and analyze the security of the mechanism. Finally, the cost of storage and Gas in smart contracts are evaluated through the prototype deployment. From the results, we can see that the proposed mechanism is security and practicality.

Stabilized Clustering Enabled V2V Communication in an NDN-SDVN Environment for Content Retrieval

Content retrieval is becoming an emerging application on an integrated network structure referred to as Software Defined Network and Vehicular Ad hoc Network (SDVN). The SDVN is expected to flexibly provide efficient packet routing without deploying road side units. In such the infrastructure-less environment, however, it is challenging to retrieve contents from dynamic networks clustered with vehicles on roadways. As a solution to the problem, we propose a new network design by conjoining Named Data Network (NDN) with SDVN (NDN-SDVN). The new NDN-SDVN is designed as to improve stableness of the cluster formation and hence enables to efficiently perform the content retrieval over Vehicle-to-Vehicle (V2V) communications. Note that one of the most important problems in the V2V is how to select a cluster head. The proposed NDN-SDN adaptively determines the cluster head by using the SDN controller under the maximum Quality of Service (QoS) criterion, while reserving an assistance head based on a Moth Flame Optimization (MFO) algorithm to immediately recompose a new cluster with the back-off time. Moreover, the content retrieval in the NDN-SDVN can be performed over both intra- and inter-cluster communications. To this end, a Kalman filter with Neural Network (KF-NN) is applied for selecting a certain number of preferable vehicles in 1-hop in order to mitigate the broadcast storm problem that often occurs in an NDN. Content retrieval is initiated by sending interest packets including two additional fields of the timestamp and the target MAC address. The head vehicle of the SDN controller maintains ontology regarding the content information cashed by other vehicles, which significantly improves the packet delivery ratio. This NDN-SDVN design is developed on the OMNeT++ simulator and their advantageous results are evaluated in terms of the head lifetime, the cluster lifetime, the satisfactory rate, the latency and the packet delivery ratio.

The Detection Method of Collusive Interest Flooding Attacks Based on Prediction Error in NDN

Named Data Networking (NDN) is one of the main research projects of the information center network (ICN), and its efficient forwarding mechanism attaches the attention of researchers. Like other networks, NDN also faces the threat of cyber attacks. With the assistance of the colluding server, the Collusive Interest Flooding Attacks (CIFA) can use the defects of the NDN’s internal forwarding mechanism to send malicious interest packets in the form of pulses. It affects the normal requests of legitimate users and reduces the quality of NDN network services in this way. By analyzing the characteristics of network traffic and CIFA model, a new CIFA detecting method based on the prediction error between particle filter and one-step prediction algorithm is proposed. This scheme samples the network traffic and judges whether the network is under attack by comparing the normalized error value of the one-step prediction and the estimate of the particle filter. Experimental analysis shows that the detection scheme in this paper has higher detection rate than the existing detection schemes.

A density-aware probabilistic interest forwarding method for content-centric vehicular networks

Vehicular networks, compared to other wireless networks, face particular challenges due to the rapidly changing topology and intermittent connections. By eliminating the need to establish and maintain an end-to-end connection, Content-Centric Network (CCN) model has recently become an appropriate solution to meet the challenging demands of vehicular network communications. In this kind of network, the basic method of forwarding interest packets is flooding. This approach will result in excessive redundancy, serious contention, and collision to which it is referred as the broadcast storm problem. In this article, a probabilistic strategy is proposed to alleviate the impact of the broadcast storm on interest forwarding in content-centric vehicular networks. In this density-aware approach, each vehicle dynamically computes the probabilities based on the number of existing neighbors. A local density approximation method is presented, which uses the information provided by the newly modified Pending Interest Table (PIT) entries. Moreover, some time-based techniques are employed to give priority to potential forwarders. The simulation results indicate that the proposed work outperforms the basic CCN. With on average 40% lower network load and 65% fewer interests compared to the basic CCN, it shows only an overall 6% decrease in reachability.