Vehicular Content Centric Networks Research Articles

Detection of Cache Pollution Attack Based on Ensemble Learning in ICN-Based VANET

Content Centric Network (CCN) can be extended to efficiently and reliably support content delivery and solve the network performance degradation caused by dynamic topology and intermittent connectivity of Vehicle Ad hoc NETwork (VANET). However, the in-network caching mechanism of Vehicular Content Centric Network (VCCN) is vulnerable against Cache Pollution Attack (CPA), where attackers aim to fill the buffer space with non-popular contents by releasing fake requests. Unavoidably, the cache hit ratio of content requests from legal users is degraded and the content retrieval latency is increased under CPA. Hence, it is critical to detect and mitigate CPA. The current solutions for static CCN cannot be directly applied into dynamic VCCN. In this paper, we propose a detection scheme based on hybrid heterogeneous multi-classifier ensemble learning, where CPA is determined by the cooperation of multiple vehicles. In our scheme, each vehicle can build or join a cluster whose head possesses more common moving attributes of position, speed and direction with other members. Besides, the cluster head as a base learner is responsible for training its own classifier by making some relevant statistics on requests and hit ratio. Specifically, the problem of ensemble classifier making from the individual classifiers is formulated as a linear optimization problem, with the goal of minimizing the false ratio of detecting CPA. The generalization ability of ensemble learning can make very accurate predictions on CPA. By comparison, our detection scheme outperforms the existing schemes in terms of detection ratio, hit ratio, retrieval delay. Besides, simulations have proved that the overfitting problem of adopting a singe base learning algorithm can be alleviated in our scheme.

Exploiting Non-Cooperative Game Against Cache Pollution Attack in Vehicular Content Centric Network

Vehicular Content Centric Network (VCCN) has been proposed to address the issues of user mobility and sporadic connectivity in Vehicular Ad hoc Network (VANET). The in-network caching of VCCN can indeed improve the performance of content distribution in terms of cache hit and delivery latency by making each node store frequently accessed data. However, data caching unfortunately suffers from Cache Pollution Attack (CPA) that sends out fabricated requests to pollute the data cache. To prevent the degradation of network performance caused by such an attack, we propose a detection and defense scheme for CPA by adopting game theory. We model the attack scenario into a non-cooperative game model. First, we prove the non-existence of pure strategy Nash Equilibrium (NE) in the attacker and defender game, and propose a normal form game model with complete information and an extensive Bayesian form game model with incomplete information. Under the guidance of NE, we propose a punishment strategy to prevent the conspiracy attack and make the attackers behave normally. Moreover, we propose a cooperative detection scheme to give the Road Side Unit (RSU) the final decision on CPA based on the direct and indirect suspicious lists which are generated by each node according to the observed traffic pattern. Simulation evaluations demonstrate that our scheme outperforms state-of-the-art schemes in terms of cache hit, detecting ratio, and cache accuracy for detecting and defending CPA.

A Cooperative Caching Scheme for VCCN With Mobility Prediction and Consistent Hashing

In order to mitigate the performance degradation of intermittent vehicular network caused by traffic mobility and sporadic connectivity issues, Vehicular Content Centric Network (VCCN) has been proposed to apply many technologies in Content Centric Network (CCN) into vehicular ad hoc networks. The open in-network caching strategy of CCN enables sharing and coordination of the cached data among multiple nodes as an efficient data access without relying on remote fetching. Nonetheless, few studies have considered the effective use of overall cache capacity with these cooperative nodes, especially the issues of cache duplication. Furthermore, most content replacement polices have ignored the needs of cooperative contents when making cache decisions. In this paper, we design a novel Cooperative Caching scheme by using Mobility Prediction and Consistent Hash for VCCN (called CCMPCH). Specifically, based on the observation that vehicles with the same trajectory are more likely to maintain stable communication links, we adopt Prediction by Partial Matching (PPM) to forecast each vehicle’s path and cluster the vehicles with similar future path, moving direction, and moving speed into one group. In each cluster, the consistent hash algorithm is used to allocate contents among cooperative nodes, thereby reducing unnecessary cache duplication while maintaining strong content availability. A popularity-based cache replacement policy is also developed to prioritize cooperative contents. We evaluate CCMPCH via extensive simulations, which demonstrates its higher cache hit ratio, shorter content access delay, and lower hop count compared to other state-of-the-art schemes.

Mitigating Broadcasting Storm Using Multihead Nomination Clustering in Vehicular Content Centric Networks

Vehicles are highly mobile nodes; therefore, they frequently change their topology. To maintain a stable connection with the server in high-speed vehicular networks, the handover process is restarted again to satisfy the content requests. To satisfy the requested content, a vehicular-content-centric network (VCCN) is proposed. The proposed scheme adopts in-network caching instead of destination-based routing to satisfy the requests. In this regard, various routing protocols have been proposed to increase the communication efficiency of VCCN. Despite disruptive communication links due to head vehicle mobility, the vehicles create a broadcasting storm that increases communication delay and packet drop fraction. To address the issues mentioned above in the VCCN, we proposed a multihead nomination clustering scheme. It extends the hello packet header to get the vehicle information from the cluster vehicles. The novel cluster information table (CIT) has been proposed to maintain several nominated head vehicles of a cluster on roadside units (RSUs). In disruptive communication links due to the head vehicle’s mobility, the RSU nominates the new head vehicle using CIT entries, resulting in the elimination of the broadcasting storm effect on disruptive communication links. Finally, the proposed scheme increases the successful communication rate, decreases the communication delay, and ensures a high cache success ratio on an increasing number of vehicles.

Cooperative Caching in Vehicular Content Centric Network Based on Social Attributes and Mobility

Communications in vehicular ad-hoc network (VANET) are subject to performance degradation as results of channel fading and intermittent network connectivity. The emerging Vehicular Content Centric Network (VCCN) is promising in supporting the needs of contents and alleviating the communication problems in VANET. Specifically, to improve the cache hit ratio and reduce the access delay of content retrieval, it helps to choose the appropriate vehicles to cache the frequently accessed data items. In this paper, we propose a Cooperative Caching scheme based on Social Attributes and Mobility Prediction (CCSAMP) for VCCN. CCSAMP is based on the observation that vehicles move around and are liable to contact each other according to drivers' common interests or social similarities. A caching node sharing more social attributes with the content requester is more likely to be interested in the same contents and distribute the contents to others with similar interests. Furthermore, a caching node that frequently meets other nodes is a better candidate to keep cache copies. To increase the network performance, CCSAMP also exploits the regularity of vehicle moving behaviors to predict the chance for a vehicle to reach hot zones based on Hidden Markov Model (HMM). We evaluate CCSAMP through the ONE simulator to demonstrate its higher cache hit ratio and lower content access delay compared to other state-of-the-art schemes.

Popularity prediction caching based on logistic regression in vehicular content centric networks

To improve the network performance caused by mobility and sporadic connectivity in the vehicular network, vehicular content centric network (VCCN) is proposed by applying CCN into the vehicular network. The open in-network caching of CCN makes nodes cache contents cooperatively to facilitate information access. To improve the network performance such as access delay and hit ratio, road side units (RSUs) should try to cache more popular contents and provide better service for mobile users. This paper aims to propose a novel cache replacement policy - popularity prediction content caching (PPCC) for VCCN. In PPCC, we incorporate the future popularity of contents into our decision making. By learning the popularity of contents, we propose a cache replacement method based on logistic regression for RSUs in order to store those frequently access contents. The input data are related to the inherent characters of the received interests and the output is the predicted content popularity which guarantees that only popular contents are cached in the network infrastructures (i.e., RSUs). Simulation evaluations demonstrate that our scheme is very effective with higher cache hit, lower access latency and higher caching efficiency compared to other state-of-the-art schemes.

Popularity prediction caching based on logistic regression in vehicular content centric networks

Popularity prediction caching based on logistic regression in vehicular content centric networks

Vehicular Content-Centric Networking Framework

In vehicular content-centric networking, contents are usually acquired in the broadcast way and this flooding inevitably increases the content acquisition cost. Moreover, vehicular content-centric networking depends on reverse paths to return the requested contents to a requester. If reverse paths disrupt due to turning or parking, then the requested contents cannot be forwarded to a requester. In this case, content acquisition failure occurs. In order to reduce the content acquisition cost and improve the content acquisition success rate, we are motivated to employ the address-centric unicast instead of the content-centric broadcast to achieve content acquisition. Based on this motivation, we propose an IP-based vehicular content-centric networking framework, which focuses on acquiring contents related to a given position. In this framework, a requester acquires contents in the address-centric unicast way, so the contents can be returned to the requester without depending on reverse paths. Moreover, contents in a given position are obtained from the nearest provider, so the content acquisition cost can be reduced. Finally, this framework is analyzed and evaluated, and the data show that it effectively reduces the content acquisition cost and improves the content acquisition success rate.

Differentiated Caching for Improved QoS in Vehicular Content-centric Networks

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

A Cooperative Caching Scheme Based on Mobility Prediction in Vehicular Content Centric Networks

Vehicular content centric networks (VCCNs) emerge as a strong candidate to be deployed in information-rich applications of vehicular communications. Due to vehicles’ mobility, it becomes rather inefficient to establish end-to-end connections in VCCNs. Consequently, content packets are usually sent back to the requesting node via different paths in VCCNs. To improve network performance of VCCNs, node mobility should be exploited for vehicles to serve as relays and to carry data for delivery. In this paper, we propose a scheme called cooperative caching based on mobility prediction (CCMP) for VCCNs. The main idea of CCMP is to cache popular contents at a set of mobile nodes that may visit the same hot spot areas repeatedly. In our CCMP scheme, we use prediction based on partial matching to predict mobile nodes’ probability of reaching different hot spot regions based on their past trajectories. Vehicles with longer sojourn time in a hot region can provide more services and should be preferred as caching nodes. To solve the problem of limited buffer at each node, we design a cache replacement based on content popularity to guarantee that only popular contents are cached. We evaluate CCMP through the opportunistic network environment simulator for its salient features in success ratio and content access delay compared to other state-of-the-art schemes.

Secure and Efficient Content Distribution in Crowdsourced Vehicular Content-Centric Networking

In future intelligent transportation systems, a large amount of content needs to be efficiently and securely exchanged between vehicles and roadside units via vehicular networks to improve the driving and traveling experience. To solve the challenges caused by poor-quality wireless links and the mobility of vehicles, vehicular content-centric networking (VCCN) emerges as a promising paradigm, which has a better content distribution efficiency, mobility, and security via named data and in-networking caching compared with an IP-based network. However, providing a high-quality experience for content distribution in VCCN is challenging due to the dynamic network topologies, varying wireless channel conditions, and vehicle user privacy. In this paper, we propose a novel crowdsourced VCCN framework for secure and efficient content distribution. This framework enables the nearby vehicles to crowdsource their caching resources and radio links for cooperative content distribution. We formulate the problem as the maximization of all users’ payoff and propose an online scheduling method to solve this solution. Furthermore, we adopt identity-based proxy reencryption and named function networking to secure the process of content distribution. The simulation results show that our proposals improve the performance of VCCN in terms of average requester utility compared with original CCN forwarding strategies.

Big data analytics for mitigating broadcast storm in Vehicular Content Centric networks

The focus of the research for big data analytics for sustainability (BDAS) is Vehicular Adhoc Networks (VANETs), since it has become the most popular technology for the researchers, academia and the organizations. However, in VANETs most part of the time a well-defined path from a consumer to the provider does not exist due to the intermittent connectivity and mobility. Hence, Vehicular Content Centric Networks (VCCNs) has been proposed and has emerged as a future Internet technology. The focus of the VCCNs is to retrieve and distribute the content faster than the existing Internet architecture in vehicular environment. In VCCNs, the consumer broadcasts the interest packet to the provider, including the name of the required content. If the provider is available at one hop neighbour, the interest packet is sent to the provider. The provider generates the data packet and sends back to the consumer. Otherwise, the neighbour vehicle becomes the forwarder vehicle who receives the interest packet from the consumer and searches in its cache called Content Storage (CS). If the content is not available in its storage, the forwarder vehicle rebroadcasts the interest packet within its vicinity forwards the interest packet to the provider. The provider generates the data packet including the content and sends back to the consumer through the selected forwarder vehicle. The VCCNs communication paradigm faces several challenges i.e., mobility, interest broadcast storm, routing, interest or data packet forwarding and forwarder selection. Various routing protocols have already been proposed and implemented in order to resolve the existing problems. However, due to the high mobility and the dynamic network topology in vehicular environment, there is no assurance that the back path is still available followed by the interest message which causes disconnected link problem. Hence, the retrieval of the required data might be effected. Thus, the aim of this paper is to propose a forwarding protocol to mitigating the interest broadcast storm and the disconnected link problems, keeping in the view of intermittent connectivity and high mobility that will improve the data delivery probability, packet loss ratio, Interest Satisfaction Ratio (ISR) and average End-to-End delay in a highway and an urban scenario of a vehicular environment. Results and demonstrations show that the proposed protocol meets all the requirements for BDAS.

ECCN: an extended CCN architecture to improve data access in vehicular content-centric network

Content-centric network (CCN) has been considered for VANETs, due to its scalability, flexibility and security. In this paper, an extended CCN architecture is proposed to reduce critical data access time in vehicular content centric networks by storing them in the number of vehicles around the source. The critical data include sensitive data such as accidents, traffic that require quick and reliable access. The aim is to reduce access time for this type of data in the discovery phase. Each vehicle stores or updates critical data in cooperation with other vehicles in the preparation phase. During the preparation phase, the critical data spread around the source by a combination of physical movement and radio propagation. This gives the requesting vehicle a better chance to find the data in a few hops, with minimal network overhead and lower delay, during the discovery phase. The efficiency of this architecture is evaluated by simulation and shown that interest packet delay and number of duplicated data packets are generally lower than the existing methods.

A Novel Urban Vehicular Content-Centric Networking Frame

In current vehicular content-centric networks, contents are usually acquired in the broadcast way. Moreover, it is hard for a requester to acquire contents from a remote provider because the global routing is not supported. Taking these issues into account, this paper proposes an IPv6-based unban vehicular content-centric networking frame. In this frame, the architecture based on road segments is proposed, and based on this architecture a requester can obtain contents in the unicast way instead of in the broadcast way. Moreover, the content address structure is proposed, and via a content address a requester can acquire contents from a remote provider. Finally, the performance of the proposed frame is evaluated, and the data results show that this frame effectively improves the contents acquisition success rate and reduces the contents acquisition cost and latency.

Hierarchical and hash based naming with Compact Trie name management scheme for Vehicular Content Centric Networks

Content-Centric Network (CCN) is a promising future Internet architecture, attracting research community and being widely adopted in the vehicular networks. The main concept of CCN is to smoothly distribute digital contents between the content provider and consumer. In these types of networks, contents are identified by unique names, however, naming those contents is still a challenging task. Therefore, we propose a hierarchical and hash based naming with efficient Compact Trie (CT) management scheme for Vehicular Content-Centric Network (VCCN). The proposed naming scheme makes the best use of the features offered by hierarchical as well as hash-based or flat naming schemes. The hierarchical part of the digital content name contains information about the content provider, type, its sub-types and attributes of the content itself that is shared between vehicles. The hash part uniquely identifies the digital content required for VCCN applications. The proposed naming scheme satisfies two main purposes: first, it helps in minimizing the routing table by aggregating the name prefixes and simplifying the routing decisions. Second, it contains attributes, spatial, temporal and their range information to easily find and resolve the content. The proposed scheme manages prefixes (e.g. Add, Search and Delete) in the tables e.g. Forwarding Information Base (FIB), Pending Interest Table (PIT), etc. The CT is relatively faster and space-efficient than Simple Trie and has better performance compared to the existing solutions of naming the required content(s). The evaluation results show that the proposed CT based prefix management scheme performs 45.5% and 23.3% faster prefix search and 55% and 34% faster prefix delete operation compared to Simple Trie and Bloom-Filter based name management schemes, respectively. The memory profile results show that average memory consumption of the proposed CT implementation is 24 and 186 times smaller than the Simple Trie and the NLAPB, respectively.

RUFS: RobUst Forwarder Selection in Vehicular Content-Centric Networks

Vehicular Content-Centric Network (VCCN) has emerged as a future network technology for vehicular networks, where the focus of communication is shifted from the host to information centric. However, VCCN faces several challenges, including interest/data packet(s) flooding, provider/consumer mobility, and so on. In this letter, we propose a scheme named RobUst Forwarder Selection (RUFS) to mitigate the interest broadcast storm. In RUFS, each vehicle shares its satisfied interest(s) statistics with neighbors. All neighbors store this information in their Neighbors Satisfied List (NSL), which helps to select the potential interest forwarder. Simulation results show that RUFS outperforms the recently proposed NAIF, DR based and basic interest forwarding in VCCN.