Popularity Incentive Caching for Vehicular Named Data Networking

In this thesis, Vehicular Named-Data Networking (VNDN) refers to the use of the Named-Data Networking communication model over Vehicular Ad-hoc Networks. With the aim of addressing the problems caused by mobility to efficiently support VNDN communications in highly mobile traffic scenarios, various contributions were proposed in the scope of this thesis. These contributions include a routing protocol, able to address VNDN problems such as broadcast storms and message redundancy, as well as solutions to enable content advertisements and for addressing the problems caused by reverse path partitioning, network partitioning, and source mobility. Finally, all the proposed solutions are integrated into a single framework called MobiVNDN. The evaluation results show that the proposed solutions are efficient and scalable, providing high VNDN application performance even in complex traffic scenarios

Vehicular Ad-hoc Networks (VANETs) has been one of the hot topics for the researchers, industries and academia for the past few decades. However, current IP based architecture is not able to cope up to the demands and researchers have looked out for ways to extend VANET architecture. Two possible collaborations which are strongly focused include Software Defined Networks (SDN) and a paradigm which is considered as part of future internet architecture Named Data Networks (NDN). 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 advantages it brings about has urged the researchers to explore it more. There are a few issues like content/data forwarding, routing strategies, naming schemes, channel constraints and adding security to the content without increasing overhead, creating gateways an standardization. The paper focuses on various content naming schemes employed in named data based vehicle networks.

Vehicular ad hoc networks have highly dynamic topologies, making data exchange among mobile nodes challenging. Named data networking (NDN) has been applied to vehicular networks recently, and the results are promising, as NDN supports highly dynamic topologies better than traditional IP architectures. However, as of yet, vehicular named data networks (VNDNs) have no support for pushing critical data into the network, and the existing consumer pull mechanism introduces undesirable delay. Therefore, we propose a proactive data dissemination scheme for pushing critical content to one-hop neighbours in VNDN. Producers of critical content first send a beacon message containing metadata about tentative new chunks. Upon receiving the beacon message, neighbors make temporary pending interest table entries, allowing them to subsequently store new chunks once received. We evaluate the proposed scheme using ndnSIM and find it more efficient than pure consumer pull VNDN.

The detection of secure vehicles for content placement in vehicle to vehicle (V2V) communications makes a challenging situation for a well‐organized dynamic nature of vehicular ad hoc networks (VANET). With the increase in the demand of efficient and adoptable content delivery, information‐centric networking (ICN) can be a promising solution for the future needs of the network. ICN provides a direct retrieval of content through its unique name, which is independent of locations. It also performs better in content retrieval with its in‐network caching and named‐based routing capabilities. Since vehicles are mobile devices, it is very crucial to select a caching node, which is secure and reliable. The security of data is quite important in the vehicular named data networking (VNDN) environment due to its vital importance in saving the life of drivers and pedestrians. To overcome the issue of security and reduce network load in addition to detect a malicious activity, we define a blockchain‐based distributive trust model to achieve security, trust, and privacy of the communicating entities in VNDN, named secure vehicle communication caching (SVC‐caching) mechanism for the placement of on‐demand data. The proposed trust management mechanism is decentralized in nature, which is used to select a trustworthy node for cluster‐based V2V communications in the VNDN environment. The SVC‐caching strategy is simulated in the NS‐2 simulator. The results are evaluated based on one‐hop count, delivery ratio, cache hit ratio, and malicious node detection. The results demonstrate that the proposed technique improves the performance based on the selected parameters.

Impact factor as an indicator of efficiency or sustainability is entirely correlated with the continuous development of the smart city concept technology application. Intelligent transportation systems (ITSs) and particularly autonomous vehicles are expected to play an important role in this challenging environment. Fast and secure connections will be pivotal in order to achieve this new vehicular communications’ application era. The use of millimeter-wave (mmWave) frequency range is the most promising approach to allow these real-time, high-demand applications that require higher bandwidth with the minimum possible latency. However, an in-depth mmWave-channel characterization of the environment is required for a proper mmWave-based solution deployment. In this work, a complete radio wave propagation channel characterization for a mmWave smart parking solution deployment in a complex outdoor environment was assessed at a 28 GHz frequency band. The considered scenario is a parking lot placed in an open free university campus area surrounded by inhomogeneous vegetation. The vehicle and vegetation density within the scenario, in terms of inherent transceivers density and communication impairments, leads to overall system operation challenges, given by multiple communication links operation at line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. By means of an in-house developed 3D ray launching (3D-RL) algorithm, the impact of variable vegetation density is addressed, providing precise modelling estimations of large-scale multipath propagation effects in terms of received power levels and path loss. The obtained results along with the proposed simulation methodology can aid in an adequate characterization of an mmWave communication channel for new vehicular communications networks, applications, and deployments, considering the outdoor conditions as well as the impact of different vegetation densities, for current as well as for future wireless technologies.

Vehicular Named Data Networking (VNDN) is a network architecture that supports various content-oriented applications in high-dynamic topology environments. Its inherent in-network caching helps with content delivery and communication efficiency in vehicular networks. Due to the variability in vehicle mobility, the change of relay nodes makes data packet transmission difficult. Additionally, frequent link interruptions and packet retransmissions lead to increased network load and reduced quality of service for users. To address these issues, this paper proposes a novel vehicle clustering-based cooperative caching strategy. The strategy first utilizes Recurrent Neural Networks (RNN) to predict vehicle connectivity and clusters vehicles into different groups based on these predictions. Concurrently, we construct a popularity prediction model based on the multi-head attention mechanism to forecast content trends. Furthermore, we introduce the concept of importance levels, allowing nodes of different levels to cache content of corresponding popularity levels. Performance evaluation results show that the proposed scheme outperforms existing strategies in terms of cache hit rate, latency, and link load.

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

In order to improve cache hit efficiency and reduce network response delay in Vehicular Named Data Networking (VNDN) environment, a routing strategy based on content type awareness and a collaborative content pre-caching strategy based on content popularity prediction for probabilistic caching were proposed. Firstly, an appropriate route-forwarding strategy is selected according to the message characteristics and whether the destination node is known. Then, unsupervised learning topic model Latent Dirichlet Allocation (LDA) is used to dynamically predict the request preference of vehicle users. Secondly, the topological relationship between different devices in the Internet of vehicles and the predicted vehicle user preferences are used to accurately and effectively predict the popularity of content, so as to reduce the redundancy of content files cached by network devices and maximize the cache hit ratio. Simulation results show that compared with other content caching strategies, this content pre-caching strategy can effectively improve cache performance.

Mobility support in vehicular named-data networking

The Internet protocol (IP) can potentially become the universal network-layer protocol over all wireless systems as it already is for wireline packet networks. Such an all-IP wireless and wireline network can bring the proven advantages of IP networking to mobile users. However, realizing an all-IP wireless network introduces many challenges, among which is soft handoff. Two major problems need to be solved in order to support soft handoff. First, multiple streams of the same IP traffic have to be distributed via multiple base stations to a mobile station. Second, pieces of data arriving at the mobile station at the same time from different base stations need to be copies of the same data in order for the mobile station's radio system to correctly combine these different pieces into a single copy. A similar problem also needs to be resolved in the reverse direction from mobile stations to base stations. Solving these problems in a distributed all-IP wireless network remains a challenge. Although solutions exist for today's circuit-switched wireless systems. This article presents a new approach for soft handoff in distributed all-IP wireless networks. It consists of two main parts. First, a new design of IP-based distributed base stations enables mobile stations in multiple cells to be on the same IP subnet and multiple streams of the same data to be distributed via multiple base stations to a mobile without broadcasting/multicasting and with minimal signaling. Second, a novel IP-layer procedure performed by the base stations ensures that the data coming simultaneously from multiple base stations to a mobile station are copies of the same data.

Device-to-device (D2D) caching network is proposed to cope with the explosively growing traffic of next-generation mobile networks. Given the limited mobile users' (MU) caching capacity, it is significant to decide which contents and how much proportion of each content should be cached. Based on the selfish nature and varied content preference of MUs, we propose a mobility aware caching incentive scheme, in which base stations (BS) reward MUs for sharing contents with others through D2D communication. By solving the problem of maximizing MU utility and minimizing BS cost at the same time, we obtain each MU's caching strategy and optimal unit reward provided by BS with adapted gradient projection algorithm. Comparisons are deliberated with several baseline caching schemes without incentive, in order to measure the performance of the proposed scheme. Simulation results show that under our settings, BS serving cost can be reduced by up to 45.6% when the optimal reward is selected compared with the fair caching scheme, the advantage is more obvious when MUs' mobility speed gets higher. Furthermore, the proposed scheme outperforms greedy caching, fair caching and random caching scheme in terms of MU utility under different distributions of content popularity.

Pricing is an effective approach for spectrum access control in cognitive radio (CR) networks. In this paper, we study the pricing effect on the equilibrium behaviors of selfish secondary users' (SUs') data packets which are served by a CR base station (BS). From the SUs' point of view, a spectrum access decision on whether to join the queue of the BS or not is characterized through an individual optimal strategy that is joining the queue with a joining probability. This strategy also requires each SU to know the average queueing delay, which is a non-trivial problem. Toward this end, we provide queueing delay analysis by using the M/G/1 queue with breakdown. From the BS's point of view, we consider a duopoly market based on the two paradigms: the opportunistic dynamic spectrum access (O-DSA) and the mixed O-DSA & dedicated dynamic spectrum access (D-DSA). In the first paradigm, two co-located opportunistic-spectrum BSs utilize freely spectrum-holes to serve SUs. Then, we show the advantages of the cooperative scenario due to the unique solution that can be obtained in a distributed manner by using the dual decomposition algorithms. For the second paradigm, there are one opportunistic-spectrum BS and one dedicated-spectrum BS. We study a price competition between two BSs as a Stackelberg game. The cooperative behavior between two BSs is modeled as a bargaining game. In both paradigms, bargain revenues of the cooperation are always higher than those due to competition in both cases. Extensive numerical analysis is used to validate our derivation.

Proactively pushing content to users has emerged as a promising approach to improve the spectrum usage in off-peak times for fifth-generation mobile networks. However, owing to the uncertainty of future user demands, base stations (BSs) may not receive payments for the pushed files. To motivate content pushing, providing economic incentives to BSs becomes essential. Based on request delay information (RDI) that characterizes the users' request time for content files, this paper studies the profit maximization for a BS and a spectrum provider (SP) by developing a Stackelberg game. Specifically, the SP sets different selling prices of bandwidth for pushing and on-demand services, while the BS responds with the optimal quantity to purchase. In the game with non-causal RDI, a sub-gradient algorithm is presented to achieve a Stackelberg equilibrium (SE). For the game with statistical RDI, a closed-form expression is derived for an SE in the single-user scenario and a simulated annealing-based algorithm is designed to obtain an SE in the multi-user scenario. It is shown that the proposed games achieve greater profit for both the SP and the BS, compared with the on-demand scheme. Furthermore, pricing with statistical RDI attains performance closely approaching that with non-causal RDI, while being more practical.

Unmanned Aerial Vehicles, popularly known as UAVs, have been used in many applications, from healthcare services to military assignments with diverse capabilities such as data transmission, cellular service provisioning, and computational offloading tasks. UAV's have been recently used to provide Security as a Service (SaaS). SaaS involves technical solutions like anti-virus and anti-spam software, firewalls, using secure operating systems, etc. UAV's are resource-constrained devices, and thus they are connected to the base station (BS) so that they may avail the computational facilities of the BS. The UAV's connect themselves to the base station using cluster heads (intermediary devices). At times several UAVs cooperatively come together to serve a given region and such a group of UAVs is called a swarm of UAVs. In real-world scenarios, many stakeholders come together to form UAV swarm configuration proving services to users. Each stakeholder wants to maximize his gains. In this work, we propose a pricing Stackelberg game among UAVs, Cluster heads, and BS by formulating their behavioral utilities. Using particle swarm optimization on each entity's utility functions, we create an optimal price strategy for each entity to maximize their profit.

In the paper, the distributed joint spectrum sharing and power allocation scheme is proposed to improve the local services in the Device-to-Device (D2D) communication underlaying cellular networks (CNs) with limited signaling overhead. The scheme aims to optimize the throughput of D2D communications over the shared uplink frequency spectrum meanwhile the base station (BS) protects the cellular users (CUs) from the interference of D2D users. Stackelberg game (SG) is formulated to model the problem for deriving the distributed scheme. In the game, the BS, as a leader, coordinates the interference from the D2D users to the cellular uplinks and maximizes its own profit by pricing the interference. On the other hand, D2D pairs, as followers, compete for the spectrum as a Nash non-cooperative game to maximize their own data rates individually. The pricing mechanism at the BS converging to the Stackelberg Equilibrium is studied. Finally, numerical examples are presented to verify the proposed scheme. It is shown that the scheme is effective on the resource allocation and the CU protection with limited signaling overhead.