Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> With the rapid advances in vehicular technologies and social multimedia applications, VSNs have emerged and gained significant attention from both industry and academia. However, due to the low communication ability between vehicles, heavy network traffic load, and limited storage capacity, VSNs face the challenge to improve the performance of content delivery to provide a pleasant and safe driving experience. Therefore, in this article, first we present a novel framework to deliver content in VSNs with D2D communication. In the proposed framework, moving vehicles can exchange content directly with each other according to D2D communication. All contents are managed in a content-centric mode, where moving vehicles can send their interests to obtain content with naming information, resulting in a reduction of network traffic load. Based on the D2D communication, parked vehicles around the street can form vehicular social communities with the moving vehicles passing along the road, where the storage capacity of VSNs can be increased by using the contents in parked vehicles. Then we present the detailed process of content delivery in VSNs including interest sending, content distribution, and content replacement. Finally, experiment results prove the efficiency of the proposal. <s> BIB001 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Heterogeneous vehicular networks (HetVNETs), which applies the heterogenous access technologies (e.g., cellular and WiFi) complementarily to provide seamless and ubiquitous connections to vehicles, have emerged as a promising and more practical paradigm to enable vehicular service applications on the road. However, with different access technologies presenting different costs in terms of download latency and bandwidth cost, how to optimize the connection along the vehicle's trip towards the lowest cost represents fundamental challenges. This paper investigates the issue by proposing an optimal access control scheme for vehicles in HetVNETs. In specific, with different access links, we first model the cost of each vehicle to download its content by jointly considering the conventional vehicle to vehicle (V2V) communication and the available access links. A coalition formation game is then introduced to formulate the cooperation among vehicles based on different interests (content cached in vehicles) and requests (content needs to download). After forming the coalition, vehicles in the same coalition can download their requested content by selecting the optimal access link to achieve the minimum cost. Simulation results demonstrate that the proposed game approach can lead to the optimal strategy for vehicles and reduce the cost. <s> BIB002 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Recently, parked vehicles have been shown to be useful to deliver content in vehicular ad hoc networks, where the parked vehicles can form social communities to share and exchange content with other moving vehicles and road side units (RSUs). However, as it takes resource such as bandwidth and power for parked vehicles and RSUs to deliver content, the incentive scheme with the optimal pricing strategy needs to be studied. Furthermore, because multiple places including RSUs and parked vehicles can deliver content to moving vehicles, the optimal algorithm to determine where to obtain the requested content should also be discussed. Therefore, in this paper, we first propose a framework of content delivery with parked vehicles, where moving vehicles can obtain content from both the RSU and parked vehicles according to the competition and cooperation among them. Then, based on a Stackelberg game, we develop a pricing model where each of the three players, including moving vehicles, RSU, and parked vehicles, can obtain their maximum utilities. Next, a gradient based iteration algorithm is presented to obtain the Stackelberg equilibrium. Finally, the simulation results prove that the proposal can outperform other conventional methods and that each player in the game can obtain its optimal strategy during the content delivery. <s> BIB003 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> With the rapid advances in vehicular technologies and the ever-increasing demands on mobile multimedia services, vehicular networks play a crucial role in intelligent transport systems by providing resilient connection among vehicles and users. Meanwhile, a huge number of parked vehicles may have abundant and underutilized resources in forms of computation, communication and storage. In this paper, we propose a vehicular edge computing (VEC) caching scheme in which content providers (CPs) collaboratively cache popular contents in the storage of parked vehicles located in multiple parking lots. The proposed VEC caching scheme extends the data center capability from the core to the edge of the networks. As a result, the duplicate transmissions from remote servers can be removed and the total transmission latency can be significantly reduced. In order to minimize the average latency to mobile users, we present a content placement algorithm based on an iterative ascending price auction. Numerical results show that the proposed caching scheme achieves a performance gain up to 24% in terms of average latency, compared to the widely-used scheme with most popularity caching. <s> BIB004 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> By leveraging the 5G enabled vehicular ad hoc network (5G-VANET), it is widely recognized that connected vehicles have the potentials to improve road safety, transportation intelligence and provide in-vehicle entertainment experience. However, many enabling applications in 5G-VANET rely on the efficient content sharing among mobile vehicles, which is a very challenging issue due to the extremely large data volume, rapid topology change, and unbalanced traffic. In this paper, we investigate content prefetching and distribution in 5G-VANET. We first introduce an edge computing based hierarchical architecture for efficient distribution of large-volume vehicular data. We then propose a multi-place multi-factor prefetching scheme to meet the rapid topology change and unbalanced traffic. The content requests of vehicles can be served by neighbors, which can improve the sharing efficiency and alleviate the burden of networks. Furthermore, we use a graph theory based approach to solve the content distribution by transforming it into a maximum weighted independent set problem. Finally, the proposed scheme is evaluated with a greedy transmission strategy to demonstrate its efficiency. <s> BIB005 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Automated driving is coming with enormous potential for safer, more convenient, and more efficient transportation systems. Besides onboard sensing, autonomous vehicles can also access various cloud services such as high definition maps and dynamic path planning through cellular networks to precisely understand the real-time driving environments. However, these automated driving services, which have large content volume, are time-varying, location-dependent, and delay-constrained. Therefore, cellular networks will face the challenge of meeting this extreme performance demand. To cope with the challenge, by leveraging the emerging mobile edge computing technique, in this article, we first propose a two-level edge computing architecture for automated driving services in order to make full use of the intelligence at the wireless edge (i.e., base stations and autonomous vehicles) for coordinated content delivery. We then investigate the research challenges of wireless edge caching and vehicular content sharing. Finally, we propose potential solutions to these challenges and evaluate them using real and synthetic traces. Simulation results demonstrate that the proposed solutions can significantly reduce the backhaul and wireless bottlenecks of cellular networks while ensuring the quality of automated driving services. <s> BIB006 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> The smart vehicles construct Vehicle of Internet which can execute various intelligent services. Although the computation capability of the vehicle is limited, multi-type of edge computing nodes provide heterogeneous resources for vehicular services.When offloading the complicated service to the vehicular edge computing node, the decision should consider numerous factors.The offloading decision work mostly formulate the decision to a resource scheduling problem with single or multiple objective function and some constraints, and explore customized heuristics algorithms. However, offloading multiple data dependency tasks in a service is a difficult decision, as an optimal solution must understand the resource requirement, the access network, the user mobility, and importantly the data dependency. Inspired by recent advances in machine learning, we propose a knowledge driven (KD) service offloading decision framework for Vehicle of Internet, which provides the optimal policy directly from the environment. We formulate the offloading decision of multi-task in a service as a long-term planning problem, and explores the recent deep reinforcement learning to obtain the optimal solution. It considers the future data dependency of the following tasks when making decision for a current task from the learned offloading knowledge. Moreover, the framework supports the pre-training at the powerful edge computing node and continually online learning when the vehicular service is executed, so that it can adapt the environment changes and learns policy that are sensible in hindsight. The simulation results show that KD service offloading decision converges quickly, adapts to different conditions, and outperforms the greedy offloading decision algorithm. <s> BIB007 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Technological evolutions in the automobile industry, especially the development of connected and autonomous vehicles, have granted vehicles more computing, storage, and sensing resources. The necessity of efficient utilization of these resources leads to the vision of vehicular cloud computing (VCC), which can offload the computing tasks from the edge or remote cloud to enhance the overall efficiency. In this paper, we study the problem of computation offloading through the vehicular cloud (VC), where computing missions from edge cloud can be offloaded and executed cooperatively by vehicles in VC. Specifically, computing missions are further divided into computing tasks with interdependency and executed in different vehicles in the VC to minimize the overall response time. To characterize the instability of computing resources resulting from the high vehicular mobility, a mobility model focusing on vehicular dwell time is utilized. Considering the heterogeneity of vehicular computing capabilities and the interdependency of computing tasks, we formulate an optimization problem for task scheduling, which is NP-hard. For low complexity, a modified genetic algorithm based scheduling scheme is designed where integer coding is used rather than binary coding, and relatives are defined and employed to avoid infeasible solutions. In addition, a task load based stability analysis of the VCC system is presented for the cases where some vehicles within the VC are offline. Numerical results demonstrate that the proposed scheme can significantly improve the utilization of computing resources while guaranteeing low latency and system stability. <s> BIB008 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Vehicular content networks (VCNs), which distribute medium-volume contents to vehicles in a fully distributed manner, represent the key enabling technology of vehicular infotainment applications. In VCNs, the road-side units (RSUs) cache replicas of contents on the edge of networks to facilitate the timely content delivery to driving-through vehicles when requested. However, due to the limited storage at RSUs and soaring content size for distribution, RSUs can only selectively cache content replicas. The edge caching scheme in RSUs, therefore, becomes a fundamental issue in VCNs. This paper addresses the issue by developing an edge caching scheme in RSUs. Specifically, we first analyze the features of vehicular content requests based on the content access pattern, vehicle's velocity, and road traffic density. A model is then proposed to determine whether and where to obtain the replica of content when the moving vehicle requests it. After this, a cross-entropy-based dynamic content caching scheme is proposed accordingly to cache the contents at the edge of VCNs based on the requests of vehicles and the cooperation among RSUs. Finally, the performance of the proposed scheme is evaluated by extensive simulation experiments. <s> BIB009 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Content dissemination, in particular, small-volume localized content dissemination, represents a killer application in vehicular networks, such as advertising distribution and road traffic alerts. The dissemination of contents in vehicular networks typically relies on the roadside infrastructure and moving vehicles to relay and propagate contents. Due to instinct challenges posed by the features of vehicles (mobility, selfishness, and routes) and limited communication ability of infrastructures, to efficiently motivate vehicles to join in the content dissemination process and appropriately select the relay vehicles to satisfy different transmission requirements is a challenging task. This paper develops a novel edge-computing-based content dissemination framework to address the issue, composed of two phases. In the first phase, the contents are uploaded to an edge computing device (ECD), which is an edge caching and communication infrastructure deployed by the content provider. By jointly considering the selfishness and the transmission capability of vehicles, a two-stage relay selection algorithm is designed to help the ECD selectively deliver the content through vehicle-to-infrastructure (V2I) communications to satisfy its requirements. In the second phase, the vehicles selected by the ECD relay the content to the vehicles that are interested in the content during the trip to destinations via vehicle-to-vehicle (V2V) communications, where the efficiency of content delivery is analyzed according to the probability that vehicles encounter on the path. Using extensive simulations, we show that our framework disseminates contents to vehicles more efficiently and brings more payoffs to the content provider than the conventional methods. <s> BIB010 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> The heterogeneous vehicular networks (HetVNETs), which apply the heterogeneous access technologies ( e.g. , cellular networks and WiFi) complementarily to provide seamless and ubiquitous connections to vehicles, have emerged as a promising and practical paradigm to enable vehicular service applications on the road. However, with different costs in terms of latency time and price, how to optimize the connection along the vehicle’s trip toward the lowest cost represents fundamental challenges. This paper investigates the issue by proposing an optimal access control scheme for vehicles in HetVNETs. In specific, with different access networks, we first model the cost of each vehicle to download the requested content by jointly considering the vehicle’s requirements of the requested content and the features of the available access networks, including conventional vehicle to vehicle communication and the heterogeneous access technologies. A coalition formation game is then introduced to formulate the cooperation among vehicles based on their different interests (contents cached in vehicles) and requests (contents to be downloaded). After forming the coalitions, vehicles in the same coalition can download their requested contents cooperatively by selecting the optimal access network to achieve the minimum costs. The simulation results demonstrate that the proposed game approach can lead to the optimal strategy for the vehicle. <s> BIB011 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Sharing perceptual data with other vehicles enhances the traffic safety of autonomous vehicles because it helps vehicles locate other vehicles and pedestrians in their blind spots. Such safety applications require high throughput and short delay, which cannot be achieved by conventional microwave vehicular communication systems. Therefore, millimeter-wave (mmWave) communications are considered to be a key technology for sharing perceptual data because of their wide bandwidth. One of the challenges of data sharing in mmWave communications is broadcasting because narrow-beam directional antennas are used to obtain high gain. Because many vehicles should share their perceptual data to others within a short time frame in order to enlarge the areas that can be perceived based on shared perceptual data, an efficient scheduling for concurrent transmission that improves spatial reuse is required for perceptual data sharing. This paper proposes a data sharing algorithm that employs a graph-based concurrent transmission scheduling. The proposed algorithm realizes concurrent transmission to improve spatial reuse by designing a rule that is utilized to determine if the two pairs of transmitters and receivers interfere with each other by considering the radio propagation characteristics of narrow-beam antennas. A prioritization method that considers the geographical information in perceptual data is also designed to enlarge perceivable areas in situations where data sharing time is limited and not all data can be shared. Simulation results demonstrate that the proposed algorithm doubles the area of the cooperatively perceivable region compared with a conventional algorithm that does not consider mmWave communications because the proposed algorithm achieves high-throughput transmission by improving spatial reuse. The prioritization also enlarges the perceivable region by a maximum of 20%. <s> BIB012 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> The drastically increasing volume and the growing trend on the types of data have brought in the possibility of realizing advanced applications such as enhanced driving safety, and have enriched existing vehicular services through data sharing among vehicles and data analysis. Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i.e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources. However, road side units that primarily presume the role of vehicular edge computing servers cannot be fully trusted, which may lead to serious security and privacy challenges for such integrated platforms despite their promising potential and benefits. We exploit consortium blockchain and smart contract technologies to achieve secure data storage and sharing in vehicular edge networks. These technologies efficiently prevent data sharing without authorization. In addition, we propose a reputation-based data sharing scheme to ensure high-quality data sharing among vehicles. A three-weight subjective logic model is utilized for precisely managing reputation of the vehicles. Numerical results based on a real dataset show that our schemes achieve reasonable efficiency and high-level of security for data sharing in VECONs. <s> BIB013 </s> Computation Offloading and Content Caching Delivery in Vehicular Edge Computing: A Survey <s> B. Heterogenous Edge Nodes <s> Mobile edge computing (MEC) has been recently proposed to bring computing capabilities closer to mobile endpoints, with the aim of providing low latency and real-time access to network information via applications and services. Several attempts have been made to integrate MEC in intelligent transportation systems (ITS), including new architectures, communication frameworks, deployment strategies and applications. In this paper, we explore existing architecture proposals for integrating MEC in vehicular environments, which would allow the evolution of the next generation ITS in smart cities. Moreover, we classify the desired applications into four major categories. We rely on a MEC architecture with three layers to propose a data dissemination protocol, which can be utilized by traffic safety and travel convenience applications in vehicular networks. Furthermore, we provide a simulation-based prototype to evaluate the performance of our protocol. Simulation results show that our proposed protocol can significantly improve the performance of data dissemination in terms of data delivery, communication overhead and delay. In addition, we highlight challenges and open issues to integrate MEC in vehicular networking environments for further research. <s> BIB014
Heterogeneous cache involves several kinds of edge nodes that cooperatively store and disseminate the contents to the vehicles. Cooperative data caching and delivery among a variety of edge nodes are essential in the heterogeneous cache. We review the optimisation of such caching based on game theory BIB010 , BIB002 , BIB011 , BIB001 , BIB003 , graph theory BIB005 , BIB006 , BIB012 , BIB007 , network-based technologies and miscellaneous. 1) Game Theory: In general, auction game BIB010 , BIB004 , coalition formation game BIB002 , BIB011 , Stackelberg game BIB001 , BIB003 were exploited to optimise the cost of data caching and dissemination  or jointly optimised with the transmission capabilities BIB010 , BIB002 , BIB011 . A novel auction game model jointly considered the content dissemination requirements of an edge computing device (ECD) with regards to the transmission capability of vehicles and prices BIB010 . A distributed twostage relay selection algorithm was formulated for the ECD to select the optimal vehicle bids with the lowest cost in relaying the content to other vehicles using the first-price sealed-bidauction. However, the study does not consider the content deadline. In contrast, leveraging the idle storage of parked vehicles in multiple parking areas, an iterative ascending price auction-based caching algorithm was presented BIB004 . The resource blocks of parked vehicles were assigned to the highest bid, which was the difference between the valuation of caching and the cost paid. The process of auction might cause some delay for a high dense vehicular networks. Another work considered the cooperation among vehicles with regards to content interests (content cached in vehicles) and content requests (content needs to download) were formulated based on a coalition formation game BIB002 , BIB011 . The selection of optimal access link was subject to the minimum cost of the content downloading time and the content price BIB002 , BIB011 . Aforementioned game-based approaches achieved the optimal strategy for each vehicle with a minimal cost BIB002 , BIB011 , and yielded higher revenue to the ECDs BIB010 than the conventional schemes. Adopting the content-centric framework  , a pricing model based on a Stackelberg game was developed for the delivery of the contents competitively from RSU or parked vehicles and cooperatively from both to the moving vehicles BIB003 . The cost was computed based on the computational task on a unit size of the resource (e.g., content). The proposed gradient-based iteration algorithm decreased the prices of RSU and parking area with the increasing transmission rate until the Nash Equilibrium was achieved. However, the work has a high algorithm complexity and the content deadline is not adddressed. 2) Graph Theory: Generally, the graph theory connects the vehicles and the edge nodes for content placement and delivery, whereby the vertices and edges can be distinguished for each proposed mechanism. The construction of the graph was assumed at the base station BIB005 , BIB006 , RSU BIB012 and edge server BIB007 . A cooperative sharing of a large volume of vehicular data from both OBUs and RSUs was developed using an undirected neighbour graph based scheduling scheme called Balanced MWIS (BMWIS) that transformed the content distribiution problem into a MWIS problem BIB005 . The results demonstrated that the proposed BMWIS achieved the lowest average delay and a high number of served nodes for each scheduling periods. A two-level edge computing architecture was presented BIB006 whereby a contact graph was constructed for the content placement and solved using a tree-based heuristic method. Meanwhile, the approximation method was used to address the conflict graph for a cooperative content sharing between vehicles. Another technique based on periodic location reports from vehicles where the edge server constructed a contact graph representing the links between the vehicles for a content placement solution BIB007 . A vehicle with a substantial gain that was proportional to the urgency of the content had a priority of broadcasting on the time slot. The implementation of graph theory-based caching might have a shortcoming of additional processing at the BS or RSU. Despite that, mmWave data sharing algorithms for V2V communications based on graph theory scheduling is proposed in BIB012 . A vertex weighting function represented the priority of each transmission whereby a high priority transmission was assigned to the farthest vehicle from the intersection, and a low priority was given to data near the intersection, i.e., max distance scheduling. It is because the high vehicle density around the intersection is overlapped. The work is beneficial in solving the interference between beams using an approximation method called a conflict rule to improve spatial reuse, but the research might face redundant data at the intersection. With the weight parameter, the results demonstrated that the data could be shared at a large geographical area. 3) Network-based Protocols and Technologies: In general, data caching and dissemination for vehicular networks can also be solved using content-centric networking BIB001 ,  , blockchain BIB013 , and network message protocols BIB014 . The use of parked vehicles for delivering the contents over VSNs based on D2D communication is highlighted BIB001 . With CCN, the vehicles only request the name of the required content from the parked vehicles without additional overhead and the process of content interest sending, content distribution, and content replacement is detailed in BIB001 . The proposed technique considerably achieved a high number of successful content transmission and the shortest download delay, but required a high algorithm complexity. Another similar work employed a group of the content-centric unit (CCU) to work with vehicles and RSUs in the proposed Content-Centric Vehicular Networks framework  . The CCU can serve one or multiple RSUs, and even one RSU can be attached to several CCUs. The priority for the contents storage is subject to the request time, the arrival rate of vehicles, and the request content distribution, i.e., Zipf, which is likely can cause high overheads for the information. However, referring to the information the lowest priority of content can be appropriately removed. A replica of required content in a selective nearby CCU was delivered to vehicle via RSU. Following the recent blockchain technology, Figure 9 shows a secure data storage and sharing using blockchain in VEC BIB013 . Smart contracts on the vehicular blockchain were proposed for a secure RSU data, and a reputation-based data sharing among vehicles called a three-weight subjective logic model for selecting the most reliable data source. The vehicle coin, which is a specific crypto-currency for vehicular edge computing and networks, is rewarded as incentives to the edge nodes in three kinds of cases: resource storage contribution, new data block update, and data providers. A local controller as seen in the figure records the total amount of contributed data storage of edgde nodes. The edge nodes (i.e., RSUs) as data aggregators periodically integrates raw data received into a data block, and requests verification from other edge nodes by broadcasting the data block. Nevertheless, the proposed blockchain-based method will be more pervasive if QoS is taken into consideration, as in BIB014 . Exploring a different mechanism, an edge-based data dissemination protocol was developed for traffic safety messages from RSUs to vehicles, and the protocol was integrated with a route request (RREQ) message and a route reply (RREP) message for delay-tolerant applications BIB014 . The farthest vehicles were scheduled on the earliest timeslot for the minimal delay, similar to BIB012 . If the vehicle received a duplicate of the messages, the message broadcasting was then terminated to minimise the overheads. 4) Miscellaneous: Another optimisation problem was formulated to minimise the average completion time and solved using a modified genetic algorithm based joint scheduling where integer coding was used BIB008 . The edge cloud sent a service request to the BS, which was aware of vehicular channel conditions, and hence the BS transmitted the request to the vehicle for data processing. However, a poor performance was observed for the case of high mobility cooperation. Another caching solution introduced the utility function to maximise the hit ratio using a cross-entropy based dynamic content caching algorithm BIB009 . The requested vehicles can fetch the content from several candidates, which are other moving vehicles, RSU, or the remote content server accordingly with regards that the average delay is well-kept. With the consideration of content popularity, content size, and also content cache capacity of the vehicle and RSU, the proposed technique achieved the highest hit ratio, the lowest relative delay, and overhead. Another work on a cost-effective resource sharing under a mixed integer nonlinear programming optimization problem was developed to minimise the cost of video service provider's in IoV  . The target user received the video prior to the VSP optimally retrieved the video either from the moving vehicle or cloud. An incentive mechanism was Fig. 9 : Secure data storage and sharing using blockchain in VEC BIB013 introduced to encourage the vehicle sharing its contents with the BS. With a massive number of vehicles on the road, a multihop vehicle-to-vehicle connection can be performed instead of multihop backhaul relay. Apart from that,  demonstrated that the VSP's cost was exponentially decreasing with the vehicle user's speed between 50 to 120 km/h. This is because the low speed VUs can sufficiently fetch the data from other vehicles within the delay constraint while the fast vehicle has a limited BS streaming process. However, both works in BIB009 ,  have a drawback in terms of high algorithm complexity and computation.