Nearby Roadside Units Research Articles

Coalition Formation Game Based Information-Energy Collaboration in Vehicle Edge Computing Networks

In vehicle edge computing network (VECN), a key issue for the roadside unit (RSU) is how to handle computationally intensive tasks timely and use energy efficiently. When an RSU cannot finish the task on time, computation offloading will be an effective approach. However, when offloading tasks most RSUs neglect the energy supply and do not consider computation requirement and energy supply jointly. In this paper, we consider a VECN where there are multiple RSUs. When an RSU has a computational task with latency constraint, it will offload the task to the nearby RSUs and/or cloud servers, and purchase electricity from the neighbors and/or power grid if it is also short of power. To conserve energy and reduce cost, not only the collaboration between the VECN and the cloud/grid, but also the collaboration of RSUs within the VECN is investigated. Specifically, we first formulate the information-energy collaboration problem, and study how the strategies of computation offloading and energy sharing interact with each other, where the RSU's individual revenue is considered. Next, since the problem is a mixed nonlinear programming problem that is hard to be solved, we reformulate it into a double-level coalition formation game, based on which an algorithm with low complexity is proposed. Finally, we prove theoretically that through finite iterations, the game-based algorithm can converge to a stable Nash equilibrium which is the solution to the original problem. Simulation results show that our scheme is superior to the existing ones in reducing edge network expenses while improving individual revenue.

Efficient and Secure Certificateless Signcryption Without Pairing for Edge Computing-Based Internet of Vehicles

The emergence of the vehicular ad-hoc network (VANETs) could meet the need for an efficient and safe transportation. Vehicles wirelessly interact with nearby road-side units (RSUs) and send the data to the cloud servers (CS), but this approach has limitations (i.e. network congestion and privacy leakage). Edge computing can effectively solve problems of network congestion, feedback delay and privacy leakage during transmission caused by CS. Thus, this paper proposes a certificateless aggregate signcryption with online/offline encryption (CLOASC) based on edge computing (EDC). Correspondingly, certificateless signcryption (CLSC), online/offline encryption (OOE) and aggregate signcryption technology solve the key escrow problem, shorten the encryption time and realize the quick verification of multiple users, respectively. Furthermore, it is worth mentioning that the scheme we propose does not have any bilinear pairings or scalar multiplications in the online encryption stage, which greatly reduces the computational cost in the online stage. In the random oracle model, our scheme was proved to be existential unforgeability under adaptive chosen message attacks (EUF-ACM) and adaptive indistinguishability under chosen-ciphertext attack (IND-CCA2) security. Simulation results show that our scheme is computationally and communication based lightweight as compared to the related.

Energy-Delay Minimization of Task Migration Based on Game Theory in MEC-Assisted Vehicular Networks

Roadside units (RSUs), which have strong computing capability and are close to vehicle nodes, have been widely used to process delay- and computation-intensive tasks of vehicle nodes. However, due to their high mobility, vehicles may drive out of the coverage of RSUs before receiving the task processing results. In this paper, we propose a mobile edge computing-assisted vehicular network, where vehicles can offload their tasks to a nearby vehicle via a vehicle-to-vehicle (V2V) link or a nearby RSU via a vehicle-to-infrastructure link. These tasks are also migrated by a V2V link or an infrastructure-to-infrastructure (I2I) link to avoid the scenario where the vehicles cannot receive the processed task from the RSUs. Considering mutual interference from the same link of offloading tasks and migrating tasks, we construct a vehicle offloading decision-based game to minimize the computation overhead. We prove that the game can always achieve Nash equilibrium and convergence by exploiting the finite improvement property. We then propose a task migration (TM) algorithm that includes three task-processing methods and two task-migration methods. Based on the TM algorithm, computation overhead minimization offloading (COMO) algorithm is presented. Extensive simulation results show that the proposed TM and COMO algorithms reduce the computation overhead and increase the success rate of task processing.

Blockchain and deep learning based trust management for Internet of Vehicles

Internet of Vehicles (IoVs) works as the most advanced component of Intelligent Transportation Systems (ITSs). In IoVs, vehicles are able to communicate with nearby vehicles or RoadSide Units (RSUs). Traffic safety and efficiency can be provided by collecting and uploading real-time traffic information through vehicles, as well as broadcasting information by RSUs. However, there may be malicious vehicles in the network uploading false information, which will lead to serious traffic problems. To alleviate this problem, a trust management system based on blockchain technology is proposed in this paper. In this system, vehicles in the network firstly collect information about their surroundings and then upload valid information to nearby RSUs. To prevent malicious vehicles from uploading false messages, this paper designs a deep learning based verification model to calculate the trustworthiness of uploaded messages, and to further obtain the credibility scores of vehicles using the calculated results, and detect malicious vehicles accordingly. Moreover, a public blockchain framework is proposed and a Proof-Of-Trust (POT) consensus algorithm is designed. Vehicles are motivated to report true and valid information, and are penalized for uploading false data under this framework. Simulation results show that this mechanism can effectively detect malicious vehicles and motivate unfamiliar vehicles to upload true and reliable information to achieve trust management in the open and dynamic vehicular network environments.

Joint offloading strategy based on quantum particle swarm optimization for MEC-enabled vehicular networks

With the development of the mobile communication technology, a wide variety of envisioned intelligent transportation systems have emerged and put forward more stringent requirements for vehicular communications. Most of computation-intensive and power-hungry applications result in a large amount of energy consumption and computation costs, which bring great challenges to the on-board system. It is necessary to exploit traffic offloading and scheduling in vehicular networks to ensure the Quality of Experience (QoE). In this paper, a joint offloading strategy based on quantum particle swarm optimization for the Mobile Edge Computing (MEC) enabled vehicular networks is presented. To minimize the delay cost and energy consumption, a task execution optimization model is formulated to assign the task to the available service nodes, which includes the service vehicles and the nearby Road Side Units (RSUs). For the task offloading process via Vehicle to Vehicle (V2V) communication, a vehicle selection algorithm is introduced to obtain an optimal offloading decision sequence. Next, an improved quantum particle swarm optimization algorithm for joint offloading is proposed to optimize the task delay and energy consumption. To maintain the diversity of the population, the crossover operator is introduced to exchange information among individuals. Besides, the crossover probability is defined to improve the search ability and convergence speed of the algorithm. Meanwhile, an adaptive shrinkage expansion factor is designed to improve the local search accuracy in the later iterations. Simulation results show that the proposed joint offloading strategy can effectively reduce the system overhead and the task completion delay under different system parameters.

Block-CLAP: Blockchain-Assisted Certificateless Key Agreement Protocol for Internet of Vehicles in Smart Transportation

In the Internet of Vehicles (IoV), numerous potential applications have come up with the use of the Internet of Things (IoT)-empowered smart devices. In IoV, vehicles, roads, street signs and traffic lights can accordingly adjust to changing conditions in order to assist drivers, and also to improve safety, ease congestion and pollution reduction. Since various entities in an IoV environment make communications over public channels, there are potential security threats. To deal with such serious threats, we design a new blockchain-assisted certificateless key agreement protocol for IoV in smart transportation context, called Block-CLAP. In Block-CLAP, through authentication key management, traffic-centric data reach to a cluster head (CH) and then to its nearby road-side unit (RSU) securely using the established secret keys. A cloud server (CS) then securely collects the information from its attached RSUs and create the transactions. Later, the transactions are formed into blocks by the CS in a Peer-to-Peer (P2P) cloud servers network, and the blocks are verified and added through voting-based consensus algorithm in the blockchain. The detailed security analysis through formal, informal and formal security verification, and comparative study show that Block-CLAP provides superior security and has low communication and computational overheads as compared with other existing competing authentication schemes in the IoV environment. Finally, the blockchain-based implementation of Block-CLAP has been performed to measure computational time needed for a varied number of transactions per block and also for a varied number of blocks mined in the blockchain.

BaaS: Broadcast as a service cross-layer learning-based approach in cloud assisted VANETs

Broadcasting plays a significant role for data dissemination in Vehicular Ad hoc Network (VANET). Many VANET services rely on broadcast communication mode to disseminate data packets over the network. However, due to high mobility of vehicles, it stills being a challenging task. In this paper, a BaaS (Broadcast as a Service ) broadcasting solution is proposed for VANET to disseminate the data efficiently to the vehicles in the network using cloud computing. Due to the limited storage and computing capacity of vehicles, all information about road traffic and the broadcasting protocol is both maintained and processed in the cloud. So, we introduce a new cloud assisted VANET (CAV) architecture organizing the different levels of communications between the VANET components and the cloud, as well as between the three cloud layers. The source vehicle broadcasts the message by requesting the best relay set from the nearby road side unit (RSU) which plays the role of intermediate to the cloud. To perform the message forwarding, the cloud provides cross layer services: infrastructure as a service for traffic data storage and relay set selection processing, and application layer service for communication with VANET entities. By integrating cloud services many broadcasting problems may be reduced such as the delay and link breakage.

Efficient RSU Selection Approaches for Load Balancing in Vehicular Ad Hoc Networks

Due to advances in wireless communication technologies, wireless transmissions gradually replace traditional wired data transmissions. In recent years, vehicles on the move can also enjoy the convenience of wireless communication technologies by assisting each other in message exchange and form an interconnecting network, namely Vehicular Ad Hoc Networks (VANETs). In a VANET, each vehicle is capable of communicating with nearby vehicles and accessing information provided by the network. There are two basic communication models in VANETs, V2V and V2I. Vehicles equipped with wireless transceiver can communicate with other vehicles (V2V) or roadside units (RSUs) (V2I). RSUs acting as gateways are entry points to the Internet for vehicles. Naturally, vehicles tend to choose nearby RSUs as serving gateways. However, due to uneven density distribution and high mobility nature of vehicles, load imbalance of RSUs can happen. In this paper, we study the RSU load-balancing problem and propose two solutions. In the first solution, the whole network is divided into sub-regions based on RSUs’ locations. A RSU provides Internet access for vehicles in its sub-region and the boundaries between sub-regions change dynamically to adopt to load migration. In the second solution, vehicles choose their serving RSUs distributedly by taking their future trajectories and RSUs’ loading information into considerations. From simulation results, the proposed methods can improve packet delivery ratio, packet delay, and load balance among RSUs.

Augmented Powell-Based Krill Herd Optimization for Roadside Unit Deployment in Vehicular Ad Hoc Networks

Abstract This article focuses on roadside unit (RSU) deployment based on the analysis of aggregation delay causes between the accident-occurring location and the nearby RSU. Information aggregation in vehicular ad hoc networks using RSU is one of the phenomenal concepts that look ahead in today’s recent advancements, since the consistency in aggregation and dissemination of data in a volatile network is high when compared with vehicle to vehicle communications. Deploying the RSU as appropriate in rural areas is cost-sensitive since the collection of information is not up to the mark when compared with urban regions. A mathematical model called Powell’s Method and a bioinspired algorithm, namely krill herd algorithm, have been hybridized and proposed in this research article for effective RSU deployment. The proposed algorithm has been tested under three different road maps, and the consistency of the algorithm has been evaluated under appropriate performance measures.

RVCloud: a routing protocol for vehicular ad hoc network in city environment using cloud computing

Routing in Vehicular Ad hoc Network (VANET) is a challenging task due to high mobility of vehicles. In this paper, a RVCloud routing protocol is proposed for VANET to send the data efficiently to the destination vehicle using cloud computing technology. In this protocol, vehicle beacon information is send to the cloud storage through the Road Side Unit (RSU). As vehicles have less storage and computing facility, the information of all the vehicles moving in the city is maintained by the cloud. Source vehicle sends the data to the destination by sending the data to the nearby RSU. After receiving the data, RSU sends a request to the cloud for an optimal RSU information, that takes minimum packet forwarding delay to send the data to the destination. Cloud provides location service by providing destination location and optimal RSU information. Then RSU sends the data to the optimal RSU using internet. By using the internet facility, packet forwarding delay and link disruption problem are reduced. Simulation results show that, RVCloud performs better than VehiCloud, P-GEDIR, GyTAR, A-STAR, and GSR routing protocols.

RoadGate: Mobility-Centric Roadside Units Deployment for Vehicular Networks

With the increase of the storage capacity, computing, and wireless networking of the vehicular embedded devices, the vehicular networks bring a potential to enable new applications for drivers and passengers in the vehicles. Due to the prohibitive cost of deployment and management of a roadside unit (RSU), it is difficult to cover roads with a large number of RSUs so that every vehicle can always keep a connection with the nearby RSU. In this paper, we study the problem of deploying the RSUs to provide the desired connectivity performance while minimizing the number of the deployed RSUs. The key idea of our solution is to exploit the time-stable mobility pattern to find the optimal deployment places. We analyze a realistic vehicle trace, observe the mobility pattern, and propose a graph model to characterize it. Based on the graph model, we transform the gateway deployment problem into a vertex selection problem in a graph. By reducing it into the minimum vertex coverage problem, we show that the RSU deployment problem is NP-complete. Then, a heuristic algorithm RoadGate is proposed to search greedily the optimal positions. Extensive simulations based on the synthetic and realistic scenarios are carried out to evaluate the performance. The results show that RoadGate outperforms other approaches in terms of the number of required RSUs and the actual achieved coverage performance.

We Can Deliver Messages to Far Vehicles

Vehicular ad hoc networks (VANETs) enable vehicles to communicate with each other but require efficient and robust routing protocols for their success. In this paper, we exploit the infrastructure of roadside units (RSUs) to efficiently and reliably route packets in VANETs. Our system operates by using vehicles to carry and forward messages from a source vehicle to a nearby RSU and, if needed, route these messages through the RSU network and, finally send them from an RSU to the destination vehicle. Our system is mostly critical for users who are far apart and want to communicate using their vehicles' onboard units. Many recent paradigms, like social networks, will greatly benefit from a system like ours to enable users on the road to exchange different types of data. We evaluate the performance of our system using the ns2 simulation platform and compare our scheme to existing solutions. The results prove the feasibility and efficiency of our scheme.

Design and Implementation of Certificate Revocation List Acquisition Method for Security of Vehicular Communications

Distributing a Certificate Revocation List (CRL) quickly to all vehicles in the system requires a very large number of road side units (RSUs) to be deployed. In reality, initial deployment stage of vehicle networks would be characterized by limited infrastructure as a result in very limited vehicle to infrastructure communication. However, every vehicle wants the most recent CRLs to protect itself from malicious users and malfunctioning equipments, as well as to increase the overall security of the vehicle networks. To address this challenge, we design and implement a nomadic device based CRL acquisition method using nomadic device’s communication capability with cellular networks. When a vehicle could not directly communicate with nearby RSUs, the nomadic device acts as a security mediator to perform vehicle’s security functions continuously through cellular networks. Therefore, even if RSUs are not deployed or sparsely deployed, vehicle’s security threats could be minimized by receiving the most recent CRLs in a reasonable time.