Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

Data Security Enhancement in 4G Vehicular Networks Based on Reinforcement Learning for Satellite Edge Computing

The vehicular network provides the dedicated short-range communication (DSRC) with IEEE 802.11p standard. The VANET model comprises of cellular vehicle-to-everything communication with wireless communication technology. Vehicular Edge Computing exhibits the promising technology to provide promising Intelligent Transport System Services. Smart application and urban computing. Satellite edge computing model is adopted in vehicular networks to provide services to the VANET communication for the management of computational resources for the end-users to provide access to low latency services for maximal execution of service. The satellite edge computing model implemented with the 4G vehicular communication network model subjected to data security issues. This paper presented a Route Computation Deep Learning Model (RCDL) to improve security in VANET communication with 4G technology. The RCDL model uses the route establishment model with the optimal route selection. The compute route is transmitted with the cryptographic scheme model for the selection of optimal route identified from the satellite edge computing model. The proposed RCDL scheme uses the deep learning-based reinforcement learning scheme for the attack prevention in the VANET environment employed with the 4G technology communication model. The simulation results expressed that proposed RCDL model achieves the higher PDR value of 98% which is ~6% higher than the existing model. The estimation of end-to-end delay is minimal for the RCDL scheme and improves the VANET communication

A Driving Path Based Opportunistic Routing in Vehicular Ad Hoc Network

Vehicular Ad Hoc Networks is a promising technologythat can widely apply to monitor the physical world in urban areas.Efficient data delivery is important in these networks and optimalroute selection is vital to improve this factor. Vehicular mobility isa reflection of human social activity and human trajectories show ahigh degree of temporal and spatial regularity. Therefore, vehiculardriving paths are predictable in a large extent. A new opportunisticrouting protocol (DPOR) is proposed in this study that uses drivingpath predictability and vehicular distribution in its route selectionprocedure. This protocol is composed of two phases: intersectionand next hop selection phases. A utility function is calculated toselect the next intersection and a new mechanism is also proposedfor the next hop selection phase. Simulation results show thatDPOR achieves high delivery ratio and low end-to-end delay in thenetwork

Network parameters impact on dynamic transmission power control in vehicular ad hoc networks

International audienceIn vehicular ad hoc networks, the dynamic change in transmission power is very effective to increase the throughput of the wireless vehicular network and decrease the delay of the message communication between vehicular nodes on the highway. Whenever an event occurs on the highway, the reliability of the communication in the vehicular network becomes so vital so that event created messages should reach to all the moving network nodes. It becomes necessary that there should be no interference from outside of the network and all the neighbor nodes should lie in the transmission range of the reference vehicular node. Transmission range is directly proportional to the transmission power the moving node. If the transmission power will be high, the interference increases that can cause higher delay in message reception at receiver end, hence the performance of the network decreased. In this paper, it is analyzed that how transmission power can be controlled by considering other different parameter of the network such as; density, distance between moving nodes, different types of messages dissemination with their priority, selection of an antenna also affects the transmission power. The dynamic control of transmission power in VANET serves also for the optimization of the resources where it needs, can be decreased and increased depending on the circumstances of the network. Different applications and events of different types also cause changes in transmission power to enhance the reachability. The analysis in this paper is comprised of density, distance with single hop and multi hop message broadcasting based dynamic transmission power control as well as antenna selection and applications based. Some summarized tables are produced according to the respective parameters of the vehicular network. At the end some valuable observations are made and discussed in detail

Persistent Localized Broadcasting in VANETs

We present a communication protocol, called LINGER, for persistent dissemination of delay-tolerant information to vehicular users, within a geographical area of interest. The goal of LINGER is to dispatch and confine information in localized areas of a mobile network with minimal protocol overhead and without requiring knowledge of the vehicles' routes or destinations. LINGER does not require roadside infrastructure support: it selects mobile nodes in a distributed, cooperative way and lets them act as "information bearers", providing uninterrupted information availability within a desired region. We analyze the performance of our dissemination mechanism through extensive simulations, in complex vehicular scenarios with realistic node mobility. The results demonstrate that LINGER represents a viable, appealing alternative to infrastructure-based solutions, as it can successfully drive the information toward a region of interest from a far away source and keep it local with negligible overhead. We show the effectiveness of such an approach in the support of localized broadcasting, in terms of both percentage of informed vehicles and information delivery delay, and we compare its performance to that of a dedicated, state-of-the-art protoco

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Design and analysis of a beacon-less routing protocol for large volume content dissemination in vehicular ad hoc networks

Largevolumecontentdisseminationispursuedbythegrowingnumberofhighquality applications for Vehicular Ad hoc NETworks(VANETs), e.g., the live road surveillance service and the video-based overtaking assistant service. For the highly dynamical vehicular network topology, beacon-less routing protocols have been proven to be efficient in achieving a balance between the system performance and the control overhead. However, to the authors’ best knowledge, the routing design for large volume content has not been well considered in the previous work, which will introduce new challenges, e.g., the enhanced connectivity requirement for a radio link. In this paper, a link Lifetime-aware Beacon-less Routing Protocol (LBRP) is designed for large volume content delivery in VANETs. Each vehicle makes the forwarding decision based on the message header information and its current state, including the speed and position information. A semi-Markov process analytical model is proposed to evaluate the expected delay in constructing one routing path for LBRP. Simulations show that the proposed LBRP scheme outperforms the traditional dissemination protocols in providing a low end-to-end delay. The analytical model is shown to exhibit a good match on the delay estimation with Monte Carlo simulations, as well