Various Routing Protocols of Vehicular Ad hoc Network: A Survey

A vehicular ad hoc network is a type of network divided by an area where car nodes can join or leave the network. Due to the flexibility of the network environment active contractual routes are used in the development of the route from the source to the destination. Various active and active protocols are updated in this paper. Active routing protocols are those that use current network information in the development of the route from the source to the destination. Active routing protocols are those that use the pre-defined network information in the route setting. Active route agreements use route tables in route development. In this review paper, a literature survey was conducted on VANET route protocols. It is analyzed that an effective route protocol offers higher performance compared to active router protocols. Keywords: VANET, Reactive, Proactive Routing

Investigating the Suitability of Different Routing Strategies In Specific VANET Application Class

Vehicular Adhoc Network (VANET), is an emerging technology that holds the opportunity to create potential applications that directly impact peoples' lives, traffic management, and infotainment services. Understanding VANET applications and the available routing protocols can help to infer the most suitable protocols that satisfy VANET application requirements. This paper develops a systematic classification methodology to classify VANET applications from a routing perspective, each application class has different network requirements which are laid down by VANET Projects conducted in different countries. Some of these requirements are related to the routing aspects and need to be satisfied by the selected routing strategies (proactive and reactive). The paper identifies routing strategies performance metrics related to each application class requirement, to efficiently guide the development of these routing strategies towards guaranteeing satisfactory performance for the applications under a wide variety of realistic VANET scenarios. It is also worth mentioning that minimum delay is a requirement needed by time and event-driven application classes. However, high reliability is a requirement needed by on-demand applications. The paper aims to provide a comparative study on the performance of routing strategies in different VANET application classes, to identify which routing strategies have better performance in specific VANET applications class. End-to-end delay is employed as a performance metric to evaluate the short delay requirement, while, the Routing Overhead (RO) is used to assess the reliability requirement. Simulation results showed that proactive routing protocol has a lower delay, which means that it is suitable for delay-sensitive applications such as time-driven and event-driven applications. The result also showed that the reactive routing protocol outperforms the proactive routing protocol in terms of RO, which means that reactive routing protocols can be nominated as proper routing strategies to satisfy the reliability requirement of the On-demand driven applications.

Proactive Routing Mechanism for Removing Far Sensor in Iot using A Design of B * Index

Background:: The concern with the IoT node is energy since nodes are depleted as their energy utilization is incrementally reduced with reduction in far off nodes. The nodes will consume energy when it senses the data, followed with the Computation, and further for transmission. Method:: We proposed the phases for Energy-saving at nodes by Enhanced Agglomerative Clustering, Dynamic Selection of Leader, disposal of faraway sensor, and B * tree cloud storage and retrieval. In a typical IoT system, the nodes are deployed in the environment initially. Nodes are clustered using Enhanced Agglomerative Clustering Algorithm. A far node elimination will be implemented for the nodes not in the cluster region. Results:: By eliminating the need for far-off sensors, we can reduce the energy used. This in turn can also improve the lifetime of sensors. When appropriate, sensitive data is moved from IoT devices and stored in the cloud. Conclusion:: This paper also proposes an approach to fetch the data from IoT by using the Query Predicate method. This research work proposes a unique choice of grouping by estimating the parameters as energy, separation, thickness and portability.

Deep Learning Based Proactive Multi-Objective Eco-Routing Strategies for Connected and Automated Vehicles

This study exploited the advancements in information and communication technology (ICT), connected and automated vehicles (CAVs), and sensing to develop proactive multi-objective eco-routing strategies for travel time and Greenhouse Gas (GHG) emissions reduction on urban road networks. For a robust application, several GHG costing approaches were examined. The predictive models for link level traffic and emission states were developed using the long short-term memory (LSTM) deep network with exogenous predictors. It was found that proactive routing strategies outperformed the reactive strategies regardless of the routing objective. Whether reactive or proactive, the multi-objective routing, with travel time and GHG minimization, outperformed the single objective routing strategies. Using a proactive multi-objective (travel time and GHG) routing strategy, we observed a reduction in average travel time (17%), average vehicle kilometer traveled (22%), total GHG (18%), and total nitrogen oxide (20%) when compared with the reactive single-objective (travel time).