Fuzzy Logic Decision Making by Localization and Recursive Algorithm in Vehicular AdHoc Network

315–317Vehicular AdHoc Networks are the most prominent and efficient technology nowadays. It achieves a high gain by using intelligent transportation systems due to their advanced version. Generally, all vehicle users expect low traffic jams and high degree of safety and security during their travel. It can be achieved by technique called Prediction Based Authentication. We present a fuzzy logic based decision making process by localization and recursion algorithm. It satisfies all the above user expectations like availability of alternative path when the travel route is busy and time minimization with low packet loss. In this algorithm we use two metrics namely position and distance metric for the purpose of easy data transmission. In this approach we do not generate any keys for transmitting the data packets. It will be done by using binary values. By creating adversary nodes the information can easily be transmitted to the neighbour nodes so that data loss can be minimized. Here, the system can operate in both online and off line modes

Fuzzy Logic Decision Making by Localization and Recursive Algorithm in Vehicular AdHoc Network

Vehicular AdHoc Networks are the most prominent and efficient technology nowadays. It achieves a high gain by using intelligent transportation systems due to their advanced version. Generally, all vehicle users expect low traffic jams and high degree of safety and security during their travel. It can be achieved by technique called Prediction Based Authentication. We present a fuzzy logic based decision making process by localization and recursion algorithm. It satisfies all the above user expectations like availability of alternative path when the travel route is busy and time minimization with low packet loss. In this algorithm we use two metrics namely position and distance metric for the purpose of easy data transmission. In this approach we do not generate any keys for transmitting the data packets. It will be done by using binary values. By creating adversary nodes the information can easily be transmitted to the neighbour nodes so that data loss can be minimized. Here, the system can operate in both online and off line modes

Fuzzy-Based Hybrid Location Algorithm for Vehicle Position in VANETs via Fuzzy Kalman Filtering Approach

Location information is very critical to VANETs such as navigation, routing, network management, and road congestion. In this paper, the vehicle location problem under urban road conditions is investigated by employing the GPS, WiFi, and Cellular Network (CN) positioning systems and by developing neighbor vehicle utilization in VANETs. Since GPS is possibly affected by satellite signal in real urban environment, while WiFi is only suitable for urban and CN is affected by the number of Base Stations (BSs) and signal strength, then a fuzzy-based hybrid location algorithm is developed. The algorithm has some advantages that it can enhance these positioning features by establishing a new fuzzy-weighting location mechanism (FLM) and also can adjust dynamically the measurement noise covariance by making use of a novel fuzzy Kalman filtering method. Finally, experiment results are given to show effectiveness and merit of the proposed approach