Parminder Singh

Vehicle ad hoc networks (VANETs) are small, local networks that could be joined by malicious users, opening the door to a variety of active and passive attacks. Vehicle ad hoc networks (VANETs) are small, local networks that could be joined by malicious users, opening the door to a variety of active and passive attacks.

Recently, extensive research has focused on the design of clustering algorithms for grouping vehicles in a set of clusters in Vehicular Ad Hoc Networks (VANETs). However, due to the dynamic nature of VANETS, frequently connected or detached nodes threaten the stability of the network. When these nodes are clustered heads (CHs), the impact of these disruptions on network performance is even worse. Therefore, the stability of clusters is an important issue that should be maintained to enhance the performance of the network with minimum data loss. In this article, a novel clustering approach is proposed, which is based on the average weight concept of three main attributes, namely, the geostationary coordinates (x, y) and drop density. The average of the above-mentioned attributes is calculated and compared with the values of other vehicles attributes. Those vehicles having minimum average values are dropped and not to be considered in the cluster formation. The cluster members having minimum Euclidean distance are considered as Cluster Head (CH) until a certain checkpoint is not attained. The checkpoints are created in order to generate the social score of the vehicles. Once the social score is attained, a multiobjective framework is developed, which considers minimizing the Euclidian distance and maximizing the social score. The social score is generated based on the Quality of Service (QoS) attained attributes, and the data transmission is performed using Ad Hoc On-Demand Distance Vector (ADOV) routing protocol. A comparison of the proposed work and existing work has also been undertaken to demonstrate the improvement in the proposed work. As a result, throughput, PDR, network longevity, and energy consumption have been improved by 28.27, 20.9, 23.12, and 27.48 percent, respectively. Extensive simulations show that the proposed scheme, unlike other popular clustering algorithms, can significantly increase the stability of the network by extending the life of the cluster head.

VANETs (vehicular ad hoc networks) have evolved as a platform for enabling intelligent inter-vehicle communication while also improving traffic safety and performance. VANETs are a difficult research topic because of the road dynamics, high mobility of cars, their unlimited power supply, and the growth of roadside wireless infrastructures. In wireless networks, game theory approaches have been widely used to investigate the interactions between competitive and cooperative behavior. In this research, we propose a technique for vehicular ad hoc networks that uses a game theory approach to automate vehicle grouping and cluster head nomination. This will eliminate the need for cluster reformation on a regular basis. Furthermore, each vehicle’s social behavior will be exploited to establish clusters in the vehicular environment. For the development of clusters on the social behavior of the cars, a machine learning approach (K-means algorithm) is applied. The proposed system is tested against a variety of characteristics, including CH life time, average cluster member life time, average number of reaffiliation times, throughput, and packet loss rate, and the results indicate that the VANET performed very well with high accuracy in validation and testing, and overall in the range of 0.97 to 0.99.

VANETs is the open model which stimulate in academia and industry oriented researches. However, the model is open and there are many violations in a communication of vehicle to vehicle (V2V) and Vehicle to Infrastructure (V2I). Any anonymous user may extract the useful information. Researchers have proposed many research proposal and solved issues related to VANET. The security is the major concern and to avoid mishappening in driving the vehicle. We proposed the authentication system that provides safety of the driver during travel on the roads. The proposed results deliver the following features: 1) Reliability of VANET model 2) Road Safety 3) Privacy of the vehicles 4) Authentication of message delivery to adjacent nodes. Finally, we provide a view point of how to detect the attacks and withdraw malicious node more efficiently.

The energy has undergone a major concern in wireless sensor networks. One direction of the LEACH protocol would be towards a future in which four levels will continue to dominate. The other direction would be towards to improve these levels further and increasingly smaller amount of energy consumption. The support provided by the LEACH protocol has been crucial in which upgrade these levels and build smart distributed network. The previous scenario is not motivated by the scientific altruism. They are large number of clients in the proposed scenario and therefore have a good reason to encourage a scalable alternative for communication. LEACH protocol to take a leaf out of the proposed scenario and it has a good energy saver, less energy consumption. The proposed scenario needs to be better understanding the catalytic role played by the previous three levels LEACH protocol. It should also see whether there is scope for deploying more nodes through collaboratively proposed protocol with three level protocols.

Vehicular ad hoc networks (VANETs) are the networks, which configured themselves, where the nodes are moving vehicles. These provide the communications required to deploy Intelligent Transportation Systems (ITS). A major dispute in VANETs is distribution of efficient and computable information because during communication nodes may leave or join the network dynamically. There is no guarantee about node availability at any given time, which leads to traffic problem, congestion problem. Therefore trailing the favorable path is a challengeable issue. Multiple routing algorithms have been developed for routing solution. In this paper the swarm-based algorithm has been presented, which helps to find out the optimal route using Bellman Ford algorithm. Ant colonization searches out the path using pheromones level. Higher the pheromone count of a route gives the optimal choice of path that can be used for packet delivery. Bellman Ford Algorithm optimizes the paths found by Ant Colony Optimization (ACO) by comparing the distance of source to all the nodes of network or cost given to the networks.

Wireless mesh networks, consisting of mesh routers and mesh clients are very robust, reliable and easily maintained networks. The current work is based on IEEE 802.11 standard amendment IEEE 802.11s specific for mesh topology based networks to improve the connectivity and coverage. It aims to control the shared medium access among the stations using Distributed Coordination Function (DCF) MAC protocol for reducing collisions and delays, thereby increasing throughput of the network.. The actual Binary Exponential Backoff (BEB) algorithm as implemented in IEEE 802.11 resets the contention window to its least value after an acknowledged transmission. From the previous works it has been observed that this sudden reset to minimum value of contention window does not ensure a reduction in collisions. It may lead to more contention in the network thereby increasing delays and affecting its throughput. The proposed work presents a Mean Backoff Algorithm in order to solve this flaw of BEB algorithm. The proposed algorithm aims to bring the contention window to some appropriate value in order to cope up with the unfairness caused due to its minimum value on successful transmission.