Volume 06 Issue 04, July 2018

Attacks, Routing Protocols and Security challenges in VANET

Roshi Mishra, Ratan Singh

Page no:01-08


Vehicular Ad hoc Networks are multichip networks with no fixed infrastructure in which the vehicles are communicate with each other (V to V) and vehicles are communicate with RSU (V to RSU) in dynamic environment. It consists of moving vehicles communicating with each other in different zones and continuously sharing traffic information for knowing traffic status. The responsibility of every vehicle is to forward the traffic status to requester vehicles. As same as MANET due to open medium security is always the major concern in VANET. The attacker vehicle/s is forward the large huge amount of unwanted messages to consume the network limited bandwidth or drops the data packets or traffic status packets. In this paper we proposed the IDS based V-RSU communication. RSU with IDS identified the attacker vehicles by that unusual interference in communication. The RSU collects the information from vehicles and forwarded to other vehicles or other RSU. The proposed IDS security algorithm is applied to RSU to recognize the attacker vehicle activities. The RSU after identified it block their functionality of communication. The proposed security scheme is identified the attacker vehicle and block their presence in network. The aim of this research is to providing security against malicious attack, to allow new proposed models to build their work on solid realistic models against packet dropping attack. In this proposed scheme, vehicles obtain traffic data when they pass by a road side unit (RSU) and then share the data after they travel out of the RSU’s coverage. A basic issue of proposed security scheme is how vehicles effectively work in presence of attacker. The simulation results are confirmed that RSU provides naught dropping of packets in presence attacker e.g. the indication of secure communication. The previous research work in security are provides the guidelines in field of security to protect network from different attacks. The packet dropping attack is dropping the all traffic information and also proposed scheme is block attacker existence and improvement network performance.

UAV Logistics Route Planning Based on Improved Adaptive Genetic Algorithm

Yuwen Pan, Zhan Wen, Wenzao Li

Page no:09-15


In intelligent logistics, parcel delivery is a big challenge for logistics companies. Using drones for parcel delivery is a very efficient method. Due to limited drone power and carrying capacity, it’s very hard to find best paths for fewer drones to cover all delivery points. In this paper, we use an improved adaptive genetic algorithm to design reasonable paths to solve this problem. So we can use the smallest number of drones and take the optimal route of short total distance and minimum total power consumption to cover all delivery points. However, for mutation probability influences the accuracy of the algorithm, the proper value of mutation probability of obtaining optimal route will be given according to experiments. The simulation results show that the planned drone routes are obviously better than the random routes. Furthermore, the number of drones required is also greatly reduced and optimal mutation probability can improve the accuracy of algorithm.

Improved Accuracy Using Advanced Location Algorithms in Ad hoc Networks

Sonkumar Verma, Prof. Dharmendra Kumar Singh

Page no:16-23


Wireless sensor networks (WSNs) have gained researchers' attention in the last several years. Small sensors powered by miniaturized microprocessors are capable of supporting several applications for civil and military domains. Determining the location of sensors is a basic and essential knowledge for most WSN algorithms and protocols including data tagging, routing, node identification, among others. This paper surveys the different algorithms that have been proposed to securely determine the location of a sensor node. By secure, we mean that adversaries cannot easily affect the accuracy of the localized sensors. In other words, the localization algorithm must be robust under several attacks. We provide taxonomy for classifying different secure localization schemes and describe possible attacks that can harm localization. In addition, we survey different secure localization schemes and show how they map to the proposed taxonomy. We also give a comparison between the different schemes, showing the attacks addressed by each.

Performance Analysis Using Different Dataset Based on K-means Clustering: Survey

Yogita Mishra, Prof. Vijay Bhandari, Dr. Amit Shrivastava

Page no:24-27


Clustering could be a very important task in methoding process. K-Means cluster could be a cluster methodology within which the given data set is split into K variety of clusters and information partitioning a group of objects into homogeneous clusters could be a basic operation in data processing. The operation is required in a very variety of information mining tasks. Cluster or information grouping is that the key technique of the information mining. It’s an unattended learning task wherever one seeks to identify a finite set of classes termed clusters to explain the information. The grouping of information into clusters relies on the principle of increasing the intra category similarity and minimizing the put down category similarity. The goal of cluster is to see the intrinsic grouping in an exceedingly set of unlabelled information. K-mean cluster is wide used to minimize square distance between options values of two points reside within the same cluster. Planned to use the Principal element Analysis methodology to reduce the information set from high dimensional to low dimensional. The new methodology is employed to search out the initial centroids to create the formula simpler and efficient. The planned methodology is simply implemented in matlab tool and is suitable for big information sets, like those in data processing applications. Experimental results show that, with a small loss of quality, the planned Method will significantly reduce the time taken than the standard kernel k-means cluster methodology. The planned Methodology is additionally compared with different recent similar methodology.

Enhanced Energy Aware in Mobile Ad hoc Network Using Localization Positioning Algorithm

Abhishek Kumar Upadhyay, Prof. Dharmendra Kumar Singh

Page no:28-32


They mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. Wireless sensor networks have recently gained a lot of attention by scientific community. Small and inexpensive devices with low energy consumption and limited computing resources are increasingly being adopted in different application scenarios including environmental monitoring, target tracking and biomedical health monitoring. In many such applications, node localization is inherently one of the system parameters. Localization process is necessary to report the origin of events, routing and to answer questions on the network coverage, assist group querying of sensors. In general, localization schemes are classified into two broad categories: range-based and range-free. However, it is difficult to classify hybrid solutions as range-based or range-free. In this paper we make these classification easy, where range-based schemes and range-free schemes are divided into two types: fully schemes and hybrid schemes. Moreover, we compare the most relevant localization algorithms and discuss the future research directions for wireless sensor networks localization schemes. In localization the problem that the positioning correctness and a few anchor nodes. Purposed algorithmic program for improvement approach and find the optimum location. Find the optimum location by satisfying every the factors with minimize error and good accuracy.