Energy and Time Efficient Routing Protocols for High throughout VANET

Vehicular Ad-Hoc networks (VANETS) has received significant attention in current years, thanks to its distinctive characteristics, that square measure totally different from Mobile Ad-Hoc networks(MANETS), like speedy topology modification, frequent link failure, and high vehicle quality. The most disadvantage of VANETS system is that the network instability, that vintages to reduce the network potency. During this article we have a tendency to suggest two algorithms: CBLTRprotocol and IDVR protocol. The CBLTR protocol aims to extend the route stability and average throughput in a very biface phase situation. The Cluster Heads (CHs) square measure chosen supported most Life-Time (LT) among all vehicles that square measure set at intervals every cluster. The IDVR protocol aims to extend the route stability and average throughput, and to scale back end-to-end delay in a very grid topology. The electoral Intersection CH (ICH) receives a collection of CandidateShortest Routes (SCSR) closed to the required destination from the Software Outlined Network (SDN). The IDVR protocol picks the best route supported its destination location, present location, and the most of the minimum average output of SCSR. We have a tendency to used grappling traffic generator simulators and MATLAB to guage the performance of our proposed protocols. These protocols considerably trounce many protocols mentioned within the literature, in terms of the many parameters

A Novel Stable Clustering Approach Based On Gaussian Distribution And Relative Velocity In VANETs

Vehicles in Vehicular Ad-hoc Networks (VANETs) are characterized by their high dynamic mobility (velocity). Changing in VANET topology is happened frequently which caused continuous network communication failures. Clustering is one of the solutions applied to reduce the VANET topology changes. Stable clusters are required and Indispensable to control, improve and analyze VANET. In this paper, we introduce a new analytical VANET's clustering approach. This approach aims to enhance the network stability. The new proposed grouping process in this study depends on the vehicles velocities mean and standard deviation. The principle of the normal (Gaussian) distribution is utilized and emerged with the relative velocity to propose two clustering levels. The staying duration of vehicles in a cluster is also calculated and used as an indication. The first level represents a very high stabile cluster. To form this cluster, only the vehicles having velocities within the range of mean ± standard deviation, collected in one cluster (i.e. only 68% of the vehicles allowed to compose this cluster). The cluster head is selected from the vehicles having velocities close to the average cluster velocity. The second level is to create a stable cluster by grouping about 95% of the vehicles. Only the vehicles having velocities within the range of mean ± 2 standard deviation are collected in one cluster. This type of clustering is less stable than the first one. The analytical analysis shows that the stability and the staying duration of vehicles in the first clustering approach are better than their values in the second clustering approach