Improved Performance by Using k-means Clustering in Vehicular Ad Hoc Network
Klíčová slova:
VANET, RSU, OBU, TA, Trust, Clustering, SecurityAbstrakt
VANETs are formed by applying the principles of MANETs, in which all node, i.e., vehicles can pursue traffic law with high speed. VANETs support two types of communication: vehicle - to- vehicle (V2V) and vehicle to-infrastructure (V2I). Vehicles communicate to RSU for the exchange of keys for the security purpose and RSU communicate to Authentication Server (AS) for the formation of secret keys. But in existing work they perform nonsymmetric cryptography in which XOR operation is performed at authentication server which increases the size of key. In this paper we proposed a technique in which we form the cluster of vehicles then perform login for sending the data. Our results are shown in NS2 simulation which proves that the performance of network improves in terms of Throughput, Routing Overhead and Packet Delivery Ratio.Cite this ArticleNeha Jain, Krishna Kumar Joshi. Improved Performance by Using k-means Clustering in Vehicular Ad Hoc Network. Journal of Communication Engineering & Systems. 2017; 7(1): 17–24p.Publikováno
Číslo
Sekce
Licence
Declaration and Copyright Transfer Form
(to be completed by authors)
I/ We, the undersigned author(s) of the manuscript entitled ‘______________’, hereby declare, that the above manuscript which is submitted for publication in the Journal, is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.
I/ We have read the final version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship. We also agree to the authorship of the article in the following order:
Author’s name Signature (s)
1. ________________
2. ________________
3. ________________
4. ________________