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Anthocnet: A Swarm Intelligence based Routing Protocols Performance in Vanets


Affiliations
1 Electronics and Communication Engineering Department, Bhagat Phool Singh Mahila Vishwavidayala, Khanpur Kalan, Sonipat, Haryana, India
2 Punjab Engineering College, Chandigarh at Panjab University, Chandigarh, India
3 Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Sonipat, Haryana, India
     

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Intelligent Transportation Systems (ITS) has brought a new era of communication in last few years. The latest area which is being into focus is Vehicular Ad-hoc Networks (VANETs). The main target is to provide safe journey and reliability to the drivers eliminating the open challenges introduced by the VANETs. Different types of routing protocols to keep networking and communication among different vehicles while moving on the road has been introduced. The older one is the topology based routing protocols but it is not suitable for different and every type of scenarios in VANETs. To overcome few of the open challenges of VANETs, classic optimization techniques can be taken into consideration. These techniques can be formulated as unsolved optimization techniques but again at the cost of new challenges. These problems introduce novel models, limited computational resources and constrained network capabilities. To handle these issues, bio-inspired algorithms can be used. In this paper, different types of Natural computing methods are discussed in brief and how bio-inspired algorithms solve the open issues in VANETs are discussed in brief. This paper also focuses on the different swarm based routing protocols being used till date in VANETs along with a brief state-of-art of such protocols. One of the swarm based routing protocol AntHocNet, which is a hybrid routing protocol is also discussed in brief in the paper and its performance is compared with some classical routing protocols meant for VANETs is also discussed.

Keywords

VANET, AntHocNet, Swarm, ITS, Natural computing, NC, Routing protocols, Bio-inspired.
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  • Anthocnet: A Swarm Intelligence based Routing Protocols Performance in Vanets

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Authors

Ritu Sehgal
Electronics and Communication Engineering Department, Bhagat Phool Singh Mahila Vishwavidayala, Khanpur Kalan, Sonipat, Haryana, India
Vijay Nehra
Punjab Engineering College, Chandigarh at Panjab University, Chandigarh, India
Pawan Dahiya
Deenbandhu Chhotu Ram University of Science and Technology, Murthal, Sonipat, Haryana, India

Abstract


Intelligent Transportation Systems (ITS) has brought a new era of communication in last few years. The latest area which is being into focus is Vehicular Ad-hoc Networks (VANETs). The main target is to provide safe journey and reliability to the drivers eliminating the open challenges introduced by the VANETs. Different types of routing protocols to keep networking and communication among different vehicles while moving on the road has been introduced. The older one is the topology based routing protocols but it is not suitable for different and every type of scenarios in VANETs. To overcome few of the open challenges of VANETs, classic optimization techniques can be taken into consideration. These techniques can be formulated as unsolved optimization techniques but again at the cost of new challenges. These problems introduce novel models, limited computational resources and constrained network capabilities. To handle these issues, bio-inspired algorithms can be used. In this paper, different types of Natural computing methods are discussed in brief and how bio-inspired algorithms solve the open issues in VANETs are discussed in brief. This paper also focuses on the different swarm based routing protocols being used till date in VANETs along with a brief state-of-art of such protocols. One of the swarm based routing protocol AntHocNet, which is a hybrid routing protocol is also discussed in brief in the paper and its performance is compared with some classical routing protocols meant for VANETs is also discussed.

Keywords


VANET, AntHocNet, Swarm, ITS, Natural computing, NC, Routing protocols, Bio-inspired.