Enhancement in Quality of Routing Service Using Metaheuristic PSO Algorithm in VANET Networks

Vehicular ad hoc Networks (VANETs) can be designed in a way to organize road protection with no specific need for any fixed infrastructure. Accordingly, the movement of all vehicles can be planned according to perceived information, and Quality of Services Routing (QoSR) algorithms can be pressured according to its available options, paths, and links, and according to the criteria and reliability of the QoSR. Ensure that QoSR is aware of the environment of the network of vehicles, including location of vehicles, direction, and speed. This study is to reduce the effects of unpredictable problems on the best pathway to replace the broken path/link. A QoSR with Particle Swarm Optimization (QoSR-PSO) is used in this article for improving QoSs in vehicular ad hoc networks. By modeling the behavior of a group of particles, particle swarm optimization algorithms find the best possible solution to the problem. In order to perform simulation experiments, NS2 simulator and VanetMobisim have been used. The comparison results with benchmark studies show the improvement in packet delivery rate (PDR), delay, Packet Drop, and overload.

[1]  Norsheila Fisal,et al.  Network coding techniques for VANET advertising applications , 2015, EURASIP J. Wirel. Commun. Netw..

[2]  Yujun Kuang,et al.  VANET Cluster-on-Demand Minimum Spanning Tree (MST) Prim clustering algorithm , 2013, 2013 International Conference on Computational Problem-Solving (ICCP).

[3]  Marco Roccetti,et al.  An Intervehicular Communication Architecture for Safety and Entertainment , 2010, IEEE Transactions on Intelligent Transportation Systems.

[4]  Amir Javadpour An Optimize-Aware Target Tracking Method Combining MAC Layer and Active Nodes in Wireless Sensor Networks , 2019, Wirel. Pers. Commun..

[5]  Mahmood Fathy,et al.  Improving QoS in VANET Using MPLS , 2012, ANT/MobiWIS.

[6]  Jeff Edmonds,et al.  ResVMAC: A Novel Medium Access Control Protocol for Vehicular Ad hoc Networks , 2017, ANT/SEIT.

[7]  Tao Peng,et al.  Combing Fuzzy Clustering and PSO Algorithms to Optimize Energy Consumption in WSN Networks , 2018, 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

[8]  Khushboo Gupta,et al.  Performance evaluation of topology based routing protocols for VANETs in urban scenarios , 2012 .

[9]  Izhak Rubin,et al.  Investigating VANET dissemination protocols performance under high throughput conditions , 2015, Veh. Commun..

[10]  Weihua Zhuang,et al.  Stochastic Modeling of Single-Hop Cluster Stability in Vehicular Ad Hoc Networks , 2016, IEEE Transactions on Vehicular Technology.

[11]  Muhammad Sohail,et al.  3VSR: Three Valued Secure Routing for Vehicular Ad Hoc Networks using Sensing Logic in Adversarial Environment , 2018, Sensors.

[12]  Sinem Coleri Ergen,et al.  Multihop-Cluster-Based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination , 2016, IEEE Transactions on Vehicular Technology.

[13]  Liu Wei,et al.  Cooperative spectrum allocation with QoS support in cognitive cooperative vehicular ad hoc networks , 2014, China Communications.

[14]  Mohamed K. Watfa,et al.  Advances in Vehicular Ad-Hoc Networks: Developments and Challenges , 2010 .

[15]  Amir Javadpour,et al.  Providing a Way to Create Balance Between Reliability and Delays in SDN Networks by Using the Appropriate Placement of Controllers , 2019, Wireless Personal Communications.

[16]  Grzegorz Wolny,et al.  Modified DMAC Clustering Algorithm for VANETs , 2008, 2008 Third International Conference on Systems and Networks Communications.

[17]  Sijing Zhang,et al.  Vehicular ad hoc networks (VANETs): Current state, challenges, potentials and way forward , 2014, 2014 20th International Conference on Automation and Computing.

[18]  Neda Moghim,et al.  An opportunistic routing based on symmetrical traffic distribution in vehicular networks , 2015, Comput. Electr. Eng..

[19]  Riri Fitri Sari,et al.  Performance evaluation of PUMA routing protocol for Manhattan mobility model on vehicular ad-hoc network , 2015, 2015 22nd International Conference on Telecommunications (ICT).

[20]  Tao Luo,et al.  Cooperative spectrum allocation with QoS support in cognitive cooperative vehicular ad hoc networks , 2014 .

[21]  Celimuge Wu,et al.  Data Dissemination with Dynamic Backbone Selection in Vehicular Ad Hoc Networks , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).

[22]  Guojun Wang,et al.  Power Curtailment in Cloud Environment Utilising Load Balancing Machine Allocation , 2018, 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI).

[23]  Arun Kumar Sangaiah,et al.  Energy-Aware Geographic Routing for Real-Time Workforce Monitoring in Industrial Informatics , 2021, IEEE Internet of Things Journal.

[24]  Liren Zhang,et al.  A Novel Cluster-Based Protocol for Topology Discovery in Vehicular Ad Hoc Network , 2012, ANT/MobiWIS.

[25]  Susana Sargento,et al.  Improving VANET protocols via network science , 2012, 2012 IEEE Vehicular Networking Conference (VNC).

[26]  Guojun Wang,et al.  Resource Management in a Peer to Peer Cloud Network for IoT , 2020, Wireless Personal Communications.

[27]  Qi Shi,et al.  Situation-Aware QoS Routing Algorithm for Vehicular Ad hoc Networks , 2022 .

[28]  Shahrokh Valaee,et al.  Vehicular ad hoc networks: architectures, research issues, methodologies, challenges, and trends , 2015, AdHocNets 2015.

[29]  Amir Javadpour,et al.  LBPSGORA: Create Load Balancing with Particle Swarm Genetic Optimization Algorithm to Improve Resource Allocation and Energy Consumption in Clouds Networks , 2021 .