Improving QoS in Internet of Vehicles Integrating Swarm Intelligence Guided Topology Adaptive Routing and Service Differentiated Flow Control

Internet of Vehicles (IoV) is an evolution of vehicular adhoc network with concepts of internet of things (IOT). Each vehicle in IOV is an intelligent object with various capabilities like sensors, computation, storage, control etc. Vehicles can connect to any other entity in the network using vario...

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Bibliographic Details
Published in:International journal of advanced computer science & applications 2023, Vol.14 (4)
Main Authors: Kayarga, Tanuja, S, Ananda Kumar
Format: Article
Language:English
Subjects:
Ad hoc networks
Adaptive control
Algorithms
Clustering
Congestion
Flow control
Heuristic methods
Internet of Things
Internet of Vehicles
Network latency
Network topologies
Particle swarm optimization
Quality of service architectures
Routing (telecommunications)
Swarm intelligence
Vehicles
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Summary:Internet of Vehicles (IoV) is an evolution of vehicular adhoc network with concepts of internet of things (IOT). Each vehicle in IOV is an intelligent object with various capabilities like sensors, computation, storage, control etc. Vehicles can connect to any other entity in the network using various services like DSRC, C2C-CC etc. Ensuring QoS for vehicle to everything (V2X) communication is a major challenge in IoV. This work applies an integration of hybrid metaheuristics guided routing and service differentiated flow control to ensure QoS in Internet of Vehicles. Clustering based network topology is adopted with clustering based on hybrid metaheuristics integrating particle swarm optimization with firefly algorithm. Over the established clusters routing decision is done using swarm intelligence. Packet flows in the network are service differentiated and flow control is done at cluster heads to reduce the congestion in the network. High congestion in routes is mitigated with back up path satisfying the QoS constraints. Due to optimization in clustering, routing and data forwarding process, the proposed solution is able to achieve higher QoS. Through simulation analysis, the proposed solution is able to achieve 2% higher packet delivery ratio and 9.67% lower end to end packet latency compared to existing works.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2023.0140448