Evaluation of VANETs Routing Protocols for Data-Based Smart Health Monitoring in Intelligent Transportation Systems

Abstract

Vehicular Ad-hoc Network (VANET) is an essential part of futuristic Intelligent Transportation Systems. VANET can improve the overall traffic control system and reduce road accident deaths by providing remote health monitoring in hazardous conditions to outdoor patients. Nowadays, vehicles have become so intelligent that they can sense patient health data and transmit it to a nearby ambulance or hospital in emergency or road accident situations. Health professionals can provide appropriate treatment without wasting critical time in further testing. Developing an efficient and reliable routing solution is a significant research problem for VANET based health monitoring applications because of time-sensitives. Routing approaches to reduce the transmission delay for critical applications are based on topological, geographical, clustering, and flooding techniques. This article has evaluated and compared widely used topological and geographical routing protocols for data-based VANETs health monitoring applications. A comprehensive analysis is performed on Ad hoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance-Vector (DSDV), Optimized Link State Routing (OLSR), Greedy Perimeter Stateless Routing (GPSR), Greedy Perimeter Stateless Routing-Modified (GPSR-M), and Max duration-Minangle Greedy Perimeter Stateless Routing (MM-GPSR) protocols with different numbers of nodes, CBR connections, communication range and packet size on Network Simulator (NS-3.23) and Simulation of Urban Mobility (SUMO) platforms. Experimental results give useful knowledge in analyzing routing protocols for VANET's data-based smart health monitoring applications.