Novel Optimized Routing Scheme for VANETs

HSDN‐GRA: A hybrid software‐defined networking‐based geographic routing protocol with multi‐agent approach

“…The agent of MA‐DSDV has a knowledge base and four components: an agent identifier, a program agent to act autonomously, a memory agent that contains all the variables, and a routing table agent. They recently proposed in Harrabi, Jaffar et al 23 to combine the multi‐agent system approach and the Particle Swarm Optimization (PSO) algorithm named PSO‐C‐MA‐DSDV for a selective destination routing protocol by clustering the nodes according to the interest or context information of the vehicles as described in Harrabi et al 32 . They applied the PSO algorithm with a set of positions and velocities as particles.…”

“…In this section, based on experimental results with JADE platform and MATLAB tool, the performances of HSDN‐GRA against MA‐DSDV and PSO‐C‐MA‐DSDV 23 approaches are exposed and analyzed. The choice of these protocols is motivated by their similarity to HSDN‐GRA.…”

“…The DSDV routing protocol 3 uses a routing table which follows the change in the network thanks to the periodic messages exchanged inside the network. MA‐DSDV 23 is an improvement of DSDV that uses the intelligence of agents in order to exploit and to share the information required by the protocol only on the perception area. Consequently, MA‐DSDV acts as HSDN‐GRA which builds path on the neighboring first.…”

“…Consequently, MA‐DSDV acts as HSDN‐GRA which builds path on the neighboring first. A comparison with PSO‐C‐MA‐DSDV 23 is carried out because data are forwarded over set of clusters too.…”

“…Furthermore, a new system modeling part is presented in this extended version, with different static and dynamic Unified Modeling Language (UML) diagrams that describe the structure and the behaviors of the entities in the IoV environment. In the current paper, we obtain new comparative results of HSDN‐GRA against more suitable routing protocols such as the Multi‐Agent Destination‐Sequenced Distance Vector (MA‐DSDV) 22 and the Particle Swarm Optimization Cluster MA‐DSDV (PSO‐C‐MA‐DSDV) 23 protocols, according to two case studies. First, the performance of the protocols when the number of vehicles increases is analyzed while the second case deals with the impact of vehicle's speed.…”