Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Ad Hoc Wireless Networks: Protocols and Systems
Ad Hoc Wireless Networks: Protocols and Systems
Ad-hoc On-Demand Distance Vector Routing
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
MALLBA: a software library to design efficient optimisation algorithms
International Journal of Innovative Computing and Applications
Using particle swam optimization for QoS in ad-hoc multicast
Engineering Applications of Artificial Intelligence
Ant-based topology convergence algorithms for resource management in VANETs
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Swarm intelligence for traffic light scheduling: Application to real urban areas
Engineering Applications of Artificial Intelligence
Green OLSR in VANETs with differential evolution
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
| Hi-index | 0.00 |
Communication protocol tuning can yield significant gains in energy efficiency, resource requirements, and the overall network performance, all of which is of particular importance in vehicular ad-hoc networks (VANETs). In this kind of networks, the lack of a predefined infrastructure as well as the high level of dynamism usually provoke problems such as the congestion of intermediate nodes, the appearance of jitters, and the disconnection of links. Therefore, it is crucial to make an optimal configuration of the routing protocols previously to the network deployment. In this work, we address the optimal automatic parameter tuning of a well-known routing protocol: Ad Hoc On Demand Distance Vector (AODV). For this task, we have used and compared five optimization techniques: PSO, DE, GA, ES, and SA. For our tests, a urban VANET scenario has been defined by following realistic mobility and data flow models. The experiments reveal that the produced configurations of AODV significantly improve their performance over using default parameters, as well as compared against other well-known routing protocols. Additionally, we found that PSO outperforms all the compared algorithms in efficiency and accuracy.