Optimizing the performance of vehicular delay tolerant networks using multi-objective PSO and artificial intelligence

摘要

Vehicular delay tolerant network (VDTN) technology uses vehicles on the road as moving nodes to deliver data from source to destination using several intermediate nodes. Efficient data dissemination in VDTN is a difficult problem due to existing trade-offs between several metric variables such as delivery ratio, delay, and overhead ratio. Inclusion of important social network parameters (like community, social strength, trust, friendship, and selfishness) in computation of forwarding probability may help to improve the performance of a routing algorithm. However, different tuning of these parameters results in different outcomes for the metric variables. A proper balancing of these parameters may result in an optimized outcome solving the trade-off between the metric variables. Nonetheless, dependency of the variables on a number of social network parameters and their mutual trade-offs makes this a non-trivial optimization problem. In this paper, we propose a novel approach to optimize these trade-offs using multi-objective particle swarm optimization (MOPSO). The proposed approach provides a set of pareto-optimal solutions also known as non-dominating solutions. Further, based on the requirements of a target application scenario, a specific optimal solution out of the pareto-optimal solution set is delivered using artificial intelligence (AI) technique. The proposed methodology is simulated in a VDTN scenario using the opportunistic network environment (ONE) simulator and Matlab. Furthermore, based on the experimental results, an exhaustive analysis is provided about how the metric variables are affected by the involvement of the social-based parameters. The capabilities of the proposed approach are validated using a statistical comparative analysis of the results. In future, the outcome of the study may play a helpful role to decide the priorities of the network parameters while designing new data dissemination algorithms for VDTN.