Delay Minimization for Data Dissemination in Large-Scale VANETs with Buses and Taxis

Abstract

Minimizing the end-to-end delay for data dissemination in a large-scale VANET with both buses of fixed schedules and taxis of random schedules is a challenging issue, due to the scalability, high-mobility, and network heterogeneity concerns. Particularly, the mix of random taxis and fixed-scheduled buses makes the delay components along a path dependent and hard to estimate. In this paper, to address the scalability and high-mobility issues, we introduce a store-and-forward framework for VANETs with extra storage using “drop boxes”, which function similar to network routers. Next, we propose an optimal link strategy which is independent of the message arrival time and can be executed in a distributed manner. Then, we derive the expected path delay, considering the dependence of the delay components along the path, and propose the optimal routing strategy to minimize the expected path delay. Trace-driven simulations have been used to validate the rigorous analysis, and demonstrate the superior performance of the proposed strategies, which result in a substantial delay reduction and a much higher delivery ratio when compared with the state-of-the-art solutions without drop boxes. The strategies can further improve the delay performance when compared with the over-simplified routing solutions which ignore the dependence of the delay components.