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Vehicles equipped with wireless communication technology, “Dedicated Short Range Communication” are a promising field for fuel optimization navigation applications. This paper presents a vehicle routing methodology modeled as a Petri Net (PN) for optimizing travel time and vehicle emission in a connected roadway network with minimal total traffic capacity to route vehicle in a dynamically changing traffic environment, and in an optimal and predictive manner. The novel unfolded PN model presented in this paper incorporates the essential features in Dynamic Programming (DP) to solve the stochastic traffic routing problem. The effectiveness of the proposed eco-friendly navigation methodology is validated by comparing the performance with conventional travel time based navigation methods.

The widespread deployment of inexpensive communications technology, computational resources in the networking infrastructure, and network-enabled end-devices pose an interesting problem: how does one locate a particular network service or a device out of millions of accessible services and devices? Traditionally, these services are accessed through well-known URLs or retrieved through search engines. However, these results tend to be very general and may not satisfy the requirements of the user. Moreover, the traditional model cannot react to the dynamic changes in service attributes and client parameters. As a solution, a secure directory tool that tracks services in the network and allows authenticated users to locate them through expressive queries can be used. This paper discusses the Next Generation Vehicle Network (NGVN), an architecture based on Java/Jini and Dynamic Discovery Service (DDS) technology.