ABSTRACT
Currently, intelligent vehicles and Intelligent Transportation Systems (ITS) are attracting a great deal of interest in research. Moreover, it is probable that in the next few years this interest will increase, because of its encouragement from instituitions of America and the European Union (through regulations) and the widespread adoption of vehicular communication systems, as well as the possibilities offered by this kind of networks: applications related to driving safety, entertainment, collection of data from the environment, social applications, etc. Ad-hoc vehicular networks (VANETs) have a special interest, since they operate using P2P (peer-to-peer) communications among their users, with no need for a centralized infrastructure, and thus can be deployed more easily and with less cost. Users that want to participate in the VANET would only have to install a small device in their cars and they will immediately join the network.
However, there are a number of issues that can slow down the adoption of such kind of networks. First, the potential high number of users will increase the number of wireless communications with the risk of saturating the available bandwidth, which has motivated the development of the so-called cognitive radio networks. Another difficulty, that is inherent to ad-hoc networks, is the transportation or routing of the data from one node (vehicle) to another in such a changing environment, where all the nodes are constantly moving and the connections among them last at most a few seconds. Finally, another key difficulty is how to design and develop applications that can benefit from the 200advantages provided by this kind of networks, since both their development and testing can be complex. Mobile agents are programs that have the capability to move their execution from one computer or device to another, and they are considered an interesting technology for VANETs. In this chapter, we present a simulation approach that we have developed, focused on the evaluation of data management strategies for vehicular networks that are based on the use of mobile agent technology.
