The rapid advance of wireless communication technologies and the increasing popularity of portable devices have resulted in a rise in demand for information by mobile users. Owing to this fact, different channel operators have started providing services to disseminate useful data and subscribers’ advertisements to mobile users. However, most existing indexing algorithms on multiple channels were designed for a homogeneous environment where it is relatively difficult for mobile users to fetch their expected data from the various data channels operated by different entities....[ Read more ]

The rapid advance of wireless communication technologies and the increasing popularity of portable devices have resulted in a rise in demand for information by mobile users. Owing to this fact, different channel operators have started providing services to disseminate useful data and subscribers’ advertisements to mobile users. However, most existing indexing algorithms on multiple channels were designed for a homogeneous environment where it is relatively difficult for mobile users to fetch their expected data from the various data channels operated by different entities.

In a heterogeneous multiple channel environment, locating the required data for mobile clients is a power- and time-consuming process. In this thesis, indexing methods are proposed in order to reduce the time and energy used to search for data in multiple data channels. In our environment, broadcast agents disseminate data through wireless data broadcast services provided by different channel operators. They are connected to a centralized index server through a wired network for broadcasting index information on the index channel. Basically, mobile clients read index information from the index channel and then look for the broadcast data by tuning into the channel according to the index information. Three indexing models are described in the thesis and simulation results are obtained to evaluate the performance of the three proposed methods.