Browsing by Subject "Pull-based"

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    An efficient broadcast scheduling algorithm for pull-based mobile environments
    (2000) Karakaya, K. Murat
    Thanks to the advances in telecommunications and computers, today mobile computing becomes a significant means in every pace of life. Many people are now carrying portable devices such as laptop computers, Personal Digital Assistants (PDAs), and cellular phones. These mobile computing devices are supported by rapidly expanding telecommunication technology. Cellular communication, wireless LAN and WAN, and satellite services are available for daily life applications, and portable devices make use of these wireless connections to contact the information providers. Thus, a user does not need to maintain a fixed connection in the network and may enjoy almost unrestricted user mobility. As the new and various mobile infrastructures emerge, users demand a new class of applications running in this environment. However, the narrow bandwidth of the wireless communication channels, the relatively short active life of the power supplies of mobile units, and the mobility of clients make the problem of data retrieval more difficult than that in wired networks. Therefore, mechanisms to efficiently transmit information to vast numbers of mobile users are of significant interest. Data broadcasting has been considered one of the most promising ways of data dissemination in mobile environments. There are two basic data broadcasting approaches available: push and pull. In push-based broadcasting approach, data is broadcast to mobile users according to users' profiles or subscriptions, whereas in pull-based broadcasting approach, transmission of data is initiated by the explicit request of users. In this thesis, we have focused on the problem of scheduling data items to broadcast in a pull-based environment. We have developed an efficient broadcast scheduling algorithm, and comparing its performance against several well-known algorithms, we have observed that our algorithm appears to be one of the best algorithms proposed so far.