Efficient Dissemination of Personalized Information Using Content

There has been a surge of interest in the delivery of personalized information to users (e.g. personalized stocks or travel information), particularly as mobile users with limited terminal device capabilities increasingly desire updated, targeted information in real time. When the number of information recipients is large and there is sufficient commonality in their interests, as is often the case, IP multicast is an efficient way of delivering the information. However, IP multicast services do not consider the structure and semantics of the information in the multicast process. We propose the use of Content-Based Multicast (CBM) where extra content filtering is performed at the interior nodes of the IP multicast tree; this will reduce network bandwidth usage and delivery delay, as well as the computation required at the sources and sinks. In this paper we evaluate the situations in which CBM is advantageous. The benefits of CBM depend critically upon how well filters are placed at interior nodes of the IP multicast tree, and the costs depend upon those introduced by filters themselves. Further, we consider the benefits of allowing the filters to be mobile so as to respond to user mobility or changes in user interests, and the corresponding costs of filter mobility. We consider two criteria: minimizing total network bandwidth utilization and minimizing mean information delivery delay. For each criterion we develop an optimal filter placement algorithm, as well as a heuristic that executes faster than the optimal algorithm. Finally, we evaluate all the algorithms by means of simulation experiments. Our results indicate that filters can be effective in substantially reducing bandwidth and delay. We also find filter mobility is worthwhile if there is sufficient locality in the interests of users, or there is marked large-scale user mobility. We conclude with suggestions for further work.