Dynamic leveling: Adaptive data broad- casting in a mobile computing environment

Abstract. The research issue of broadcasting has attracted a considerable amount of attention in a mobile computing system. By utilizing broadcast channels, a server is able to continuously and repeatedly broadcast data to mobile users. From these broadcast channels, mobile users obtain the data of interest efficiently and only need to wait for the required data to be present on the broadcast channel. Given the access frequencies of data items, one can design proper data allocation in the broadcast channels to reduce the average expected delay of data items. In practice, the data access frequencies may vary with time. We explore in this paper the problem of adjusting broadcast programs to effectively respond to the changes of data access frequencies, and develop an efficient algorithm DL to address this problem. Performance of algorithm DL is analyzed and a system simulator is developed to validate our results. Sensitivity analysis on several parameters, including the number of data items, the number of broadcast disks, and the variation of access frequencies, is conducted. It is shown by our results that the broadcast programs adjusted by algorithm DL are of very high quality and are in fact very close to the optimal ones