Scheduling and caching strategies for correlated data in push-based information systems

Abstract

Recently, there has been increasing interest in information systems that deliver data using broadcast in both wired and wireless environments. The strategy in which a server repeatedly broadcasts data to clients can result in a larger throughput, and various methods have been studied to reduce the average response time to data requests in such systems. In this paper, we propose a strategy for scheduling the broadcast program which takes into account the correlation among data items. This strategy puts data items with strong correlation side by side in the broadcast program in order to reduce the average response time. We also propose a caching strategy which extends a conventional caching strategy so that it can take advantage of correlation among broadcast data items for greater efficiency. Finally: we use simulation studies to evaluate the performance of our proposed strategies.

A Novel Adaptive Framework for Wireless Push Systems Based on Distributed Learning Automata

“…The simulation results presented in this section are obtained with the following values to the parameters: P = Table 1 summarizes the characteristics of the networks that have been simulated while Figs. 5,6,7,8,9,10,11,12,13,14 depict the simulation results of these networks. Figure 5 depicts the response time of network N 1 as the number of groups varies.…”

“…In push systems (e.g. [6][7][8]), the server is considered to have an a-priori estimation of the client demands and schedules its broadcasts according to these estimates of the demand per information item. On the contrary to the pull approach, the "pure" push systems provide high scalability and client hardware simplicity but are unable to operate efficiently in environments with a-priori unknown and dynamic client demands.…”

Data Delivery System with Convergence of Terrestrial Digital Broadcasting and Communication for Cellular Phone

“…Some relate to the hybrid data delivery with the function of broadcasting and bidirectional communication [5] [6], and others relate to the scheduling and caching strategies in the push-based data delivery [7][8] [9]. However, effective data delivery methods for the DTV standard for cellular phone have not discussed yet.…”

A novel HMM-based learning framework for improving dynamic wireless push system performance

“…Thus, the broadcast of one information item will probably satisfy a large number of clients that have the same demand at the same time period. Among other architectures (pull and hybrid approaches), the push systems [1][2][3] seem to be the most promising, since they achieve high scalability and low complexity. Their operation involves a server being located onto a base station, which makes a priori assumptions about the demand probability of the information items and schedules its broadcasts according to these assumptions without any participation of the client side.…”

“…Thus, the ''pure'' push systems [1][2][3] are unable to adapt to a priori unknown client demands. Other adaptive push systems use a learning automaton module, trying to adapt to environments with a priori unknown client demands [4].…”