Learning automata: an introduction
Learning automata: an introduction
IEEE/ACM Transactions on Networking (TON)
Scheduling data broadcast in asymmetric communication environments
Wireless Networks
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Adaptive Data Broadcast in Hybrid Networks
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Broadcast Scheduling for Information Distribution
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Wireless Networks
Propagation measurements and models for wireless communications channels
IEEE Communications Magazine
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With the increasing popularity of wireless networks and mobile computing, data broadcasting has emerged as an efficient way of delivering data to mobile clients having a high degree of commonality in their demand patterns. This paper proposes a push system that continuously adapts to the demand pattern of the client population in order to reflect the overall popularity of each data item. The adaptation is accomplished using a simple feedback from the clients. We propose that the simple feedback is sent only from clients whose distance from the server does not incur a significant timing overhead for the acknowledgment of an item. Simulation results are presented which reveal satisfactory performance in high-speed environments with a priori unknown and dynamic client demands.