Broadcast disks: data management for asymmetric communication environments
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Scheduling data broadcast in asymmetric communication environments
Wireless Networks
Handbook of wireless networks and mobile computing
The Architecture of Videotex Systems
The Architecture of Videotex Systems
Optimizing Index Allocation for Sequential Data Broadcasting in Wireless Mobile Computing
IEEE Transactions on Knowledge and Data Engineering
The Data Broadcast Problem with Preemption
STACS '00 Proceedings of the 17th Annual Symposium on Theoretical Aspects of Computer Science
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
TOSA: a near-optimal scheduling algorithm for multi-channel data broadcast
Proceedings of the 6th international conference on Mobile data management
Time-Critical On-Demand Data Broadcast: Algorithms, Analysis, and Performance Evaluation
IEEE Transactions on Parallel and Distributed Systems
Improved Approximation Algorithms for Broadcast Scheduling
SIAM Journal on Computing
Online Scheduling Sequential Objects with Periodicity for Dynamic Information Dissemination
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 5th international conference on Emerging networking experiments and technologies
A Novel Adaptive Framework for Wireless Push Systems Based on Distributed Learning Automata
Wireless Personal Communications: An International Journal
Towards realizable, low-cost broadcast systems for dynamic environments
IEEE/ACM Transactions on Networking (TON)
Clustering-driven wireless data broadcasting
IEEE Wireless Communications
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Periodic broadcast scheduling typically considers a set of discrete data items, characterized by their popularity, size and scheduling cost. A classic goal is the definition of an infinite, periodic schedule that yields minimum mean client serving time and minimum mean scheduling cost at the same time. This task has been proven to be NP-Hard and more recent works have discarded the scheduling cost attribute, focusing only on the minimization of the mean client serving time. In the context of the present work the scheduling cost is reinstated. An analysis-based scheduling technique is presented, which can practically minimize the mean client serving time and the mean scheduling cost concurrently. Comparison with related approaches yields superior performance in all test cases.