Balancing push and pull for data broadcast
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficient algorithms for scheduling data broadcast
Wireless Networks
Introduction to Algorithms
Object Organization on a Single Broadcast Channel in the Mobile Computing Environment
Multimedia Tools and Applications
Data Allocation on Wireless Broadcast Channels for Efficient Query Processing
IEEE Transactions on Computers
Data on Air: Organization and Access
IEEE Transactions on Knowledge and Data Engineering
Query Processing in Broadcasted Spatial Index Trees
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Pushing dependent data in clients-providers-servers systems
Wireless Networks
Broadcasting and blocking large data sets with an index tree
Broadcasting and blocking large data sets with an index tree
On Exploring Channel Allocation in the Diverse Data Broadcasting Environment
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
TOSA: a near-optimal scheduling algorithm for multi-channel data broadcast
Proceedings of the 6th international conference on Mobile data management
A power-saving protocol for exact GkNN search in wireless broadcast environments
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
Effective protocols for kNN search on broadcast multi-dimensional index trees
Information Systems
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In wireless mobile environments, data broadcasting is an effective approach to disseminate information to mobile clients. In some applications, the access pattern of all the data can be represented by a weighted DAG. In this paper, we explore how to efficiently generate the broadcast schedule in a wireless environment for the data set having a weighted DAG access pattern. Such a broadcast schedule not only minimizes the access latency but also is a topological ordering of the DAG. Minimized access latency ensures the quality of service (QoS). We prove that it is NP-hard to find an optimal broadcast schedule and provide some heuristics. After giving an analysis for these heuristics on the latency and complexity, we implement all the proposed heuristics to compare their performance.