Energy efficient indexing on air
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Broadcast disks: data management for asymmetric communication environments
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Log-time algorithms for scheduling single and multiple channel data broadcast
MobiCom '97 Proceedings of the 3rd annual ACM/IEEE international conference on Mobile computing and networking
Minimizing service and operation costs of periodic scheduling
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
The data broadcast problem with non-uniform transmission times
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Polynomial-time approximation scheme for data broadcast
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Efficient Data Allocation over Multiple Channels at Broadcast Servers
IEEE Transactions on Computers
Multi-Level Multi-Channel Air Cache Designs for Broadcasting in a Mobile Environment
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Optimal Index and Data Allocation in Multiple Broadcast Channels
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Modern Computer Algebra
Efficient heuristics for data broadcasting on multiple channels
Wireless Networks
A linearly convergent method for broadcast data allocation
Computers & Mathematics with Applications
Scheduling non-uniform data with expected-time constraint in wireless multi-channel environments
Journal of Parallel and Distributed Computing
A data partition based near optimal scheduling algorithm for wireless multi-channel data broadcast
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Skewed allocation of non-uniform data for broadcasting over multiple channels
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Maximum bandwidth broadcast in single and multi-interface networks
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
COCOA'11 Proceedings of the 5th international conference on Combinatorial optimization and applications
FlexInd: a flexible and parameterizable air-indexing scheme for data broadcast systems
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Information Sciences: an International Journal
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Algebraic data retrieval algorithms for multi-channel wireless data broadcast
Theoretical Computer Science
Efficient Approximation Algorithm for Data Retrieval with Conflicts in Wireless Networks
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
Hi-index | 14.98 |
Broadcast is an efficient and scalable way of transmitting data to an unlimited number of clients that are listening to a channel. Cyclically broadcasting data over the channel is a basic scheduling technique, which is known as flat scheduling. When multiple channels are available, a data allocation technique is needed to assign data to channels. Partitioning data among channels in an unbalanced way, depending on data popularities, is an allocation technique known as skewed allocation. In this paper, the problem of data broadcasting over multiple channels is considered, assuming skewed data allocation to channels and flat data scheduling per channel, with the objective of minimizing the average waiting time of the clients. First, several algorithms, based on dynamic programming, are presented which provide optimal solutions for N data items and K channels. Specifically, for data items with uniform lengths, an O(NK\log N) time algorithm is proposed, which improves over the previously known O(N^2K) time algorithm. When K \le 4, a simpler O(N\log N) time algorithm is exhibited which requires only O(N) time if the data items are sorted. Moreover, for data items with nonuniform lengths, it is shown that the problem is NP-hard when K=2 and strong NP-hard for arbitrary K. In the former case, a pseudopolynomial algorithm is discussed whose time is O(NZ), where Z is the sum of the data lengths. In the latter case, an algorithm is devised with time exponential in the maximum data length, which can optimally solve, in reasonable time, only small instances. For larger instances, a new heuristic is devised which is experimentally tested on some benchmarks whose popularities are characterized by Zipf distributions. Such experimental tests reveal that the new heuristic proposed here always outperforms the best previously known heuristic in terms of solution quality.