SIAM Journal on Computing
Efficient 2-dimensional approximate matching of non-rectangular figures
SODA '91 Proceedings of the second annual ACM-SIAM symposium on Discrete algorithms
Non-standard stringology: algorithms and complexity
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Efficient 2-dimensional approximate matching of half-rectangular figures
Information and Computation
Scheduling Parallel Machines On-line
SIAM Journal on Computing
Scheduling to minimize average completion time: off-line and on-line algorithms
Proceedings of the seventh annual ACM-SIAM symposium on Discrete algorithms
On the complexity of coordinated display of multimedia objects
Theoretical Computer Science
A fast string searching algorithm
Communications of the ACM
On Coordinated Display of Structured Video
IEEE MultiMedia
An Optimal Resource Scheduler for Continuous Display of Structured Video Objects
IEEE Transactions on Knowledge and Data Engineering
On Scheduling Atomic and Composite Continuous Media Objects
IEEE Transactions on Knowledge and Data Engineering
Resource Scheduling for Composite Multimedia Objects
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
A Modified Split-Radix FFT With Fewer Arithmetic Operations
IEEE Transactions on Signal Processing
| Hi-index | 0.00 |
The problem of scheduling resources for tasks with variable requirements over time can be stated as follows. We are given two sequences of vectors A=A 1,驴,A n and R=R 1,驴,R m . Sequence A represents resource availability during n time intervals, where each vector A i has q elements. Sequence R represents resource requirements of a task during m intervals, where each vector R i has q elements. We wish to find the earliest time interval i, termed latency, such that for 1驴k驴m, 1驴j驴q: A i+k驴1 j 驴R k j , where A i+k驴1 j and R k j are the jth elements of vectors A i+k驴1 and R k , respectively. One application of this problem is I/O scheduling for multimedia presentations. The fastest known algorithm to compute the optimal solution of this problem has ${\mathcal{O}}(n\sqrt{m}\log m)$ computation time (Amir and Farach, in Proceedings of the ACM-SIAM symposium on discrete algorithms (SODA), San Francisco, CA, pp. 212---223, 1991; Inf. Comput. 118(1):1---11, 1995). We propose a technique that approximates the optimal solution in linear time: ${\mathcal{O}}(n)$ . We evaluated the performance of our algorithm when used for multimedia I/O scheduling. Our results show that 95% of the time, our solution is within 5% of the optimal.