Minimizing mean flow time with release time constraint
Theoretical Computer Science
On-line scheduling in the presence of overload
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
MOCA: a multiprocessor on-line competitive algorithm for real-time system scheduling
Theoretical Computer Science - Special issue on dependable parallel computing
Approximating total flow time on parallel machines
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Minimizing the flow time without migration
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
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We consider a benefit model for on-line preemptive scheduling. In this model jobs arrive to the on-line scheduler at their release time. Each job arrives with its own execution time and its benefit function. The flow time of a job is the time that passes from its release to its completion. The benefit function specifies the benefit gained for any given flow time. A scheduler's goal is to maximize the total gained benefit. We present a constant competitive ratio algorithm for that model in the uniprocessor case for benefit functions that do not decrease too fast.We also extend the algorithm to the multiprocessor case while maintaining constant competitiveness. The multiprocessor algorithm does not use migration, i.e., preempted jobs continue their execution on the same processor on which they were originally processed.