摘要
We study the problem of scheduling tasks for execution by. a processor when the tasks can stochastically generate new tasks. Tasks can be of different types, and each type has a fixed, known probability of generating. other tasks. We present results on the random variable S-sigma modeling the maximal space needed by the processor to store the currently active tasks when acting under the scheduler sigma. We obtain tail bounds for the distribution of S-sigma for both offline and online schedulers, and investigate the expected value E[S-sigma].
- 出版日期2012-1