In this paper we study the multiple-processor multitask scheduling problem in both deterministic and stochastic models. We consider and analyze Modified Shortest Remaining Processing Time (M-SRPT) scheduling algorithm, a simple modification of SRPT, which always schedules jobs according to SRPT whenever possible, while processes tasks in an arbitrary order. The M-SRPT algorithm is proved to achieve a competitive ratio of $\Theta(\log \alpha +\beta)$ for minimizing response time, where $\alpha$ denotes the ratio between maximum job workload and minimum job workload, $\beta$ represents the ratio between maximum non-preemptive task workload and minimum job workload. In addition, the competitive ratio achieved is shown to be optimal (up to a constant factor), when there are constant number of machines. We further consider the problem under Poisson arrival and general workload distribution (\ie, $M/GI/N$ system), and show that M-SRPT achieves asymptotic optimal mean response time when the traffic intensity $\rho$ approaches $1$, if job size distribution has finite support. Beyond finite job workload, the asymptotic optimality of M-SRPT also holds for infinite job size distributions with certain probabilistic assumptions, for example, $M/M/N$ system with finite task workload.
翻译:在本文中,我们研究了确定性和随机性模式中的多处理器多任务调度问题。我们考虑并分析了修改后最短的剩余处理时间(M-SRPT)排期算法,这是对SRPT的简单修改,它总是尽可能按照SRPT安排工作,而程序则按任意顺序安排工作。M-SRPT算法被证明可以达到一个竞争性比率,即:美元(log =alpha ⁇ beta),以尽量减少反应时间,美元(alpha$)表示最大工作工作量和最低工作工作量之间的比率,美元(beta$)代表最大非先发制人任务工作量和最低工作工作量之间的比率。此外,在机器数量不变的情况下,所实现的竞争比率被证明是最佳的(最高因素),我们进一步考虑Poisson抵达和一般工作量分配下的问题(\i, $M/GI/N$系统),并表明M-SRPT在交通强度接近1美元时,如果工作规模的配置具有一定的弹性工作工作量,那么,M-PT-S-S-S-S-S-S-S-S-Slestal laim ex-S-S-Slvical latistrim ex ex ex ex latistr ex ex latic ex ex ex ex ex ex ex ex ex ex ex ex laticilticticil ex ex ex latistr ex lati ex latistr latistrit latiplpltistr latistr latistrit latisk exx exx exx exx exx exx exx expstr latistr latistr siblistr latistr latistr latistr siblistr latisk s exp exp ex si) latistr ex ex ex ex exm exm exm exm exm ex ex ex exm exm ex ex exm exm ex ex) ex) lati ex ex