价值衰减工件非抢占加工中贪婪调度的效率损失
Efficiency-Loss of Greedy Schedules in Non-Preemptive Processing of Jobs with Decaying Value
摘要：
我们考虑了在N个处理器上动态调度J个作业的非抢占式执行问题，其中每个作业的值（或完成后获得的奖励）随着时间的推移而衰减。所有的作业最初都在缓冲区中可用，并且它们的服务时间分布是已知的。当一个处理器变得可用时，必须确定安排哪个空闲作业，以便最大化完成所有作业所累积的总期望奖励。这样的问题出现在不同的应用领域，例如，调度病人的医疗程序，易腐货物的供应链，数据包调度延迟敏感的通信网络流量等计算的最佳时间表是一般棘手的，而在线低复杂度的时间表往往是必不可少的，在实践中。它表明，简单的贪婪/近视的时间表可证明达到性能的一个因素2 + E[max_j sigma_j]（min_j E[sigma_j]）从最优。当服务时间相同分布时，此界限可以改进为2倍。贪婪的时间表的各个方面进行了检查，它被证明在一些实际情况下，尽管它忽略了奖励衰减更深的时间，执行相当接近最优。
英文摘要：
We consider the problem of dynamically scheduling J jobs on N processors for non-preemptive execution where the value of each job (or the reward garnered upon completion) decays over time. All jobs are initially available in a buffer and the distribution of their service times are known. When a processor becomes available, one must determine which free job to schedule so as to maximize the total expected reward accrued for the completion of all jobs. Such problems arise in diverse application areas, e.g. scheduling of patients for medical procedures, supply chains of perishable goods, packet scheduling for delay-sensitive communication network traffic, etc. Computation of optimal schedules is generally intractable, while online low-complexity schedules are often essential in practice. It is shown that the simple greedy/myopic schedule provably achieves performance within a factor 2 + E[max_j sigma_j](min_j E[sigma_j]) from optimal. This bound can be improved to a factor of 2 when the service times are identically distributed. Various aspects of the greedy schedule are examined and it is demonstrated to perform quite close to optimal in some practical situations despite the fact that it ignores reward-decay deeper in time.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
