论文标题

用MakePan最小化的在线日程安排:最先进的结果,研究挑战和开放问题

Online Scheduling with Makespan Minimization: State of the Art Results, Research Challenges and Open Problems

论文作者

Dwibedy, Debasis, Mohanty, Rakesh

论文摘要

自格雷厄姆(Graham)开创性工作以来,在过去的五十年中,在线计划是一个精心研究和挑战性的研究问题,在各种应用中具有巨大的实际意义,例如交互式并行处理,通信网络中的路由,分布式数据管理,客户服务器通信,交通运输,工业制造业和生产中的交通管理,交通管理,交通管理和生产。在此问题中,调度程序将一一接收到一系列作业,以在许多机器上进行调度。在作业到达后,调度程序将作业不可撤销地分配给机器,然后在下一个作业的可用性之前,目的是最大程度地减少计划工作的完成时间。本文重点介绍了在线安排一系列独立工作和统一相关机器的独立工作的贡献的状态,并特别关注了先发制人和非抢先的处理格式,通过考虑将pan最小化为最佳标准。我们从初学者的角度介绍了在线调度的基本方面以及一般调度框架的背景。文献中著名的确定性和随机在线调度算法获得的重要竞争分析结果以及研究挑战和开放问题。讨论了一些新兴的近期趋势,例如资源增强和半对线计划,以此作为未来研究工作的动机。

Online scheduling has been a well studied and challenging research problem over the last five decades since the pioneering work of Graham with immense practical significance in various applications such as interactive parallel processing, routing in communication networks, distributed data management, client-server communications, traffic management in transportation, industrial manufacturing and production. In this problem, a sequence of jobs is received one by one in order by the scheduler for scheduling over a number of machines. On arrival of a job, the scheduler assigns the job irrevocably to a machine before the availability of the next job with an objective to minimize the completion time of the scheduled jobs. This paper highlights the state of the art contributions for online scheduling of a sequence of independent jobs on identical and uniform related machines with a special focus on preemptive and non-preemptive processing formats by considering makespan minimization as the optimality criterion. We present the fundamental aspects of online scheduling from a beginner's perspective along with a background of general scheduling framework. Important competitive analysis results obtained by well-known deterministic and randomized online scheduling algorithms in the literature are presented along with research challenges and open problems. Two of the emerging recent trends such as resource augmentation and semi-online scheduling are discussed as a motivation for future research work.

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