AF: EAGER: Scheduling with Resource Contraints

即使计算能力、网络带宽和其他资源的可用性快速增加，用户和应用程序对计算的需求和对资源的使用也以大致相同的速度增加。因此，无论在硬件效率方面取得多大进展，我们都将始终需要高效的算法来管理这些资源。以智能方式管理额外资源的理念超越了计算机系统，并与许多其他科学和工业领域相关。在各种实际系统中，可以通过向作业操作分配资源，例如额外的金钱、加班费、能源、燃料、催化剂、分包或额外的人力来控制处理时间。在这样的系统中，作业调度和资源分配决策应该仔细协调，以实现最高效的系统性能。在许多工业领域都有应用。PI计划研究在有额外资源约束的调度中出现的几个算法问题。虽然这个领域在过去十年和以后得到了很大的关注，但PI将专注于两个在计算机科学界很少受到关注的领域--当时间表的好处和能源或其他资源的成本被货币化时的调度，以及超出通常研究的计算机系统设置的模型的调度。因为这些都很少受到关注，所以这项工作有点投机性。如果成功，这项工作可能会产生很高的影响，应用到许多新的领域。PI将设计简单、低开销的算法。

Even as the availability of computing power, network bandwidth and other resources increases at a rapid rate, users and applications increase their demand for computation and their use of resources at roughly the same pace.  Thus, no matter how much progress is made  on hardware efficiency, we will always need efficient algorithms to manage these resources. The philosophy of managing additional resources in an intelligent manner goes beyond computer systems, and is relevant to many other  scientific and industrial areas. In various real-life systems, processing times may be controllable by allocating resources, such as additional money, overtime, energy, fuel, catalysts, subcontracting, or additional manpower, to the job operations. In such systems, job scheduling and resource allocation decisions should be coordinated carefully to achieve the most efficient system performance. Applications arise in many industrial areas.The PI plans to study several algorithmic problems that arise in scheduling with additional resource constraints.   While this field has received much attention over the past ten years and beyond, the PI will focus on two areas that have received very little attention in the computer science community -- scheduling when the benefit of the schedule and the cost of energy or other resources are monetized, and scheduling in models that go beyond the typically studied computer systems setting.  Because these have received very little attention, this work is somewhat speculative.  If successful, this work could have a high impact, with applications into many new areas. The PI will design simple, low overhead algorithms.