Beyond processor sharing
Beyond processor sharing
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超越处理器共享
DOI：
10.1145/1243401.1243409
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
R. Nunez
中科院分区：
文献类型：
--
作者：
S. Aalto;U. Ayesta;S. Borst;V. Misra;R. Nunez
虽然（平等）处理器共享（PS）学科为公平资源分配机制的性能提供了重要见解，但它在分析和设计加权公平队列和加权轮循等差异化调度算法方面存在固有的局限性。歧视性处理器共享（DPS）和广义处理器共享（GPS）学科是对此类服务差异化机制性能建模的自然概括。多级处理器共享（MLPS）是普通处理器共享策略的进一步扩展，它在基于规模的调度策略的分析、设计和实施中发挥了举足轻重的作用。我们回顾了 DPS、GPS 和 MLPS 模型的各种关键结果，强调了这些规则在多大程度上继承了普通 PS 的理想特性或能够提供差异化服务。
While the (Egalitarian) Processor-Sharing (PS) discipline offers crucial insights in the performance of fair resource allocation mechanisms, it is inherently limited in analyzing and designing differentiated scheduling algorithms such as Weighted Fair Queueing and Weighted Round-Robin. The Discriminatory Processor-Sharing (DPS) and Generalized Processor-Sharing (GPS) disciplines have emerged as natural generalizations for modeling the performance of such service differentiation mechanisms. A further extension of the ordinary PS policy is the Multilevel Processor-Sharing (MLPS) discipline, which has captured a pivotal role in the analysis, design and implementation of size-based scheduling strategies. We review various key results for DPS, GPS and MLPS models, highlighting to what extent these disciplines inherit desirable properties from ordinary PS or are capable of delivering service differentiation.