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On fundamental tradeoffs between delay bounds and computational complexity in packet scheduling algorithms

机译:分组调度算法中延迟界限与计算复杂度之间的基本权衡

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We clarify, extend, and solve a long-standing open problem concerning the computational complexity for packet scheduling algorithms to achieve tight end-to-end delay bounds. We first focus on the difference between the time a packet finishes service in a scheduling algorithm and its virtual finish time under a GPS (General Processor Sharing) scheduler, called GPS-relative delay. We prove that, under a slightly restrictive but reasonable computational model, the lower bound computational complexity of any scheduling algorithm that guarantees O(1) GPS-relative delay bound is /spl Omega/(logn). We also discover that, surprisingly, the complexity lower bound remains the same even if the delay bound is relaxed to O(n/sup a/) for 0
机译:我们阐明,扩展并解决了一个长期存在的开放问题,该问题涉及数据包调度算法的计算复杂性,以实现严格的端到端延迟范围。我们首先关注数据包在调度算法中完成服务的时间与在GPS(通用处理器共享)调度器下的虚拟完成时间(称为GPS相对延迟)之间的差异。我们证明,在略有限制但合理的计算模型下,保证O(1)GPS相对延迟范围的任何调度算法的下限计算复杂度为/ spl Omega /(logn)。我们还发现,令人惊讶的是,即使对于0 <1,延迟范围放宽到O(n / sup a /),复杂度下限也保持不变。这意味着延迟复杂度折衷曲线在“间隔” [O(1),O(n))中是平坦的。稍后我们有条件地将两个复杂度结果(对于O(1)或O(n / sup a /)延迟)扩展到一个更强大的计算模型,即线性决策树。最后,我们表明,如果延迟范围是通过延迟率(LR)框架提供的,则相同复杂度的下限有条件地适用于保证严格的端到端延迟范围。

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