有限缓冲条件下QoS约束下的速度缩放

Parikshit Hegde, Akshit Kumar, R. Vaze
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引用次数: 0

摘要

在最大丢包概率约束下,考虑具有可变速度和有限缓冲区的单个服务器。服务器的处理成本是服务器速度的凸函数。如果一个数据包到达时缓冲区已满,它将立即被丢弃。给定有限的服务器缓冲区,目标是在最大丢包概率约束下找到最优的动态服务器速度,以最小化总体成本。众所周知,找到精确的最优解是困难的,因此考虑了具有可证明的近似界的算法。结果表明,当缓冲区大小足够大时,所提算法能达到最优性能。对于任意缓冲区大小,常数近似保证得到了一个大的类数据包到达分布,如伯努利,指数,泊松等。
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Speed scaling under QoS constraints with finite buffer
A single server with variable speed and a finite buffer is considered under a maximum packet drop probability constraint. The cost of processing by the server is a convex function of the speed of the server. If a packet arrives when the buffer is full, it is dropped instantaneously. Given the finite server buffer, the objective is to find the optimal dynamic server speed to minimize the overall cost subject to the maximum packet drop probability constraint. Finding the exact optimal solution is known to be hard, and hence algorithms with provable approximation bounds are considered. We show that if the buffer size is large enough, the proposed algorithm achieves the optimal performance. For arbitrary buffer sizes, constant approximation guarantees are derived for a large class of packet arrival distributions such as Bernoulli, Exponential, Poisson etc.
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