Instability of backoff protocols with arbitrary arrival rates

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Leslie Ann Goldberg, John Lapinskas
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引用次数: 0

Abstract

In contention resolution, multiple processors are trying to coordinate to send discrete messages through a shared channel with limited communication. If two processors send at the same time, the messages collide and are not transmitted successfully. Queue-free backoff protocols are an important special case — for example, Google Drive and AWS instruct their users to implement binary exponential backoff to handle busy periods. It is a long-standing conjecture of Aldous (1987) [4] that no stable backoff protocols exist for any positive arrival rate of processors. This foundational question remains open; instability is only known in general when the arrival rate of processors is at least 0.42 (Goldberg et al., 2004 [13]). We prove Aldous' conjecture for all backoff protocols outside of a tightly-constrained special case using a new domination technique to get around the main difficulty, which is the strong dependencies between messages.
任意到达率下退避方案的不稳定性
在争用解决中,多个处理器试图通过有限通信的共享通道协调发送离散消息。如果两个处理器同时发送消息,则消息会发生冲突,无法成功传输。无队列回退协议是一个重要的特例——例如,谷歌Drive和AWS指导他们的用户实现二进制指数回退来处理繁忙时段。Aldous(1987)[4]的一个长期猜想是,对于任何正的处理器到达率,不存在稳定的后退协议。这个基本问题仍然悬而未决;一般来说,只有当处理器到达率至少为0.42时,才知道不稳定性(Goldberg et al., 2004[13])。我们使用一种新的支配技术证明了除严格约束的特殊情况外所有退退协议的Aldous猜想,以绕过消息之间的强依赖关系这一主要困难。
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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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