异构缓存槽的在线分页

IF 0.9 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Marek Chrobak, Samuel Haney, Mehraneh Liaee, Debmalya Panigrahi, Rajmohan Rajaraman, Ravi Sundaram, Neal E. Young
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引用次数: 0

摘要

通过允许每个请求不仅指定点p,而且指定可能为其提供服务的服务器子集S,可以很自然地概括在线\(k\) -Server问题。迄今为止,只研究了这一问题的少数特殊情况。本文提出的工作目标是更系统地探索均匀和星形指标情况下的这种推广。对于统一度量,这个问题等价于分页的一般化,其中每个请求不仅指定一个页面p,还指定一个缓存槽的子集S,并通过在S中的某个槽中有一个p的副本来满足。我们将这个问题称为槽异构分页。在实际设置中,只有缓存槽或服务器的某些子集会出现在请求中。因此,我们通过指定可请求的槽集族\({\mathcal {S}}\subseteq 2^{[k]}\)来参数化问题,并建立竞争比的界限,作为缓存大小k和族\({\mathcal {S}}\)的函数:如果允许所有请求集(\({\mathcal {S}}=2^{[k]}\setminus \{\emptyset \}\)),则最优确定性和随机竞争比指数级地比标准分页(\({\mathcal {S}}=\{[k]\}\))差。作为\(|{\mathcal {S}}|\)和k的函数,最优确定性比为多项式:最多\(O(k^2|{\mathcal {S}}|)\),最少\(\Omega (\sqrt{|{\mathcal {S}}|})\)。对于任意高度为h的层流族\({\mathcal {S}}\),最优比例为O(hk)(确定性)和\(O(h^2\log k)\)(随机化)。层流\({\mathcal {S}}\)的特殊情况(我们称之为All-or-One Paging)通过允许每个请求指定放置所请求页面的特定槽来扩展标准分页。加权全或一分页的最优确定性比率为\(\Theta (k)\)。离线All-or-One分页为\(\mathbb{N}\mathbb{P}\) -hard。层叠情况的一些结果通过对分页的一般化的简化来显示,其中每个请求指定一组\(P\)页面,并通过从\(P\)获取任何页面到缓存来满足。后一个问题(层流族高度为h)的最佳比率最多为hk(确定性)和\(hH_k\)(随机)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Paging with Heterogeneous Cache Slots

It is natural to generalize the online \(k\)-Server problem by allowing each request to specify not only a point p, but also a subset S of servers that may serve it. To date, only a few special cases of this problem have been studied. The objective of the work presented in this paper has been to more systematically explore this generalization in the case of uniform and star metrics. For uniform metrics, the problem is equivalent to a generalization of Paging in which each request specifies not only a page p, but also a subset S of cache slots, and is satisfied by having a copy of p in some slot in S. We call this problem Slot-Heterogenous Paging. In realistic settings only certain subsets of cache slots or servers would appear in requests. Therefore we parameterize the problem by specifying a family \({\mathcal {S}}\subseteq 2^{[k]}\) of requestable slot sets, and we establish bounds on the competitive ratio as a function of the cache size k and family \({\mathcal {S}}\):

  • If all request sets are allowed (\({\mathcal {S}}=2^{[k]}\setminus \{\emptyset \}\)), the optimal deterministic and randomized competitive ratios are exponentially worse than for standard Paging (\({\mathcal {S}}=\{[k]\}\)).

  • As a function of \(|{\mathcal {S}}|\) and k, the optimal deterministic ratio is polynomial: at most \(O(k^2|{\mathcal {S}}|)\) and at least \(\Omega (\sqrt{|{\mathcal {S}}|})\).

  • For any laminar family \({\mathcal {S}}\) of height h, the optimal ratios are O(hk) (deterministic) and \(O(h^2\log k)\) (randomized).

  • The special case of laminar \({\mathcal {S}}\) that we call All-or-One Paging extends standard Paging by allowing each request to specify a specific slot to put the requested page in. The optimal deterministic ratio for weighted All-or-One Paging is \(\Theta (k)\). Offline All-or-One Paging is \(\mathbb{N}\mathbb{P}\)-hard.

Some results for the laminar case are shown via a reduction to the generalization of Paging in which each request specifies a set \(P\) of pages, and is satisfied by fetching any page from \(P\) into the cache. The optimal ratios for the latter problem (with laminar family of height h) are at most hk (deterministic) and \(hH_k\) (randomized).

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来源期刊
Algorithmica
Algorithmica 工程技术-计算机:软件工程
CiteScore
2.80
自引率
9.10%
发文量
158
审稿时长
12 months
期刊介绍: Algorithmica is an international journal which publishes theoretical papers on algorithms that address problems arising in practical areas, and experimental papers of general appeal for practical importance or techniques. The development of algorithms is an integral part of computer science. The increasing complexity and scope of computer applications makes the design of efficient algorithms essential. Algorithmica covers algorithms in applied areas such as: VLSI, distributed computing, parallel processing, automated design, robotics, graphics, data base design, software tools, as well as algorithms in fundamental areas such as sorting, searching, data structures, computational geometry, and linear programming. In addition, the journal features two special sections: Application Experience, presenting findings obtained from applications of theoretical results to practical situations, and Problems, offering short papers presenting problems on selected topics of computer science.
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