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17,405
Performance guarantees for Btrees . . .
, 2010
"... Most Btree papers assume that all N keys have the same size K, that f = B/K keys fit in a disk block, and therefore that the search cost is O(log f+1 N) block transfers. When keys have variable size, however, Btree operations have no nontrivial performance guarantees. This paper provides Btreeli ..."
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Most Btree papers assume that all N keys have the same size K, that f = B/K keys fit in a disk block, and therefore that the search cost is O(log f+1 N) block transfers. When keys have variable size, however, Btree operations have no nontrivial performance guarantees. This paper provides B
Performance Guarantees for Web Server EndSystems: A ControlTheoretical Approach
 IEEE Transactions on Parallel and Distributed Systems
, 2001
"... The Internet is undergoing substantial changes from a communication and browsing infrastructure to a medium for conducting business and marketing a myriad of services. The World Wide Web provides a uniform and widelyaccepted application interface used by these services to reach multitudes of client ..."
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Cited by 271 (19 self)
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of clients. These changes place the web server at the center of a gradually emerging eservice infrastructure with increasing requirements for service quality and reliability guarantees in an unpredictable and highlydynamic environment.
Population estimation with performance guarantees
 In Proceedings of IEEE Symposium on Information Theory
, 2007
"... Abstract — We estimate the population size by sampling uniformly from the population. Given an accuracy to which we need to estimate the population with a prespecified confidence, we provide a simple stopping rule for the sampling process. I. SUMMARY Many applications such as species estimation [1] ..."
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Cited by 7 (1 self)
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Abstract — We estimate the population size by sampling uniformly from the population. Given an accuracy to which we need to estimate the population with a prespecified confidence, we provide a simple stopping rule for the sampling process. I. SUMMARY Many applications such as species estimation [1], database sampling [2], and epidemiologic studies [3], [4], [5] call for estimating a population size based on a relatively small sample. We derive a simple, yet nearly optimal, stopping rule for sampling and an estimation formula for alphabet size from uniform samples taken from the population. We will consider an approach outlined for the species estimation problem by Good [6] further on in the summary. For a more complete survey of prior results obtained in the species estimation problem, see [1]. For problems in database sampling see [7], [2]. The results obtained in this paper are also related to capturerecapture problems [3], [4], [5], where the unknown population size is estimated given the number of samples that are recaptured (repetitions) when sampling randomly from the population. Here, we are interested in how many recaptures are necessary to estimate the population to a given accuracy with a specified confidence. Intuitively speaking, the more the number of recaptures, the better the population size can be estimated. Formally, in an nelement sample let m denote the number of distinct elements. Let r = n − m denote the number of repeated elements. For example, in c,g,c,s,g,c,v, there are n = 7 samples, there are m = 4 distinct elements, c,g,s, and v, and r = 7 − 4 = 3 repeated elements, one g and two c ′. In the following, n independent samples are drawn uniformly from a kelement population and M k n and R k n = n − M k n are the random number of distinct and repeated elements observed. We drop the subscripts and superscripts when there is no ambiguity. A. Good’s approach By linearity of expectations, E(M) = k 1 −
Service Disciplines for Guaranteed Performance Service in PacketSwitching Networks
 Proceedings of the IEEE
, 1995
"... While today’s computer networks support only besteffort service, future packetswitching integratedservices networks will have to support realtime communication services that allow clients to transport information with performance guarantees expressed in terms of delay, delay jitter, throughput, ..."
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Cited by 609 (4 self)
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While today’s computer networks support only besteffort service, future packetswitching integratedservices networks will have to support realtime communication services that allow clients to transport information with performance guarantees expressed in terms of delay, delay jitter, throughput
Efficient verification of performability guarantees
 in Proceedings of the 5th International Workshop on Performability Modeling of Computer and Communication Systems
, 2001
"... The performability of a system is usually evaluated as the mean of a performance measure, aggregated over all failure scenarios (both tolerated and not) through a Markov reward process. This metric can gloss over performance deficiencies in important portions of the failure scenario space, and is al ..."
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Cited by 2 (0 self)
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The performability of a system is usually evaluated as the mean of a performance measure, aggregated over all failure scenarios (both tolerated and not) through a Markov reward process. This metric can gloss over performance deficiencies in important portions of the failure scenario space
Performance Guarantees on ATM Networks
"... Recent developments in ATM technology has made multiplexingof a wide range of traffic with diverse performance requirements important. The statistical multiplexing of several traffic types such as voice, video and data can lead to network congestion thus violating the quality of service (QOS) guaran ..."
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) guarantees. In order to meet the performance requirements of the applications an efficient transport protocol and congestion control mechanism becomes necessary. We propose a transport mechanism for guaranteeing application required QOS requirements over an ATM network. Leakybucket congestion control scheme
Facade: Virtual Storage Devices With Performance Guarantees
, 2003
"... Highend storage systems, such as those in large data centers, must service multiple independent workloa&. Workloa& often require predictable quality of service, deslite the fact that they have to compete with other rapidlychanging workloads for access to common storage resources. We presen ..."
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Cited by 108 (11 self)
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present a novel approach to providing performance guarantees in this highlyvolatile scenario, in an efficient and costeffective way. Facade, a virtual store controller, sits between hosts and storage devices in the network, and throttles individual I/0 requests from multiple clients so that devices do
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