A pattern-based prediction: An empirical approach to predict end-to-end network latency

Kim, JunSeong; Yi, Jongsu

doi:10.1016/j.jss.2010.07.014

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…It measures network round trip time (RTT) by sending ICMP (Internet Control Message Protocol) echo request and receiving echo reply messages. Though there may exist asymmetry between the forward and the backward network delays, as in many studies on latency dynamics, we use RTTs in this experiment [5,7,12]. We measured network latency between nodes over a 24-hour period; within the Chung-Ang University campus for a small scale network, between the Chung-Ang University and the Busan University of Foreign Studies for a medium scale network, and between the Chung-Ang University and the Duke University for a large scale network.…”

Section: Network Traffic Measurementsmentioning

confidence: 99%

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A classification of network traffic status for various scale networks

Park

Kim

2013

The International Conference on Information Networking 2013 (ICOIN)

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Techniques of network status estimation and traffic prediction are required for network control and user applications in the contexts where a variety of traffic data sources are available. Due to the difficulty of estimating applications' network demands and the difficulty of predicting network load, however, the management of network resources has often been ignored. This paper presents a heuristic of network status classification that has been observed in various scale operational networks. The basic idea of the approach is that network traffic repeat cycles of congested states and that a variation of network latency is strongly correlated with the past history of the latency. We directly monitor network load by continually measuring endto-end network latencies in real operational networks and classify network traffic status with respect to the stability and the burstiness of the latencies. The experimental results showed that the proposed method is capable of evaluating network traffic status and reflecting the related fluctuations.

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Section: Network Traffic Measurementsmentioning

confidence: 99%

“…We use several simple numerical models to characterize network latency based on measurements of latency history [10,11,12]. While we want to have all the past latency measurements in this study only the previous K measurements at time t are considered.…”

Section: A Network Latency Characterizationsmentioning

confidence: 99%

A classification of network traffic status for various scale networks

Park

Kim

2013

The International Conference on Information Networking 2013 (ICOIN)

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A case study on oscillating behavior of end-to-end network latency

Kim

Park

2012

The International Conference on Information Network 2012

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An Efficient Stochastic Update Propagation Method in Data Warehousing

Bordoloi

Kapoor

Jacks

2021

Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing

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This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as compared with the real-time method) due to update propagation required because of changes in source data. More importantly, the method allows system users to place limits on the discrepancy between the source data and the ODS data that could result due to a time lag between source data changes and the update operation. Finally, the pre-specified limits on the discrepancy are maintained while accounting for two crucial factors in distributed systems: 1) some nodes are situated on more congested network links, and 2) some of the links on the network are less reliable. Real-time data propagation does not account for these frequently encountered networking concerns.

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A pattern-based prediction: An empirical approach to predict end-to-end network latency

Cited by 4 publications

References 12 publications

A classification of network traffic status for various scale networks

A classification of network traffic status for various scale networks

A case study on oscillating behavior of end-to-end network latency

An Efficient Stochastic Update Propagation Method in Data Warehousing

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