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Privacy Protection Through Hiding Location Coordinates Using Geometric Transformation Techniques in Location-Based Services Enabled Mobiles Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Gaussian Tendencies in Data Flow in Communication Links

Authors : Rudra Pratap Ojha, Dharm Raj, Pramod Kumar Srivastava, Goutam Sanyal

Published in: Cyber Security

Publisher: Springer Singapore

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Abstract

We have modeled data flow in communication link using random motion of a particle, which results in a Gaussian pattern of traffic flow over a period of time. The varying degrees of spectral deviation present a coherent model of data flow for wired links. We have considered multiple link systems and presented an n-dimensional representation of traffic model using a Gaussian function governed by n-parameters. The model opens new insights toward analyzing and predicting bandwidth requirements in communication links and their prospective failure.

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previous chapter The Digital Signature Schemes Based on Two Hard Problems: Factorization and Discrete Logarithm
Literature
1.
Sunita K, Mukta N, Jiten M, Shilpa S (2001) Traffic characterization for heterogeneous applications. ECPE 6504
2.
Moore AW, Zuev D (2005) Internet traffic classification using Bayesian analysis techniques. In: Proceedings of the 2005 ACM SIGMETRICS international conference on measurement and modeling of computer systems, pp 50–60
3.
Hohn N, Veitch D (2003) Inverting sampled traffic. In: Proceeding ACM internet measurement conference, Miami, USA, pp 222–233, Oct 2003
4.
Coffman KG, Odlyzko AM (2001) Internet growth: is there a”Moore’s law “for data traffic?”. In: Abello J, Ardalos PMP, Resende GC (eds) Handbook of massive data sets. Kluwer
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Reif F Fundamental of statistical and thermal physics
Metadata
Title
Gaussian Tendencies in Data Flow in Communication Links
Authors
Rudra Pratap Ojha
Dharm Raj
Pramod Kumar Srivastava
Goutam Sanyal
Copyright Year
2018
Publisher
Springer Singapore
Book
Cyber Security

Print ISBN: 978-981-10-8535-2

Electronic ISBN: 978-981-10-8536-9

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-8536-9_48

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