The design and evaluation of the Simple Self-Similar Sequences Generator

Authors:
Pedro R. M. Inácio;Branka Lakic;Mário M. Freire;Manuela Pereira;Paulo P. Monteiro
Affiliations:
Nokia Siemens Networks Portugal S.A., Rua Irmãos Siemens, No. 1, 2720-093 Amadora, Portugal and IT-Networks and Multimedia Group, Department of Computer Science, University of Beira Interior, ...;Institute of Telecommunication, University Campus of Santiago, P-3810-193 Aveiro, Portugal;IT-Networks and Multimedia Group, Department of Computer Science, University of Beira Interior, Rua Marquês d'Ávila e Bolama, 6201-001 Covilhã, Portugal;IT-Networks and Multimedia Group, Department of Computer Science, University of Beira Interior, Rua Marquês d'Ávila e Bolama, 6201-001 Covilhã, Portugal;Nokia Siemens Networks Portugal S.A., Rua Irmãos Siemens, No. 1, 2720-093 Amadora, Portugal and Institute of Telecommunication, University Campus of Santiago, P-3810-193 Aveiro, Portugal
Venue:
Information Sciences: an International Journal
Year:
2009

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Abstract

This paper describes a new algorithm for the generation of pseudo random numbers with approximate self-similar structure. The Simple Self-Similar Sequences Generator (4SG) elaborates on an intuitive approach to obtain a fast and accurate procedure, capable of reproducing series of points exhibiting the property of persistence and anti-persistence. 4SG has a computational complexity of O(n) and memory requirements of the order of log"2(N), where N is the number of points to be generated. The accuracy of the algorithm is evaluated by means of computer-based simulations, recurring to several Hurst parameter estimators, namely Variance Time (VT) and the Wavelets-based estimator. The Hosking and the Wavelets-based methods for the generation of self-similar series were submitted to the same tests the 4SG was analysed with, providing for a basis for comparison of several performance aspects of the algorithm. Results show that the proposal embodies a good candidate not only for on-demand emulation of arbitrarily long self-similar sequences, but also for fast and efficient online simulations.