A user-friendly self-similarity analysis tool

被引:38
作者
Karagiannis, T [1 ]
Faloutsos, M [1 ]
Molle, M [1 ]
机构
[1] Univ Calif Riverside, Dept Comp Sci & Engn, Riverside, CA 92521 USA
关键词
D O I
10.1145/956993.957004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The concepts of self-similarity, fractals, and long-range dependence (LRD) have revolutionized network modeling during the last decade. However, despite all the attention these concepts have received, they remain difficult to use by non-experts. This difficulty can be attributed to a relative complexity of the mathematical basis, the absence of a systematic approach to their application and the absence of publicly available software. In this paper, we introduce SELFIS, a comprehensive tool, to facilitate the evaluation of LRD by practitioners. Our goal is to create a stand-alone public tool that can become a reference point for the community. Our tool integrates most of the required functionality for an in-depth LRD analysis, including several LRD estimators. In addition, SELFIS includes a powerful approach to stress-test the existence of LRD. Using our tool, evidence are presented that the widely-used LRD estimators can provide misleading results. It is worth mentioning that 25 researchers have acquired SELFIS within a month of its release, which clearly demonstrates the need for such a tool.
引用
收藏
页码:81 / 93
页数:13
相关论文
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