2013/08/18 by Xiaofeng Bai, Abdallah Shami, Bai, Xiaofeng +1 · 35 citations
Computer Science · Engineering · Mathematics · #Artificial intelligence #Computer network #Computer science #Data mining #Dependency (UML) #Engineering #FOS: Computer and information sciences #Mathematics #Network Security and Intrusion Detection #Network Traffic and Congestion Control #Network traffic control #Network traffic simulation #Networking and Internet Architecture (cs.NI) #Peer-to-Peer Network Technologies #Property (philosophy) #Protocol (science) #Range (aeronautics) #Self-similarity #Similarity (geometry) #Traffic generation model #cs.NI
paper · pdf · doi:10.48550/arxiv.1308.3842
published in arXiv (Cornell University) (Cornell University) · Self-Similar Traffic
arxiv created 2013/08/18 · openalex publication_date 2013/08/18 · arxiv updated 2013/08/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
In order to closely simulate the real network scenario thereby verify the effectiveness of protocol designs, it is necessary to model the traffic flows carried over realistic networks. Extensive studies [1] showed that the actual traffic in access and local area networks (e.g., those generated by ftp and video streams) exhibits the property of self-similarity and long-range dependency (LRD) [2]. In this appendix we briefly introduce the property of self-similarity and suggest a practical approach for modeling self-similar traces with specified traffic intensity.