TAILIEUCHUNG - Mạng lưới giao thông và đánh giá hiệu suất P20

Since the statistical analysis of Ethernet local-area network (LAN) traces in Leland et al. [20], there has been signi®cant progress in developing appropriate mathematical and statistical techniques that provide a physical-based, networking-related understanding of the observed fractal-like or self-similar scaling behavior of measured data traf®c over time scales ranging from hundreds of milliseconds to seconds and beyond. These techniques explain, describe, and validate the reported large-time scaling. | Self-Similar Network Traffic and Performance Evaluation Edited by Kihong Park and Walter Willinger Copyright 2000 by John Wiley Sons Inc. Print ISBN 0-471-31974-0 Electronic ISBN 0-471-20644-X 20 TOWARD AN IMPROVED UNDERSTANDING OF NETWORK TRAFFIC DYNAMICS R. H. Riedi Department of Electrical and Computer Engineering Rice University Houston TX 77251 Walter Willinger Information Sciences Research Center AT T Labs-Research Florham Park NJ 07932 INTRODUCTION Since the statistical analysis of Ethernet local-area network LAN traces in Leland et al. 20 there has been significant progress in developing appropriate mathematical and statistical techniques that provide a physical-based networking-related understanding of the observed fractal-like or self-similar scaling behavior of measured data traffic over time scales ranging from hundreds of milliseconds to seconds and beyond. These techniques explain describe and validate the reported large-time scaling phenomenon in aggregate network traffic at the packet level in terms of more elementary properties of the traffic patterns generated by the individual users and or applications. They have impacted our understanding of actual network traffic to the point where we now know why aggregate data traffic exhibits fractal scaling behavior over time scales from a few hundreds of milliseconds onward. In fact a measure of the success of this new understanding is that the corresponding mathematical arguments are at the same time rigorous and simple are in full agreement with the networking researchers intuition and with measured 507 508 NETWORK TRAFFIC DYNAMICS data and can be explained readily to a non-networking expert. These developments have helped immensely in demystifying fractal-based traffic modeling and have given rise to new insights and physical understanding of the effects of large-time scaling properties in measured network traffic on the design management and performance of high-speed networks. However to provide a

TÀI LIỆU LIÊN QUAN
TỪ KHÓA LIÊN QUAN
TAILIEUCHUNG - Chia sẻ tài liệu không giới hạn
Địa chỉ : 444 Hoang Hoa Tham, Hanoi, Viet Nam
Website : tailieuchung.com
Email : tailieuchung20@gmail.com
Tailieuchung.com là thư viện tài liệu trực tuyến, nơi chia sẽ trao đổi hàng triệu tài liệu như luận văn đồ án, sách, giáo trình, đề thi.
Chúng tôi không chịu trách nhiệm liên quan đến các vấn đề bản quyền nội dung tài liệu được thành viên tự nguyện đăng tải lên, nếu phát hiện thấy tài liệu xấu hoặc tài liệu có bản quyền xin hãy email cho chúng tôi.
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.