Monitored network data allows operators to gain valuable insight into the health and status of a network. Whilst such data is useful for real-time analysis, there is often a need to post-process historical network performance data. Storage of the monitored data then becomes a serious issue as network monitoring activities generate significant quantities of data. The work in this thesis is motivated by the need of measuring the performance of high-speed networks. Such networks produce large amounts of data over a long period of time, making the storage of this information practically inefficient. A possible solution to this problem is to use lossy compression on an on-line system that intelligently compresses computer network measurements while preserving the quality in important characteristics of the signal. This thesis contributes to the knowledge by examining two threshold estimation techniques, two threshold application techniques and the impact of window size on the lossy compression performance. In addition eight different wavelets were examined in terms of compression performance, energy preservation, scaling behaviour, quality attributes and Long Range Dependence.
具體描述
讀後感
評分
評分
評分
評分
用戶評價
相關圖書
本站所有內容均為互聯網搜索引擎提供的公開搜索信息，本站不存儲任何數據與內容，任何內容與數據均與本站無關，如有需要請聯繫相關搜索引擎包括但不限於百度，google,bing,sogou 等
© 2025 qciss.net All Rights Reserved. 小哈圖書下載中心 版权所有