发明申请
US20090006607A1 SCALABLE METHODS FOR DETECTING SIGNIFICANT TRAFFIC PATTERNS IN A DATA NETWORK
有权
用于检测数据网络中重要交通模式的可扩展方法
- 专利标题: SCALABLE METHODS FOR DETECTING SIGNIFICANT TRAFFIC PATTERNS IN A DATA NETWORK
- 专利标题(中): 用于检测数据网络中重要交通模式的可扩展方法
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申请号: US11770430申请日: 2007-06-28
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公开(公告)号: US20090006607A1公开(公告)日: 2009-01-01
- 发明人: Tian Bu , Jin Cao , Aiyou Chen , Pak-Ching Lee
- 申请人: Tian Bu , Jin Cao , Aiyou Chen , Pak-Ching Lee
- 主分类号: G06F15/173
- IPC分类号: G06F15/173 ; G06F17/30
摘要:
Methods and apparatuses are provided for detecting traffic patterns in a data network. A sequential hashing scheme can be utilized that has D hash arrays. Each hash array i, wherein 1≦i≦D, includes Mi independent hash tables each having K buckets, with each of the buckets having an associated traffic total. Each of the keys corresponds with a single bucket of each of the Mi independent hash tables of each hash array i. The keys of the data network are partitioned into D words. As traffic is received for a key, a traffic total of each bucket that corresponds with a key is updated. The hash arrays can then be utilized to identify high traffic buckets of the independent hash tables having a traffic total greater than a threshold value. The high traffic buckets can be used to detect significant traffic patterns of the data network.
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