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1. 发明授权

US09083708B2 Asymmetric end host redundancy elimination for networks 有权
标题翻译：网络不对称终端主机冗余消除
公开(公告)号：US09083708B2
公开(公告)日：2015-07-14
申请号：US12781782
申请日：2010-05-17
申请人： Ramachandran Ramjee , Bhavish Aggarwal , Pushkar Chitnis , George Varghese , Ashok Anand , Chitra Muthukrishnan , Athula Balachandran
发明人： Ramachandran Ramjee , Bhavish Aggarwal , Pushkar Chitnis , George Varghese , Ashok Anand , Chitra Muthukrishnan , Athula Balachandran
IPC分类号： G06F15/16 , H04L29/08
CPC分类号： H04L67/1002
摘要： An end host redundancy elimination system and method to provide redundancy elimination as an end system service. Embodiments of the system and method use optimization techniques that reduce server central processing unit (CPU) load and memory footprint as compared to existing approaches. For server storage, embodiments of the system and method use a suite of highly-optimized data structures for managing metadata and cached payloads. An optimized asymmetric max-match technique exploits the inherent structure in data maintained at the server and client and ensures that client processing load is negligible. A load-adaptive fingerprinting technique is used that is much faster than current fingerprinting techniques while still delivering similar compression. Load-adaptive means that embodiments of the fingerprinting technique can adapt CPU usage depending on server load. Embodiments of the system and method operate above the transmission control protocol (TCP) layer, thereby reducing the number of roundtrips needed for data transfer.
摘要翻译：终端主机冗余消除系统和方法，作为终端系统服务提供冗余消除。与现有方法相比，系统和方法的实施例使用减少服务器中央处理单元（CPU）负载和存储器占用的优化技术。对于服务器存储，系统和方法的实施例使用一组高度优化的数据结构来管理元数据和高速缓存的有效载荷。优化的非对称最大匹配技术利用了在服务器和客户机上维护的数据的固有结构，并确保客户端处理负载可以忽略不计。使用比当前指纹技术更快的负载自适应指纹技术，同时仍然提供类似的压缩。负载自适应意味着指纹技术的实施例可以根据服务器负载来调整CPU使用。系统和方法的实施例在传输控制协议（TCP）层之上操作，从而减少数据传输所需的往返次数。

2. 发明授权

US08880933B2 Learning signatures for application problems using trace data 有权
标题翻译：使用跟踪数据学习应用程序问题的签名
公开(公告)号：US08880933B2
公开(公告)日：2014-11-04
申请号：US13080393
申请日：2011-04-05
申请人： Ranjita Bhagwan , Venkata N. Padmanabhan , Bhavish Aggarwal , Lorenzo De Carli
发明人： Ranjita Bhagwan , Venkata N. Padmanabhan , Bhavish Aggarwal , Lorenzo De Carli
IPC分类号： G06F11/00 , G06N5/02 , H04L12/24 , G06F11/16 , G06F11/07 , H04L12/26
CPC分类号： G06N5/025 , G06F11/079 , G06F11/1658 , H04L41/0636 , H04L43/04
摘要： The problem signature extraction technique extracts problem signatures from trace data collected from an application. The technique condenses the manifestation of a network, software or hardware problem into a compact signature, which could then be used to identify instances of the same problem in other trace data. For a network configuration, the technique uses as input a network-level packet trace of an application's communication and extracts from it a set of features. During the training phase, each application run is manually labeled as GOOD or BAD, depending on whether the run was successful or not. The technique then employs a learning technique to build a classification tree not only to distinguish between GOOD and BAD runs but to also sub-classify the BAD runs into different classes of failures. Once a classification tree has been learned, problem signatures are extracted by walking the tree, from the root to each leaf.
摘要翻译：问题签名提取技术从应用程序收集的跟踪数据中提取问题签名。该技术将网络，软件或硬件问题的表现集中到紧凑签名中，然后可以将其用于识别其他跟踪数据中相同问题的实例。对于网络配置，该技术用作输入应用程序通信的网络级数据包跟踪，并从中提取一组特征。在培训阶段，每个应用程序运行都会手动标记为GOOD或BAD，具体取决于运行是否成功。然后，该技术采用学习技术来构建分类树，不仅可以区分GOOD和BAD运行，而且还将BAD运行次分类到不同类别的故障中。一旦学习了分类树，就可以通过将树从根移到每个叶来提取问题签名。

3. 发明申请

US20120260141A1 LEARNING SIGNATURES FOR APPLICATION PROBLEMS USING TRACE DATA 有权
标题翻译：使用跟踪数据的应用问题的学习签名
公开(公告)号：US20120260141A1
公开(公告)日：2012-10-11
申请号：US13080393
申请日：2011-04-05
申请人： Ranjita Bhagwan , Venkata N. Padmanabhan , Bhavish Aggarwal , Lorenzo De Carli
发明人： Ranjita Bhagwan , Venkata N. Padmanabhan , Bhavish Aggarwal , Lorenzo De Carli
IPC分类号： G06F11/34
CPC分类号： G06N5/025 , G06F11/079 , G06F11/1658 , H04L41/0636 , H04L43/04
摘要： The problem signature extraction technique extracts problem signatures from trace data collected from an application. The technique condenses the manifestation of a network, software or hardware problem into a compact signature, which could then be used to identify instances of the same problem in other trace data. For a network configuration, the technique uses as input a network-level packet trace of an application's communication and extracts from it a set of features. During the training phase, each application run is manually labeled as GOOD or BAD, depending on whether the run was successful or not. The technique then employs a learning technique to build a classification tree not only to distinguish between GOOD and BAD runs but to also sub-classify the BAD runs into different classes of failures. Once a classification tree has been learned, problem signatures are extracted by walking the tree, from the root to each leaf.
摘要翻译：问题签名提取技术从应用程序收集的跟踪数据中提取问题签名。该技术将网络，软件或硬件问题的表现集中到紧凑签名中，然后可以将其用于识别其他跟踪数据中相同问题的实例。对于网络配置，该技术用作输入应用程序通信的网络级数据包跟踪，并从中提取一组特征。在培训阶段，每个应用程序运行都会手动标记为GOOD或BAD，具体取决于运行是否成功。然后，该技术采用学习技术来构建分类树，不仅可以区分GOOD和BAD运行，而且还将BAD运行次分类到不同类别的故障中。一旦学习了分类树，就可以通过将树从根移到每个叶来提取问题签名。

4. 发明申请

US20110282932A1 ASYMMETRIC END HOST REDUNDANCY ELIMINATION FOR NETWORKS 有权
标题翻译：不平等的终端主机对网络的排除
公开(公告)号：US20110282932A1
公开(公告)日：2011-11-17
申请号：US12781782
申请日：2010-05-17
申请人： Ramachandran Ramjee , Bhavish Aggarwal , Pushkar Chitnis , George Varghese , Ashok Anand , Chitra Muthukrishnan , Athula Balachandran
发明人： Ramachandran Ramjee , Bhavish Aggarwal , Pushkar Chitnis , George Varghese , Ashok Anand , Chitra Muthukrishnan , Athula Balachandran
IPC分类号： G06F15/16
CPC分类号： H04L67/1002
摘要： An end host redundancy elimination system and method to provide redundancy elimination as an end system service. Embodiments of the system and method use optimization techniques that reduce server central processing unit (CPU) load and memory footprint as compared to existing approaches. For server storage, embodiments of the system and method use a suite of highly-optimized data structures for managing metadata and cached payloads. An optimized asymmetric max-match technique exploits the inherent structure in data maintained at the server and client and ensures that client processing load is negligible. A load-adaptive fingerprinting technique is used that is much faster than current fingerprinting techniques while still delivering similar compression. Load-adaptive means that embodiments of the fingerprinting technique can adapt CPU usage depending on server load. Embodiments of the system and method operate above the transmission control protocol (TCP) layer, thereby reducing the number of roundtrips needed for data transfer.
摘要翻译：终端主机冗余消除系统和方法，作为终端系统服务提供冗余消除。与现有方法相比，系统和方法的实施例使用减少服务器中央处理单元（CPU）负载和存储器占用的优化技术。对于服务器存储，系统和方法的实施例使用一组高度优化的数据结构来管理元数据和缓存的有效载荷。优化的非对称最大匹配技术利用了在服务器和客户机上维护的数据的固有结构，并确保客户端处理负载可以忽略不计。使用比当前指纹技术更快的负载自适应指纹技术，同时仍然提供类似的压缩。负载自适应意味着指纹技术的实施例可以根据服务器负载来调整CPU使用。系统和方法的实施例在传输控制协议（TCP）层之上操作，从而减少数据传输所需的往返次数。

5. 发明申请

US20090323516A1 DIAGNOSING NETWORK PROBLEMS 审中-公开
标题翻译：诊断网络问题
公开(公告)号：US20090323516A1
公开(公告)日：2009-12-31
申请号：US12147522
申请日：2008-06-27
申请人： Ranjita Bhagwan , Bhavish Aggarwal , Venkata N. Padmanabhan , Geoffrey M. Voelker
发明人： Ranjita Bhagwan , Bhavish Aggarwal , Venkata N. Padmanabhan , Geoffrey M. Voelker
IPC分类号： G06F11/00
CPC分类号： H04L41/0866 , H04L41/0636 , H04L41/0853 , H04L41/0856
摘要： The method collects configuration data about the network, compares it to known good configurations to see if a corrective configuration is available. In addition, the method will review known bad configurations and determine if any of the successful corrective configurations for the bad configuration would be appropriate for the bad configuration under consideration.
摘要翻译：该方法收集有关网络的配置数据，将其与已知的良好配置进行比较，以查看校正配置是否可用。此外，该方法将检查已知的不良配置，并确定坏配置的成功校正配置是否适合所考虑的不良配置。

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