Distributed application framework for prioritizing network traffic using application priority awareness

    公开(公告)号:US10805235B2

    公开(公告)日:2020-10-13

    申请号:US15792635

    申请日:2017-10-24

    Abstract: A system and a method for prioritizing network traffic using application awareness and network awareness in a network environment is disclosed. An exemplary method can include receiving a network traffic priority for network traffic associated with a job performed by a distributed application; and based on the network traffic priority, assigning the network traffic to a network classification model, such as an access control list, associated with a network element for directing the network traffic in a network. The network classification model is associated with a network traffic priority class having defined quality of service (QoS) features, such that the network traffic traverses the network according to the defined QoS features.

    OPTIMIZING PLACEMENT OF VIRTUAL MACHINES
    3.
    发明申请
    OPTIMIZING PLACEMENT OF VIRTUAL MACHINES 有权
    优化虚拟机配置

    公开(公告)号:US20150127834A1

    公开(公告)日:2015-05-07

    申请号:US14242131

    申请日:2014-04-01

    CPC classification number: H04L47/78 G06F9/5044

    Abstract: Systems and methods are described for allocating resources in a cloud computing environment. The method includes receiving a computing request, the request for use of at least one virtual machine and a portion of memory. In response to the request, a plurality of hosts is identified and a cost function is formulated using at least a portion of those hosts. Based on the cost function, at least one host that is capable of hosting the virtual machine and memory is selected.

    Abstract translation: 描述了在云计算环境中分配资源的系统和方法。 该方法包括接收计算请求,使用至少一个虚拟机的请求和一部分存储器。 响应于该请求,识别多个主机,并且使用这些主机的至少一部分来表示成本函数。 基于成本函数,选择能够托管虚拟机和存储器的至少一个主机。

    Distributed application framework that uses network and application awareness for placing data

    公开(公告)号:US10050862B2

    公开(公告)日:2018-08-14

    申请号:US14617591

    申请日:2015-02-09

    Abstract: A distributed application framework, along with related systems and/or methods described herein, can intelligently place data using network knowledge. An exemplary method can include receiving data placement information from a distributed application that identifies a source node of data in a network and a list of potential destination nodes in the network for the distributed application to place the data; for each potential destination node, determining a network latency associated with transferring the data from the source node to the potential destination node using network metrics associated with the network; and sending the determined network latencies to the distributed application, such that the distributed application can assign the data to one of the potential destination nodes based on the determined network latencies.

    OPTIMIZED HADOOP TASK SCHEDULER IN AN OPTIMALLY PLACED VIRTUALIZED HADOOP CLUSTER USING NETWORK COST OPTIMIZATIONS
    6.
    发明申请
    OPTIMIZED HADOOP TASK SCHEDULER IN AN OPTIMALLY PLACED VIRTUALIZED HADOOP CLUSTER USING NETWORK COST OPTIMIZATIONS 审中-公开
    优化的HADOOP任务调度器在使用网络成本优化的最佳配置虚拟化HADOOP集群中

    公开(公告)号:US20160350146A1

    公开(公告)日:2016-12-01

    申请号:US14726336

    申请日:2015-05-29

    Abstract: The present disclosure describes, among other things, a method for optimizing task scheduling in an optimally placed virtualized cluster using network cost optimizations. The method comprises computing a first network cost matrix for a plurality of available physical nodes, determining a first solution to a first optimization problem of virtual machine placement onto the plurality of available physical nodes based on the first network cost matrix, wherein the first solution comprises one or more optimally placed virtual machines, computing a second network cost matrix for allocating one or more tasks to one or more possible optimally placed virtual machines of the first solution, and determining a second solution to a second optimization problem of task allocation onto one or more possible optimally placed virtual machines of the first solution based on the second network cost matrix.

    Abstract translation: 本公开尤其描述了一种使用网络成本优化在优化的虚拟化集群中优化任务调度的方法。 该方法包括计算多个可用物理节点的第一网络成本矩阵,基于第一网络成本矩阵来确定虚拟机放置到多个可用物理节点上的第一优化问题的第一解决方案,其中第一解决方案包括 一个或多个优化放置的虚拟机,计算用于将一个或多个任务分配给所述第一解决方案的一个或多个可能的最佳放置的虚拟机的第二网络成本矩阵,以及确定任务分配到一个或多个任务上的第二优化问题的第二解决方案 基于第二网络成本矩阵的第一解决方案的更可能的最佳放置的虚拟机。

    DISTRIBUTED APPLICATION FRAMEWORK FOR PRIORITIZING NETWORK TRAFFIC USING APPLICATION PRIORITY AWARENESS
    7.
    发明申请
    DISTRIBUTED APPLICATION FRAMEWORK FOR PRIORITIZING NETWORK TRAFFIC USING APPLICATION PRIORITY AWARENESS 有权
    分布式应用框架,优先使用应用程序优先认知的网络交通

    公开(公告)号:US20160094480A1

    公开(公告)日:2016-03-31

    申请号:US14499000

    申请日:2014-09-26

    CPC classification number: H04L47/805 H04L47/12 H04L47/2441 H04L47/2475

    Abstract: A system and a method for prioritizing network traffic using application awareness and network awareness in a network environment is disclosed. An exemplary method can include receiving a network traffic priority for network traffic associated with a job performed by a distributed application; and based on the network traffic priority, assigning the network traffic to a network classification model, such as an access control list, associated with a network element for directing the network traffic in a network. The network classification model is associated with a network traffic priority class having defined quality of service (QoS) features, such that the network traffic traverses the network according to the defined QoS features.

    Abstract translation: 公开了一种在网络环境中使用应用意识和网络意识来优先化网络流量的系统和方法。 示例性方法可以包括:接收与由分布式应用执行的作业相关联的网络流量的网络流量优先级; 并且基于网络流量优先级,将网络流量分配给与网络元件相关联的诸如访问控制列表的网络分类模型,用于将网络流量引导到网络中。 网络分类模型与具有定义的服务质量(QoS)特征的网络流量优先级相关联,使得网络流量根据定义的QoS特征穿越网络。

    OPTIMIZING PLACEMENT OF VIRTUAL MACHINES
    10.
    发明申请

    公开(公告)号:US20170346759A1

    公开(公告)日:2017-11-30

    申请号:US15682091

    申请日:2017-08-21

    Abstract: Systems and methods are described for allocating resources in a cloud computing environment. The method includes receiving a computing request, the request for use of at least one virtual machine and a portion of memory. In response to the request, a plurality of hosts is identified and a cost function is formulated using at least a portion of those hosts. Based on the cost function, at least one host that is capable of hosting the virtual machine and memory is selected.

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