公开(公告)号：US20160234071A1

公开(公告)日：2016-08-11

申请号：US14617591

申请日：2015-02-09

Applicant: CISCO TECHNOLOGY, INC.

Inventor： Raghunath O. Nambiar ,  Karthik Krishna Kulkarni

IPC: H04L12/24 ,  H04L12/26

CPC classification number: H04L45/00 ,  H04L43/08 ,  H04L45/123 ,  H04L45/306 ,  H04L47/125

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.

Abstract translation: 分布式应用框架以及本文描述的相关系统和/或方法可以使用网络知识来智能地放置数据。 示例性方法可以包括从分布式应用接收数据放置信息，所述分布式应用识别网络中的数据的源节点和用于分布式应用的网络中的潜在目的地节点的列表以放置数据; 对于每个潜在目的地节点，使用与所述网络相关联的网络度量来确定与从所述源节点传输所述数据到所述潜在目的地节点相关联的网络等待时间; 以及将确定的网络延迟发送到所述分布式应用，使得所述分布式应用可以基于所确定的网络延迟将所述数据分配给所述潜在目的地节点之一。

公开(公告)号：US09367344B2

公开(公告)日：2016-06-14

申请号：US14509691

申请日：2014-10-08

Applicant: CISCO TECHNOLOGY, INC.

Inventor： Yathiraj B. Udupi ,  Debojyoti Dutta ,  Madhav V. Marathe ,  Raghunath O. Nambiar

IPC: G06F9/455

CPC classification number: G06F9/45558 ,  G06F9/5066 ,  G06F2009/45562 ,  H04L47/78

Abstract: The present disclosure relates to assignment or generation of reducer virtual machines after the “map” phase is substantially complete in MapReduce. Instead of a priori placement, distribution of keys after the “map” phase over the mapper virtual machines can be used to efficiently reducer tasks in virtualized cloud infrastructure like OpenStack. By solving a constraint optimization problem, reducer VMs can be optimally assigned to process keys subject to certain constraints. In particular, the present disclosure describes a special variable matrix. Furthermore, the present disclosure describes several possible cost matrices for representing the costs determined based on the key distribution over the mapper VMs (and other suitable factors).

Abstract translation: 本公开涉及在MapReduce中的“映射”阶段基本完成之后分配或生成reducer虚拟机。 在映射器虚拟机上的“映射”阶段之后，可以使用OpenStack虚拟化云基础设施中的有效减少任务来代替先验位置分配密钥。 通过解决约束优化问题，可以将reducer VM最优化地分配给具有某些限制的处理密钥。 具体地，本公开描述了特殊变量矩阵。 此外，本公开描述了用于表示基于映射器VM上的密钥分布（和其他合适因素）确定的成本的几种可能的成本矩阵。

公开(公告)号：US20160103695A1

公开(公告)日：2016-04-14

申请号：US14509691

申请日：2014-10-08

Applicant: CISCO TECHNOLOGY, INC.

Inventor： Yathiraj B. Udupi ,  Debojyoti Dutta ,  Madhav V. Marathe ,  Raghunath O. Nambiar

IPC: G06F9/455

CPC classification number: G06F9/45558 ,  G06F9/5066 ,  G06F2009/45562 ,  H04L47/78

Abstract: The present disclosure relates to assignment or generation of reducer virtual machines after the “map” phase is substantially complete in MapReduce. Instead of a priori placement, distribution of keys after the “map” phase over the mapper virtual machines can be used to efficiently reducer tasks in virtualized cloud infrastructure like OpenStack. By solving a constraint optimization problem, reducer VMs can be optimally assigned to process keys subject to certain constraints. In particular, the present disclosure describes a special variable matrix. Furthermore, the present disclosure describes several possible cost matrices for representing the costs determined based on the key distribution over the mapper VMs (and other suitable factors).

Abstract translation: 本公开涉及在MapReduce中的“映射”阶段基本完成之后分配或生成reducer虚拟机。 在映射器虚拟机上的“映射”阶段之后，可以使用OpenStack虚拟化云基础设施中的有效减少任务来代替先验位置分配密钥。 通过解决约束优化问题，可以将reducer VM最优化地分配给具有某些限制的处理密钥。 具体地，本公开描述了特殊变量矩阵。 此外，本公开描述了用于表示基于映射器VM上的密钥分布（和其他合适因素）确定的成本的几种可能的成本矩阵。