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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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: 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.