Flow management and flow modeling in network clouds

Abstract

Assignment of network addresses and estimations of flow sizes associated with network nodes can be enhanced. Assignment management component (AMC) partitions a set of network addresses into subsets of network addresses associated with respective classes. For respective virtual machines (VMs), an estimator component estimates a flow size associated with a VM based on parameters associated with the VM. AMC classifies VMs based on threshold flow-size values and respective estimated flow sizes of VMs, and assigns VMs to respective sub-groups of VMs associated with respective subsets of network addresses based on respective classifications of VMs. AMC assigns an available network address of a subset of network addresses associated with a class to a VM of a sub-group associated with that class. Estimated flow sizes and performance metrics also are utilized to make determinations regarding VM placement, traffic management, load balancing, resource allocation, and orchestration in cloud networks.

What is claimed is: 
     
         1 . A method, comprising:
 determining, by a system comprising a processor, a flow size associated with a network node based on a characteristic associated with the network node; and   based on the flow size, determining, by the system, a network address that is to be assigned to the network node from a group of network addresses associated with a classification relating to a range of flow sizes.   
     
     
         2 . The method of  claim 1 , further comprising:
 in response to the determining of the network address to be assigned to the network node, assigning, by the system, the network address of the group of network addresses associated with the classification to the network node based on the flow size, wherein the flow size has been determined to be associated with the classification of a group of classifications comprising respective classifications relating to respective ranges of flow sizes, wherein the respective classifications comprise the classification, and wherein the respective ranges of flow sizes comprise the range of flow sizes.   
     
     
         3 . The method of  claim 1 , wherein the determining the network address that is to be assigned to the network node from the group of network addresses comprises determining the network address that is to be assigned to the network node from the group of network addresses based on a first available network address of the group of network addresses or a least used network address of the group of network addresses, and wherein the least used network address is determined to have been used less than other network addresses of the group of network addresses. 
     
     
         4 . The method of  claim 1 , wherein the network address is an Internet protocol address or a media access control address. 
     
     
         5 . The method of  claim 1 , further comprising:
 estimating, by the system, the flow size associated with the network node based on the characteristic associated with the network node, wherein the determining the flow size associated with the network node comprises determining the flow size associated with the network node based on the estimating of the flow size.   
     
     
         6 . The method of  claim 5 , further comprising:
 determining, by the system, a model of flow sizes associated with network nodes in relation to characteristics associated with the network nodes based on real flow sizes associated with network nodes, wherein the real flow sizes are measured, and   wherein the estimating the flow size associated with the network node based on the characteristic associated with the network node comprises estimating the flow size associated with the network node based on the characteristic associated with the network node and the model.   
     
     
         7 . The method of  claim 5 , wherein the network node is a virtual machine, and wherein the characteristic associated with the virtual machine comprises a number of virtual central processing units associated with the virtual machine, a flavor size associated with the virtual machine, a memory size associated with the virtual machine, a disk space associated with the virtual machine, a receive and transmit factor associated with the virtual machine, a swap space associated with the virtual machine, a first amount of volume storage associated with the virtual machine, a second amount of block storage associated with the virtual machine, a server characteristic of a server associated with the virtual machine, a hypervisor characteristic of a hypervisor associated with the virtual machine, or an application characteristic of an application associated with the virtual machine. 
     
     
         8 . The method of  claim 1 , further comprising:
 partitioning, by the system, network addresses into respective groups of network addresses, comprising the group of network addresses, based on respective characteristics associated with respective applications associated with respective network nodes, comprising the network node, wherein the respective groups of network addresses are associated with the respective classifications; and   classifying, by the system, the network node as being associated with the classification that is associated with the group of network addresses based on a result of comparing the flow size associated with the network node to respective threshold flow sizes associated with the respective classifications.   
     
     
         9 . The method of  claim 1 , wherein the group of network addresses comprises network addresses in a consecutive address order. 
     
     
         10 . The method of  claim 1 , wherein a function is applied to respective characteristics, comprising the characteristic, to facilitate estimating respective flow sizes, comprising the flow size, associated with respective network nodes, comprising the network node, and wherein the method further comprises:
 analyzing, by the system, the respective flow sizes and respective actual flow sizes associated with the respective network nodes;   determining, by the system, an amount of an error between the respective flow sizes and the respective actual flow sizes; and   adaptively modifying, by the system, the function to generate a modified function, based on the amount of the error, to mitigate the amount of the error.   
     
     
         11 . The method of  claim 1 , wherein the network node is a virtual machine, and wherein the method further comprises:
 estimating, by the system, performance metrics associated with virtual machines, comprising the virtual machine, based on characteristics, comprising the characteristic, associated with the virtual machines; and   determining, by the system, a placement of the virtual machine for a launching of the virtual machine by a server based on the flow size of the virtual machine, the performance metrics associated with the virtual machine, and resources of the server that are available to support an application associated with the virtual machine.   
     
     
         12 . The method of  claim 1 , further comprising:
 detecting, by the system, a deviation from the flow size associated with the network node during a defined time period;   determining, by the system, whether an amount of the deviation satisfies a defined threshold amount of deviation; and   in response to determining that the amount of the deviation satisfies the defined threshold amount of deviation, determining, by the system, that a defined anomaly has occurred with respect to a network associated with the network node, wherein the defined anomaly is an attack on the network or a network anomaly relating to a service failure associated with the network.   
     
     
         13 . A system, comprising:
 a processor; and   a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:
 determining a flow size associated with a network node based on an attribute associated with the network node; and 
 based on the flow size, determining, from a group of network addresses associated with a classification relating to a range of flow sizes, a network address that is to be assigned to the network node. 
   
     
     
         14 . The system of  claim 13 , wherein the operations further comprise:
 predicting the flow size associated with the network node based on the attribute associated with the network node, wherein the determining the flow size associated with the network node comprises determining the flow size associated with the network node based on the predicting of the flow size associated with the network node.   
     
     
         15 . The system of  claim 14 , wherein the network node is a virtual machine, and wherein the attribute comprises a flavor size, a number of virtual central processing units, a memory size, a disk space, a communication bandwidth factor, a swap space, a first amount of volume storage, a second amount of block storage, a server-related attribute associated with a server, a hypervisor-related attribute associated with a hypervisor, or an application-related attribute associated with an application executable by the virtual machine. 
     
     
         16 . The system of  claim 13 , wherein the network address is an Internet protocol address or a media access control address. 
     
     
         17 . The system of  claim 13 , wherein the operations further comprise:
 partitioning network addresses into respective groups of network addresses, comprising the group of network addresses, based on respective application-related attributes associated with respective applications associated with respective network nodes, comprising the network node, wherein the respective groups of network addresses are associated with respective classifications relating to respective ranges of flow sizes, wherein the respective classifications comprise the classification, and wherein the respective ranges of flow sizes comprise the range of flow sizes; and   determining that the network node is associated with the classification that is associated with the group of network addresses based on a result of evaluating the flow size associated with the network node and respective threshold flow sizes associated with the respective classifications.   
     
     
         18 . The system of  claim 13 , wherein the operations further comprise:
 determining first data traffic processing rules that are determined to be able to provide first flow-aggregated measurements that facilitate first estimations of flow sizes associated with respective network nodes with a first accuracy that is higher than a second accuracy of second estimations of the flow sizes associated with the respective network nodes that are able to be obtained from second flow-aggregated measurements using second data traffic processing rules; and   facilitating application of the first data traffic processing rules to facilitate enhanced accuracy in further estimations of the flow sizes associated with the network nodes.   
     
     
         19 . A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor, facilitate performance of operations, comprising:
 determining a flow amount associated with a network node based on a characteristic associated with the network node; and   based on the flow amount, assigning, from a group of network addresses associated with a classification that is associated with a range of flow amounts, a network address to the network node.   
     
     
         20 . The non-transitory machine-readable medium of  claim 19 , wherein the operations further comprise:
 partitioning network addresses into respective groups of network addresses, comprising the group of network addresses, based on respective attributes associated with respective applications associated with respective network nodes, comprising the network node, wherein the respective groups of network addresses are associated with respective classifications that are associated with respective ranges of flow amounts, wherein the respective classifications comprise the classification, and wherein the respective ranges of flow amounts comprise the range of flow amounts; and   determining that the network node is associated with the classification that is associated with the group of network addresses based on a result of comparing the flow amount associated with the network node to respective threshold flow amounts associated with the respective classifications.