Abstract: The technologies described herein are generally directed to placing edge hub equipment for virtual radio access networks based on resource availability and performance in advanced networks, such as a fifth generation (5G) network or other next generation networks. For example, a method described herein can include receiving a request to select, for deployment of hub equipment, between site locations, with the deployment of the hub equipment being to connect, in a fronthaul segment, radio unit equipment of the network at a radio location to a backhaul connection equipment. The method can further include, based on the request, the radio location, and the backhaul location, comparing a characteristic of the site locations. Further, the method can include responding to the request with a selected site location that was selected based on a result of the comparing.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a request for a communication service from a user equipment, based on the obtaining of the request, assigning a first identifier to the user equipment as part of the communication service, obtaining first data from the user equipment as part of the communication service, analyzing at least the first data in accordance with at least one algorithm to determine that the user equipment is likely misconfigured in an amount that is greater than a threshold, resulting in a determination, based on the determination, mapping the first identifier to a second identifier associated with the user equipment, generating a message based on the mapping, and transmitting the message. Other embodiments are disclosed.

Abstract: A processing system may obtain a first sampled flow record for a first flow in a network, comprising information regarding selected packets of the first flow, derive, from the first sampled flow record, a data volume and a duration of the first flow, and determine a first flow metric for the first flow that is calculated from the data volume and the duration, where the first flow metric is one of a plurality of flow metrics for a plurality of flows, and where the plurality of flow metrics is determined from the plurality of sampled flow records associated with the plurality of flows. The processing system may then classify the first flow into one of at least two classes, based upon the first flow metric and at least a first flow metric threshold.

Abstract: A radio access network intelligent controller (RIC) can comprise a physical resource block (PRB) scheduler that can facilitate the streaming of videos. When a user equipment (UE) requests a video, the PRB scheduler can take into account channel quality data associated with the connection between the UE and a distributed unit of a base station. The PRB scheduler can also receive video stream rate information from a video server. Based on the video stream rate information and the channel quality data, the PRB scheduler can make a decision regarding what types of videos to facilitate streaming to the UE.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.

Abstract: Intelligent network probe placement optimization (e.g., using a computerized tool) is enabled. A method can comprise determining, from an inventory database, physical interfaces and service paths for data traffic to be monitored, according to a two-way active management protocol, with respect to network interfaces between cloud compute elements in a leaf-spine cloud fabric and radio access network equipment, based on the cloud compute elements, determining directed acyclic graph information representative of a directed acyclic graph of connections between the cloud compute elements and other cloud compute elements in the leaf-spine cloud fabric other than the cloud compute elements, and based on the directed acyclic graph information, determining a number and a distribution of probes to be employed at at least some of the physical interfaces and the service paths to monitor a parameter of the data traffic according to the two-way active management protocol.

Abstract: Intelligent network probe placement optimization (e.g., using a computerized tool) is enabled. A method can comprise determining, from an inventory database, physical interfaces and service paths for data traffic to be monitored, according to a two-way active management protocol, with respect to network interfaces between cloud compute elements in a leaf-spine cloud fabric and radio access network equipment, based on the cloud compute elements, determining directed acyclic graph information representative of a directed acyclic graph of connections between the cloud compute elements and other cloud compute elements in the leaf-spine cloud fabric other than the cloud compute elements, and based on the directed acyclic graph information, determining a number and a distribution of probes to be employed at at least some of the physical interfaces and the service paths to monitor a parameter of the data traffic according to the two-way active management protocol.

Abstract: Misconfigured user equipment (UE) can cause additional traffic generation to server devices (e.g., 911 server device) and overload the server devices. Thus, detecting these UEs and blocking them before they hit the application servers in the mobility network can be facilitated via an identification and blocking approach. The system can comprise an identification correlator that can correlate S1 interface application protocol identification (S1-APID) associated with the UE to an international mobile subscriber identity (IMSI) of the UE. When the identification correlator collects data feeds from a network, the identification correlator can share this data with a call data record engine to determine if the UE is a misconfigured UE and prompt the network core to drop/block the misconfigured UE from a communication.

Abstract: A device includes a processor and a memory. The processor effectuates operations including monitoring enterprise network traffic associated with one or more user equipment (UE). The processor further effectuates operations including comparing the enterprise network traffic to a UE profile associated with each of the one or more UE. The processor further effectuates operations including determining whether the comparison indicates that a predetermined threshold has been exceeded. The processor further effectuates operations including in response to the indication that the predetermined threshold has been exceeded, generating an alert, wherein exceeding the predetermined threshold is indicative of a denial of service attack on an enterprise network or an attempt to remove enterprise data via the one or more UE.

Abstract: A radio access network intelligent controller (RIC) can comprise a physical resource block (PRB) scheduler that can facilitate the streaming of videos. When a user equipment (UE) requests a video, the PRB scheduler can take into account channel quality data associated with the connection between the UE and a distributed unit of a base station. The PRB scheduler can also receive video stream rate information from a video server. Based on the video stream rate information and the channel quality data, the PRB scheduler can make a decision regarding what types of videos to facilitate streaming to the UE.

Abstract: A device includes a processor and a memory. The processor effectuates operations including monitoring enterprise network traffic associated with one or more user equipment (UE). The processor further effectuates operations including comparing the enterprise network traffic to a UE profile associated with each of the one or more UE. The processor further effectuates operations including determining whether the comparison indicates that a predetermined threshold has been exceeded. The processor further effectuates operations including in response to the indication that the predetermined threshold has been exceeded, generating an alert, wherein exceeding the predetermined threshold is indicative of a denial of service attack on an enterprise network or an attempt to remove enterprise data via the one or more UE.

Abstract: A processing system may obtain a first sampled flow record for a first flow in a network, comprising information regarding selected packets of the first flow, derive, from the first sampled flow record, a data volume and a duration of the first flow, and determine a first flow metric for the first flow that is calculated from the data volume and the duration, where the first flow metric is one of a plurality of flow metrics for a plurality of flows, and where the plurality of flow metrics is determined from the plurality of sampled flow records associated with the plurality of flows. The processing system may then classify the first flow into one of at least two classes, based upon the first flow metric and at least a first flow metric threshold.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.

Abstract: The technologies described herein are generally directed to centralized management of wireless relay node equipment in a fifth generation (5G) or other next generation networks. In accordance with one or more embodiments, a method described herein can include facilitating identifying a connection between first network equipment and second network equipment, the first network equipment being connected to a user equipment and the second network equipment. In embodiments, the method can further include facilitating monitoring the connection between the first network equipment and the second network equipment, resulting in monitoring data, wherein the second network equipment is communicatively coupled to backhaul network equipment, and with the user equipment being communicatively coupled to the backhaul network equipment via the second network equipment. Further, based on the monitoring data, adjusting, by the centralized controller system, a characteristic of the connection, in accordance with embodiments.

Abstract: The present disclosure describes detection and mitigation of malicious wireless devices, in a wireless communication network including a radio access network (RAN) and a core network (CN), in a manner for selectively preventing the malicious wireless devices from using the wireless communication network based on identification of the malicious wireless devices in the wireless communication network. In one example, detection and mitigation of malicious wireless devices may include detecting a malicious wireless device based on identification of malicious activity by the malicious wireless device, identifying the malicious wireless device within the RAN based on correlation of one or more CN-based identifiers of the malicious wireless device within the CN and one or more RAN-based identifiers of the malicious wireless device within the RAN, and preventing the malicious wireless device from using the wireless communication network based on the one or more RAN-based identifiers of the malicious wireless device.

Abstract: A device includes a processor and a memory. The processor effectuates operations including monitoring enterprise network traffic associated with one or more user equipment (UE). The processor further effectuates operations including comparing the enterprise network traffic to a UE profile associated with each of the one or more UE. The processor further effectuates operations including determining whether the comparison indicates that a predetermined threshold has been exceeded. The processor further effectuates operations including in response to the indication that the predetermined threshold has been exceeded, generating an alert, wherein exceeding the predetermined threshold is indicative of a denial of service attack on an enterprise network or an attempt to remove enterprise data via the one or more UE.

Abstract: The technologies described herein are generally directed to centralized management of wireless relay node equipment in a fifth generation (5G) or other next generation networks. In accordance with one or more embodiments, a method described herein can include facilitating identifying a connection between first network equipment and second network equipment, the first network equipment being connected to a user equipment and the second network equipment. In embodiments, the method can further include facilitating monitoring the connection between the first network equipment and the second network equipment, resulting in monitoring data, wherein the second network equipment is communicatively coupled to backhaul network equipment, and with the user equipment being communicatively coupled to the backhaul network equipment via the second network equipment. Further, based on the monitoring data, adjusting, by the centralized controller system, a characteristic of the connection, in accordance with embodiments.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.

Abstract: Mobility service providers and others can use cloud platforms to meet customer demand. Due to changing demand or changing technology numerous issues arise. For example, server utilization within the cloud platform can become less efficient over time. As another example, virtual machines and virtual network functions processed by the cloud platform typically need to be extensively tested and certified, which can be expensive. Moreover, intra-platform communication can play a significant role in the costs to operate a cloud platform. Techniques detailed herein can address many of these issues, e.g., by providing mechanisms for increasing host or server utilization in response to changing demand, introducing a container technique for virtual machines to mitigate testing costs, and modeling bandwidth resources.