Hewlett Packard Enterprise Development LP

Aruba Networks, Inc.

Ataur Rehman

Manaswini Lakshmikanth Sugatoor

Gopal Agarwal

Manas Sharma

Pradeep Iyer

Gopal Gupta

Abhishek Mishra

Brijesh Kumar Yadav

Ganesh Valluru Ramakrishnappa

Abhinesh Mishra

A method for managing bandwidth may include identifying a first tier of applications and a second tier of applications, determining a number of user sessions associated with at least one application among the first tier of applications and the second tier of applications, each user session consuming a percentage of bandwidth of at least one communication channel in a network, and baselining a second tier application bandwidth use for each user session associated with the second tier of applications to determine a first interval and a second interval. The method may also include calculating a second tier application usage score associated with the second tier of applications, the calculating including determining a percentage of bandwidth used by the second tier of applications in the first interval and determining a percentage of bandwidth used by the second tier of applications in the second interval, generating a user score based on the second tier application usage score and a percentage of use of the first tier of applications, and adjusting a bandwidth allocation based on the user score.

Managing bandwidth based on user behavior

A method for classifying devices may include determining that a device is located at a location for more than a threshold amount of time and identifying that the device is a moving candidate based on a percentage of times a plurality of signal strength values for the device fall inside a baseline interval. The method may also include determining a most frequent pattern set of signal strength values for the device, classifying the device as fixed if the most frequent pattern set of signal strength values for the device includes at least one overlapping interval, and classifying the device as moving if the most frequent pattern set of signal strength values for the device includes at least one non-overlapping interval.

Identifying fixed WLAN devices using mobility patterns

An example non-transitory, computer-readable medium includes instructions that cause a device to determine, for uplinks of a branch gateway, a link health baseline. The instructions further cause the device to determine, for a set of criticality classes, a class link health baseline for each link health baseline, based on the link health baseline and a tolerance level of each criticality class. The instructions further cause the device to calculate, based in part on weighted parameters of the class link health baselines and an uplink cost, a path quality threshold score for each application category and for each uplink. The instructions further cause the device to select, for each application category, a primary uplink and a secondary uplink based on the path quality threshold scores. The instructions further cause the device to route network traffic through the primary uplink of the application category assigned to the network traffic.

Uplink selection in a SD-WAN

Example method includes: receiving, by a network device, a plurality of signal strength values associated with a particular timestamp corresponding to a particular client device from a plurality of access points in a wireless network at a site; determining a mobility pattern based on the plurality of signal strength values associated with the particular timestamp corresponding to the particular client device; comparing the mobility pattern associated with the particular timestamp corresponding to the particular client device with mobility patterns associated with other timestamps or corresponding to other client devices to identify a set of frequent mobility patterns; determining whether an unassociated client device exhibits a threshold number of frequent mobility patterns for a threshold amount of time; and determining that the unassociated client device presents in the site in response to the unassociated client device exhibiting the threshold number of the frequent mobility patterns for the threshold amount of time.

Determining that a client device presents in a site using frequent client mobility patterns

Aspects of categorizing MAC address randomization include obtaining probe data for a plurality of time intervals. A likelihood measure of a specified OS type and version belonging to each of a plurality of MAC address randomization categories is determined and the specified OS type and version is categorized based on the likelihood measure.

Categorization of MAC address randomization

In some examples, a non-transitory computer-readable medium may contain instructions executable by a processing resource to collect Wi-Fi data points. The Wi-Fi data points may correspond to a plurality of users of an enterprise for a particular number of days. In some examples, the Wi-Fi data points may indicate a time period during each of the particular number of days when each of the plurality of users was connected to a Wi-Fi network. Instructions may further be executable to determine that a subset of the Wi-Fi data points represent outliers and remove the subset of Wi-Fi data points to create a data set. The data set may comprise non-outlier Wi-Fi data points. Instructions may further be executable to determine a Wi-Fi Adoption Index (WAI) for each of the plurality of users based on the data set.

Wi-Fi adoption index

Example implementations relate to network deployment of devices. For example, a non-transitory computer readable medium storing instructions executable by a processing resource can determine a plurality of deployment thresholds of a plurality of devices, wherein the plurality of deployment thresholds are associated with a type of the plurality of devices. The instructions can cause the processing resource to monitor deployment data associated with the plurality of devices to identify a device with a deployment outlier. The device with the deployment outlier is a device with deployment data that is outside a deployment threshold of the device. The instructions can cause the processing resource to adjust the deployment threshold of the device based on the monitoring.

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Bengaluru, India

Ataur Rehman