Abstract: An Internet of Things (IoT) topology analyzer includes an input to passively receive packets exchanged between IoT devices operating within a network and at least one IoT server connected to the network. A processor is coupled to the input and is configured to determine a number of IoT devices operating within the network based on the received packets, with the number of IoT devices used to define an IoT topology of the network.

Abstract: Techniques proactively deploy analytics to a computerized edge device. The techniques involve receiving data from the edge device. The data is conveyed through the edge device from a set of sensors disposed at a particular location. The techniques further involve performing analytics on the data to identify a set of edge device rules that defines a set of actions for the edge device to carry out under a set of predefined conditions potentially sensed by the set of sensors. The techniques further involve providing a command to the edge device. The command (i) includes the set of edge device rules and (ii) directs the edge device to, at a future time, start operating according to the set of edge device rules to protect against unsuccessful deployment of the command to the edge device due to subsequent delayed communication between the processing circuitry and the edge device.

Abstract: Systems and methods for identifying a new device in an internet of things (IoT) network comprising a plurality of devices. The method includes, by a processor: detecting that a new device has been added to the IoT network; receiving identification data corresponding to the new device; determining a first device identification using a deep learning algorithm; determining a second device identification using a clustering algorithm; determining a third device identification based on a reference table; determining a fourth device identification by analyzing one or more values included in the identification data. The method further includes selecting, at least one of the first device identification, the second device identification, the third device identification, or the fourth device identification, as a final device identification by performing a weighted selection.

Abstract: A system for optimizing network traffic is described. An appliance operates within a cluster of appliances. The appliance includes one or more network interfaces to facilitate a first secure session between a client device and the appliance, and a second secure session between the appliance and a server. One of the network interfaces is configured to receive a secure connection request to the server. A secure session exchange module acquires a message from another appliance, with the message indicating that the other appliance is acting as a primary instance for the server. The secure session exchange module determines whether a valid primary instance for the server exist, and requests from the other appliance at least one session-related parameter based on determination of existence of the valid primary instance for the server. A session to the server is used based on at least one session-related parameter acquired from the other appliance.

Abstract: Described embodiments provide systems and methods for initiating establishment of a connection. The system may include a device intermediary between a client and a server. The device may determine at least one server name indicator (SNI) for an application executing on the client and having a secure session established with the server. The device may determine, for each domain name corresponding to the at least one SNI, a session timeout value for the corresponding domain name. The device may send a message to the client according to each session timeout value, to cause the client to initiate establishment of a connection for the corresponding domain name using the secure session.

Abstract: Described embodiments provide systems and methods for initiating establishment of a connection. The system may include a device intermediary between a client and a server. The device may determine at least one server name indicator (SNI) for an application executing on the client and having a secure session established with the server. The device may determine, for each domain name corresponding to the at least one SNI, a session timeout value for the corresponding domain name. The device may send a message to the client according to each session timeout value, to cause the client to initiate establishment of a connection for the corresponding domain name using the secure session.

Abstract: The present disclosure discloses a system that automatically identifies the most efficient times to upgrade software associated with an IoT device. The system employs machine-learning mechanisms to precisely identify the specific time interval where there will be the least impact on the functionality of the IoT device or a cluster of IoT devices.

Abstract: A device for an Internet of Things (IoT) workspace monitors the IoT workspace to determine a change in a number of IoT devices operating within the IoT workspace. A respective topology of the IoT workspace is determined based the number of IoT devices operating in the IoT workspace. The IoT devices based on each topology are mapped, with each map identifying locations of the IoT devices within the IoT workspace. Relationships and dependencies are determined between the IoT devices for each map. A weight is assigned to each IoT device based on the determined relationships and dependencies for each map. The assigned weights of the changed number of IoT devices are compared to the assigned weights of the IoT devices operating before the change so as to quantify an impact of the change in the IoT workspace.

Abstract: A device for an Internet of Things (IoT) workspace monitors the IoT workspace to determine a change in a number of IoT devices operating within the IoT workspace. A respective topology of the IoT workspace is determined based the number of IoT devices operating in the IoT workspace. The IoT devices based on each topology are mapped, with each map identifying locations of the IoT devices within the IoT workspace. Relationships and dependencies are determined between the IoT devices for each map. A weight is assigned to each IoT device based on the determined relationships and dependencies for each map. The assigned weights of the changed number of IoT devices are compared to the assigned weights of the IoT devices operating before the change so as to quantify an impact of the change in the IoT workspace.

Abstract: An Internet of Things (IoT) topology analyzer includes an input to passively receive packets exchanged between IoT devices operating within a network and at least one IoT server connected to the network. A processor is coupled to the input and is configured to determine a number of IoT devices operating within the network based on the received packets, with the number of IoT devices used to define an IoT topology of the network.

Abstract: Techniques proactively deploy analytics to a computerized edge device. The techniques involve receiving data from the edge device. The data is conveyed through the edge device from a set of sensors disposed at a particular location. The techniques further involve performing analytics on the data to identify a set of edge device rules that defines a set of actions for the edge device to carry out under a set of predefined conditions potentially sensed by the set of sensors. The techniques further involve providing a command to the edge device. The command (i) includes the set of edge device rules and (ii) directs the edge device to, at a future time, start operating according to the set of edge device rules to protect against unsuccessful deployment of the command to the edge device due to subsequent delayed communication between the processing circuitry and the edge device.

Abstract: The present disclosure discloses a system that automatically identifies the most efficient times to upgrade software associated with an IoT device. The system employs machine-learning mechanisms to precisely identify the specific time interval where there will be the least impact on the functionality of the IoT device or a cluster of IoT devices.

Abstract: A system for optimizing network traffic is described. An appliance operates within a cluster of appliances. The appliance includes one or more network interfaces to facilitate a first secure session between a client device and the appliance, and a second secure session between the appliance and a server. One of the network interfaces is configured to receive a secure connection request to the server. A secure session exchange module acquires a message from another appliance, with the message indicating that the other appliance is acting as a primary instance for the server. The secure session exchange module determines whether a valid primary instance for the server exist, and requests from the other appliance at least one session-related parameter based on determination of existence of the valid primary instance for the server. A session to the server is used based on at least one session-related parameter acquired from the other appliance.

Abstract: Systems and methods for identifying a new device in an internet of things (IoT) network comprising a plurality of devices. The method includes, by a processor: detecting that a new device has been added to the IoT network; receiving identification data corresponding to the new device; determining a first device identification using a deep learning algorithm; determining a second device identification using a clustering algorithm; determining a third device identification based on a reference table; determining a fourth device identification by analyzing one or more values included in the identification data. The method further includes selecting, at least one of the first device identification, the second device identification, the third device identification, or the fourth device identification, as a final device identification by performing a weighted selection.

Abstract: The systems and methods discussed herein provide for a predictive monitoring technique to suppress data exchange between the client device or devices and the monitoring device or devices. Regression-based intelligent predictions systems executed both by the client device or devices and the monitoring device or devices perform identical prediction algorithms. If the predicted metric values and the actual measured metric values on the client device are very close, then the client device may skip transmitting the measured metric values to the monitoring device; similarly, if a measured metric value is not received by the monitoring device, then the monitoring device knows that the measured metric was similar to the predicted metric on the client device, and accordingly may utilize the predicted metric on the monitoring device. Because transmission of the measured metric values may be skipped, network traffic and interface and processor utilization is significantly decreased.

Abstract: A system for optimizing network traffic is described. The system includes a plurality of appliances, each having an SSL session exchange module. An appliance in active state is called a primary appliance, and one or more appliances in inactive state are called secondary appliances. An appliance of a cluster of appliances comprises a secure session exchange module and one or more network interfaces configured to facilitate a first secure session between a client device and the appliance and a second secure session between the appliance and a server. The secure session exchange module in a primary appliance is configured to provide a message for sending to one or more secondary appliances. The message indicates that the appliance is acting as a primary instance for a server. The secure session exchange module in the primary appliance is also configured to acquire at least one session-related parameter through a handshake procedure for a secure layer with the server.

Abstract: The systems and methods discussed herein provide for a predictive monitoring technique to suppress data exchange between the client device or devices and the monitoring device or devices. Regression-based intelligent predictions systems executed both by the client device or devices and the monitoring device or devices perform identical prediction algorithms. If the predicted metric values and the actual measured metric values on the client device are very close, then the client device may skip transmitting the measured metric values to the monitoring device; similarly, if a measured metric value is not received by the monitoring device, then the monitoring device knows that the measured metric was similar to the predicted metric on the client device, and accordingly may utilize the predicted metric on the monitoring device. Because transmission of the measured metric values may be skipped, network traffic and interface and processor utilization is significantly decreased.

Abstract: A secure session pre-handshake establishment module facilitates a secure session connection request between an appliance and a server associated with a website. The facilitation causes the appliance to receive session information. At least one session to one or more servers listed in a server group is reused if the session information corresponding to the secure session connection request has been cached. Secure session connections between the appliance and servers listed in the server group are formed if the session information corresponding to the secure session connection request has not been cached to pre-establish one or more SSL connections so that when one or more SSL connection requests are received, the one or more pre-established SSL connections can be used without performing full SSL handshake procedures.

Abstract: Described embodiments provide systems and methods for initiating establishment of a connection. The system may include a device intermediary between a client and a server. The device may determine at least one server name indicator (SNI) for an application executing on the client and having a secure session established with the server. The device may determine, for each domain name corresponding to the at least one SNI, a session timeout value for the corresponding domain name. The device may send a message to the client according to each session timeout value, to cause the client to initiate establishment of a connection for the corresponding domain name using the secure session.

Abstract: An appliance and a method of pre-establishing SSL session connections for SSL connection establishment are provided. The appliance comprises a secure session pre-handshake establishment module configured to facilitate a secure session connection between an appliance and a server associated with a website, wherein the facilitation causes the appliance to receive session information, determine whether session information corresponding to the secure session connection request has been cached, determine whether the server is associated with a server group based on the determination that session information has not been cached, and form secure session connections between the appliance and servers listed in the server group based on the determination that the server is associated with a server group.