Abstract: The invention provides methods, systems and computer program products for job management and for allocating resources for cloud based or remote device based job processing. The invention provides a scalable architecture for job management and for allocating resources for cloud based or remote device based job processing comprising a job manager machine, having a resource pool of secondary job manager machines assigned thereto. The job manager machine has a resource pool of computing machines assigned thereto—comprising at least a gateway machine and a non-gateway machine. Received jobs or computing tasks are selectively transmitted to one of the gateway machine and the non-gateway machine. Each of the gateway machine and the non-gateway machine are configured to respond differently to forwarded job or computing task.

Abstract: The invention provides methods, systems and computer program products for job management and for allocating resources for cloud based or remote device based job processing. The invention provides a scalable architecture for job management and for allocating resources for cloud based or remote device based job processing comprising a primary job manager machine, having a resource pool of secondary job manager machines assigned thereto. Each secondary job manager machine has a resource pool of computing machines assigned thereto—for execution jobs or computing tasks assigned to the secondary job manager machine by the primary job manager machine. In an embodiment, each secondary job manager machine has one or more accelerator cache proxies for enabling low latency data object retrieval for computing tasks being executed by the computing machines assigned to the secondary job manager.

Abstract: A method of validating a desired image of a virtualization software and a firmware package to be installed in a host against a hardware compatibility list (HCL) includes: acquiring a bill of materials for the host that lists hardware devices of the host; for each of the hardware devices, searching for firmware and a driver thereof in the HCL; for each driver included in the desired image that corresponds to one of the hardware devices, determining whether or not the driver is compatible according to the HCL; for each firmware included in the firmware package that corresponds to one of the hardware devices, determining whether or not the firmware is compatible according to the HCL; and validating the desired image of the virtualization software and the firmware package to be installed in the host if each of the hardware devices has a compatible driver and a compatible firmware.

Abstract: The principal object of the embodiments herein is to disclose predictive capacity analysis and pro-active performance bottleneck identification using multivariate machine learning techniques for efficient network capacity expansion and optimization to enhance customer experience by improving quality of service (QoS) while ensuring better return of investment (ROI).

Abstract: A method of validating a desired image of a virtualization software and a firmware package to be installed in a host against a hardware compatibility list (HCL) includes: acquiring a bill of materials for the host that list hardware devices of the host; for each of the hardware devices, searching for firmware and driver thereof in the HCL; for each driver included in the desired image that corresponds to one of the hardware devices, determining whether or not the driver is compatible according to the HCL; for each firmware included in the firmware package that corresponds to one of the hardware devices, determining whether or not the firmware is compatible according to the HCL; and validating the desired image of the virtualization software and the firmware package to be installed in the host if each of the hardware device has a compatible driver and a compatible firmware.

Abstract: A method of validating a desired image of a virtualization software and a firmware package to be installed in a plurality of hosts against a hardware compatibility list (HCL) includes: acquiring hardware inventory of the hosts to determine hardware devices installed therein; for each of the hardware devices, searching for firmware and driver thereof in the HCL; for each driver included in the desired image that corresponds to one of the hardware devices, determining whether or not the driver is compatible according to the HCL; for each firmware included in the firmware package that corresponds to one of the hardware devices, determining whether or not the firmware is compatible according to the HCL; and validating the desired image of the virtualization software and the firmware package to be installed in the hosts if each of the hardware device has a compatible driver and a compatible firmware.

Abstract: The invention provides systems, methods and computer program products for executing remote application iteration(s) of client application software on a remote server platform, and for enabling each remote application iteration of a client application software to have access to a corresponding instance of an application software environment that contains or otherwise has access to data object(s) necessary for execution of the remote application iteration. The invention additionally enables execution of a remote application iteration of a client software application at a remote server platform, through need-based or dynamic retrieval of data objects from an on-premise device for provisioning (on the remote platform server) an instance of the client software application environment required for execution of the remote application iteration of the client software application.

Abstract: A method of validating a desired image of a virtualization software and a firmware package to be installed in a plurality of hosts against a hardware compatibility list (HCL) includes: acquiring hardware inventory of the hosts to determine hardware devices installed therein; for each of the hardware devices, searching for firmware and driver thereof in the HCL; for each driver included in the desired image that corresponds to one of the hardware devices, determining whether or not the driver is compatible according to the HCL; for each firmware included in the firmware package that corresponds to one of the hardware devices, determining whether or not the firmware is compatible according to the HCL; and validating the desired image of the virtualization software and the firmware package to be installed in the hosts if each of the hardware device has a compatible driver and a compatible firmware.

Abstract: The invention provides systems, methods and computer program products for executing remote application iteration(s) of client application software on a remote server platform, and for enabling each remote application iteration of a client application software to have access to a corresponding instance of an application software environment that contains or otherwise has access to data object(s) necessary for execution of the remote application iteration. The invention additionally enables execution of a remote application iteration of a client software application at a remote server platform, through need-based or dynamic retrieval of data objects from an on-premise device for provisioning (on the remote platform server) an instance of the client software application environment required for execution of the remote application iteration of the client software application.

Abstract: A system, method, and computer program product are provided for performing intelligent RAN energy management. In operation, a system correlates information including site configuration details, RAN attributes, and energy consumption attributes for each of a plurality of areas including sites, clusters, or zones. The system assigns each of the plurality of areas to one of a plurality of categories based on similar characteristics including associated site configuration details and RAN attributes. Further, the system identifies one of more of a plurality of sites in each of the plurality of categories as bad for energy consumption based on the energy consumption attributes associated with a particular category.

Abstract: A system, method, and computer program product are provided for utilizing radio access network (RAN) information and mobile backhaul (MBH) network information to assess network site performance. In operation, a system receives information associated with a radio access network. Additionally, the system receives information associated with a mobile backhaul network corresponding to the radio access network. The system correlates the information associated with the radio access network with the information associated with the mobile backhaul network to create correlated information. Further, the system calculates scores for the correlated information. Moreover, the system calculates a score for a site associated with the mobile backhaul network utilizing the scores for the correlated information.

Abstract: Tracing of networking feature data may be provided for networking features running on network devices such as routers and switches. Examples of this feature tracing include “SGT tracing”, “Access Control Entry (‘ACE’) tracing”, and “Equal Cost Multipath (‘ECMP’) tracing.” In ACE tracing, a network administrator may desire to trace all the ACEs of Access Control Lists (“ACLs”) a particular packet is subject to. In ECMP, tracing information may be collected as to the ECMP links a particular packet is sent through at each of a plurality of network devices.

Abstract: Tracing of networking feature data may be provided for networking features running on network devices such as routers and switches. Examples of this feature tracing include “SGT tracing”, “Access Control Entry (‘ACE’) tracing”, and “Equal Cost Multipath (‘ECMP’) tracing.” In ACE tracing, a network administrator may desire to trace all the ACEs of Access Control Lists (“ACLs”) a particular packet is subject to. In ECMP, tracing information may be collected as to the ECMP links a particular packet is sent through at each of a plurality of network devices.

Abstract: A source device that plans to participate in one or more encrypted communication sessions with a destination device sends a discovery message towards the destination device. An intermediary device that processes this discovery message requests a master key from the source device. The source verifies that the intermediary device is a trusted device and then sends the intermediary device the requested master key. Prior to transmitting encrypted messages to the destination device, the source device sends session key information, encrypted using the master key, to the intermediary device. The intermediary device uses this session key information to decrypt and process encrypted messages sent as part of the encrypted communication session between the source device and the destination device.

Abstract: A source device that plans to participate in one or more encrypted communication sessions with a destination device sends a discovery message towards the destination device. An intermediary device that processes this discovery message requests a master key from the source device. The source verifies that the intermediary device is a trusted device and then sends the intermediary device the requested master key. Prior to transmitting encrypted messages to the destination device, the source device sends session key information, encrypted using the master key, to the intermediary device. The intermediary device uses this session key information to decrypt and process encrypted messages sent as part of the encrypted communication session between the source device and the destination device.