Alcatel Lucent

At+t Corp.

Avaya Technology LLC

Alcatel-lucent USA Inc.

Nokia of America Corporation

Ncr Corporation

Avaya Technologies Corp

Eric Jonathan Bauer

Randee Susan Adams

Daniel Weiler Eustace

Yuk-Ming Peter Lam

Mark Michael Clougherty

Kedar S Namjoshi

Lyle Dean Kipp

Xuemei Zhang

Paul Hampton Franklin

John H Haller

Frederik G A Vandeputte

Li Erran Li

Peter Bosch

Iraj Saniee

Yang Guo

Volker Hilt

William David Reents, Jr

Behrokh Samadi

Prakash Iyer

Douglas A Kimber

Wassim A Matragi

Abhaya Asthana

Gang Yang

Russel W Schaffer

Meenakshi Sharma

John Orleanski

Fang-Fe S Huan

William M Reents

David A Gatenby

Elena Nesvetaeva

A capability for management of computing infrastructure under emergency peak capacity conditions is presented. The capability for management of computing infrastructure under emergency peak capacity conditions may support configuration of computing infrastructure to provide additional computing capacity for the emergency peak capacity conditions. The computing infrastructure may include capacity supporting equipment configured to provide computing capacity of the computing infrastructure and environmental equipment configured to support operation of the capacity supporting equipment. The configuration of computing infrastructure to support additional computing capacity for an emergency peak capacity condition may include configuration of capacity supporting equipment to operate in emergency operating mode, rather than normal operating mode, to support the additional computing capacity for the emergency peak capacity condition. The configuration of cloud computing infrastructure to provide additional computing capacity for an emergency peak capacity condition may include configuration of environmental equipment to support operation of capacity supporting equipment in emergency operating mode.

Management of computing infrastructure under emergency peak capacity conditions

A capability for perfect application capacity analysis for elastic capacity management of a cloud-based application is presented. The capability for perfect application capacity analysis for elastic capacity management of a cloud-based application may support use of perfect application capacity analysis to identify opportunities for improvements in elastic capacity management of the cloud-based application. The capability for perfect application capacity analysis for elastic capacity management of a cloud-based application may include receiving historical application demand and capacity data for the cloud-based application, determining a set of constraints associated with the cloud-based application, determining perfect application capacity data for the cloud-based application based on the historical application demand data for the cloud-based application and the set of constraints associated with the cloud-based application, and identifying, based on the historical application capacity data for the cloud-based application and the perfect application capacity data for the cloud-based application, an opportunity to improve elastic capacity management for the cloud-based application.

Perfect application capacity analysis for elastic capacity management of cloud-based applications

Various exemplary embodiments relate to a method of preventing extreme coresidency hazards among application instances in a cloud network. The method includes determining a first failure group of a first instance of an application; establishing a connection with a second instance of a peer application; determining a second failure group of the second instance; comparing the first failure group to the second failure group; and establishing a second connection with a third instance of the peer application if the first failure group and the second failure group share a failure point.

Preventing extreme coresidency hazards in cloud computing

Various exemplary embodiments relate to a method and related network node including one or more of the following: identifying a hardware failure of a failed component of a plurality of hardware components; determining a set of agent devices currently configured to utilize the failed component; reconfiguring an agent device to utilize a working component of the plurality of hardware components. Various exemplary embodiments additionally or alternatively relate to a method and related network node including one or more of the following: projecting a failure date for the hardware module; determining whether the projected failure date is acceptable based on a target replacement date for the hardware module; if the projected failure date is not acceptable: selecting a parameter adjustment for a hardware component, wherein the parameter adjustment is selected to move the projected failure date closer to the target replacement date, and applying the parameter adjustment to the hardware component.

Hardware consumption architecture

A method and system for network element recovery are provided. In one form, frontend servers intelligently proxy error or unavailability messages returned by backend servers and simulate frontend server failure. In at least one form, the frontend server also includes intelligence or logic to determine that directing the client to recover service to an alternate system or site would assure better service availability, reliability, and/or quality-of-experience for the client.

Method and system for network element service recovery

A capability is provided for reducing response variance of virtual processors. A controller receives a processing request. The controller may propagate the processing request toward multiple virtual processors hosted on multiple hardware devices contemporaneously. The controller may propagate the processing request toward a first virtual processor hosted on a first hardware device and propagate the processing request toward a second virtual processor hosted on a second hardware device based on a determination that a timeout period expires before a processing response is received from the first virtual processor. The timeout period may be determined based on one or more response time statistics of the virtual processor and one or more response time statistics of a physical processor.

Reducing response time variance of virtual processors

A capability is provided for improving service availability experienced by a user requesting access to a service via a user device, where the service has multiple service instances available from multiple data centers. A set of servicing data centers is selected for the user device. The set of servicing data centers is selected from a set of candidate data centers. The set of servicing data centers is selected from the set of candidate data centers in a manner for maximizing the independence/orthogonality of the network paths between the user device and the servicing data centers. The set of servicing data centers includes two or more of the candidate data centers from which the user device may access the service, thereby providing the user device with a primary service instance and one or more backup service instances which may be used to access the service.

Apparatus and method for providing service availability to a user via selection of data centers for the user

Various embodiments provide a method and apparatus of providing a rapid disaster recovery preparation in cloud networks that proactively detects disaster events and rapidly allocates cloud resources. Rapid disaster recovery preparation may shorten the recovery time objective (RTO) by proactively growing capacity on the recovery application(s)/resource(s) before the surge of recovery traffic hits the recovery application(s)/resource(s). Furthermore, rapid disaster recovery preparation may shorten RTO by growing capacity more rapidly than during 'normal operation' where the capacity is increased by modest growth after the load has exceeded a utilization threshold for a period of time.

Method and apparatus for rapid disaster recovery preparation in a cloud network

Various exemplary embodiments relate to a method and related network node including one or more of the following: detecting, by a resource allocation device, a failure of server hardware; identifying a first agent device that is configured to utilize the server hardware; and taking at least one action to effect a reconfiguration of the first agent device in response to the server hardware failure. Various embodiments additionally include one or more of the following: identifying a second agent device that is configured to utilize the server hardware; and taking at least one action to effect a reconfiguration of the second agent device in response to the server hardware failure. Various embodiments additionally include one or more of the following: receiving, by the resource allocation device from a second agent device, an indication of the failure of server hardware, wherein the second agent device is different from the first agent device.

Hardware failure mitigation

Various exemplary embodiments relate to a method and related network node including one or more of the following: determining that a diagnostic test should be performed on a hardware component of a plurality of hardware components, wherein the plurality of hardware components support a plurality of agent devices and at least one agent device of the plurality of agent devices is assigned to at least one of the plurality of hardware components; ensuring that no agent device of the plurality of agent devices is assigned to the hardware component; and after ensuring that no agent device of the plurality of agent devices is assigned to the hardware component, performing the diagnostic test on the hardware component, wherein at least one other hardware component of the plurality of hardware components continues operation during performance of the diagnostic test.

Live module diagnostic testing

The invention includes a method and apparatus for reconfiguring a first base station element to attempt to serve at least a portion of the plurality of wireless terminals served by a second base station element in response to detection of a failure condition at a second base station element that was serving the plurality of wireless terminals prior to the occurrence of the failure condition.

Method and apparatus for improving wireless network reliability

The invention includes a method for predicting a scheduled downtime associated with a system. In one embodiment, a method includes determining a system model associated with the system according to a system type of the system, determining at least one scheduled system downtime event type associated with the system using the system model, selecting at least one scheduled system downtime event model according to the at least one scheduled system downtime event type, and predicting the scheduled system downtime using the at least one scheduled system downtime event model.

Method and apparatus for predicting scheduled system downtime

The invention includes a method and apparatus for assessing an available version of a sourced element. The method includes obtaining a description of an available version of the sourced element, identifying a plurality of evaluation items for the sourced element by evaluating the description using at least one evaluation category including a plurality of evaluation parameters, and determining an overall assessment of the available version of the sourced element using the identified evaluation items for the sourced element. The overall assessment is indicative of a value associated with the available version of the sourced element. The method may further include generating overall assessments of other available versions of a sourced element or generating overall assessments of available versions of other sourced elements, and prioritizing the available versions of the sourced elements using the overall assessments of the available versions of the sourced elements.

Growing community of inventors

Freehold, NJ, United States of America

Eric Jonathan Bauer