Methods and Systems of Dynamic Management of Resources in a Virtualized Environment

Abstract

The methods and systems described herein centralize simulation resources and effectively delivering training and simulation services to a broad set of distributed users at both the enterprise and operational levels. The cloud-based delivery of simulation applications described herein enables on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. In exemplary systems, users may provision computing capabilities, such as server time and network storage, as needed, automatically without requiring human interaction.

We claim: 
     
         1 . A process for dynamically managing a pool of virtual and physical resources accessible by multiple tenants running multiple instances of a distributable simulation application, the method comprising:
 monitoring, by at least one processing server in the pool, a processing load of each of the multiple instances of the distributable simulation application running within one or more virtual machines in the pool, the one or more virtual machines each comprising a plurality of nodes;   determining, by the at least one processing server, that one or more nodes of the one or more virtual machines is overloaded or underloaded by a status of each of the multiple instance of the distributable simulation application;   if overloaded then starting, by the at least one processing server, at least one new virtual machine; and   instructing, by the at least one processing server, the one or more multiple instances of the application causing the overload to transfer a portion of its processing load from the one or more overloaded nodes to the at least one new virtual machine;   if underloaded then instructing, by the at least one processing server, the one or more multiple instances of the application currently running on one or more underloaded nodes to transfer all of its processing load from the one or more underloaded nodes to one or more alternate nodes; and   stopping, by the at least one processing server, the one or more of the underloaded nodes.   
     
     
         2 . The process according to  claim 1 , wherein monitoring the processing loads includes determining by an extension framework module for each of the multiple instances of the distributable simulation application health of each of the multiple instances. 
     
     
         3 . The process according to  claim 2 , wherein determining health includes determination a status of each of the multiple instances wherein status indicates one of a limitation of a distributable simulation application instance' s objectives or an excess processing capacity in view of the distributable simulation application instance' s objectives. 
     
     
         4 . The process according to  claim 2 , wherein the monitoring by the at least one processing server is initiated by launching the individual extension framework modules by each of the multiple instances of the application, wherein each of the individual extension framework modules facilitates reporting of status for an individual multiple instance back to the at least one processing server. 
     
     
         5 . The process according to  claim 1 , further comprising:
 monitoring, by the at least one processing server in the pool, a status of each of the one or more virtual machines in the pool to determine level of performance thereof and increasing or decreasing assigned use thereof by instance of the application accordingly.   
     
     
         6 . The process according to  claim 2 , further comprising: determining by extension framework module for at least one of the multiple instances distributable simulation application occurrence of a gasp condition and a status of overloaded. 
     
     
         7 . A process for dynamically managing a pool of virtual and physical resources accessible by multiple tenants running multiple instances of a distributable simulation application, the method comprising:
 monitoring by a processing server a status of each of the multiple instances of the distributable simulation application, wherein the monitoring is initiated by launching an individual extension framework module by each of the multiple instances of the distributable simulation application, wherein the individual extension framework modules facilitate reporting of the status of each of the multiple instances back to the processing server and further wherein monitoring the status of each of the multiple instances of the distributable simulation application includes monitoring the health of the distributable simulation application including gasp conditions; and   managing by the processing server the pool of virtual and physical resources responsive to the status of each of the multiple instances of the distributable simulation application.   
     
     
         8 . The process according to  claim 7 , wherein monitoring the status of the multiple instances of the distributable simulation application includes determining for each of the multiple instances a status causing a limitation of distributable simulation application objectives or excess processing capacity to occur during each of the multiple instances. 
     
     
         9 . The process according to  claim 7 , wherein the extension framework modules provide transfer instructions for adjusting the pool of virtual and physical resources responsive to the reported status of the multiple instances of the distributable simulation application. 
     
     
         10 . The process according to  claim 8 , wherein the extension framework modules provide transfer instructions for adjusting the pool of virtual and physical resources responsive to the reported status of the multiple instances of the distributable simulation application. 
     
     
         11 . The method according to  claim 10 , wherein the transfer instructions include instructing one or more corresponding plugin modules to transfer a portion of a processing load for an instance of the distributable simulation application to one or more different virtual machines when a status of the instance of the distributable simulation application causes a limitation of distributable simulation application objectives. 
     
     
         12 . The method according to  claim 9 , wherein the transfer instructions include instructing one or more corresponding plugin modules to transfer a portion of a processing load for an instance of the distributable simulation application to one or more different virtual machines when a status of the instance of the distributable simulation application causes a gasp condition. 
     
     
         13 . The method according to  claim 10 , wherein the transfer instructions include:
 instructing one or more corresponding plugin modules to transfer all of a processing load for an instance of the distributable simulation application to one or more different virtual machines when a status of the instance of the distributable simulation application causes excess processing capacity to occur during the instance; and   instructing a virtual machine on which the instance of the distributable simulation application was running to stop processing.