Software engine virtualization and dynamic resource and task distribution across edge and cloud
A system and method for enabling software engine virtualization and dynamic resource and task distribution across edge and cloud, comprising at least one cloud server comprising memory and at least one processor, the at least one cloud server hosting at least one cloud engine configured to store and process application data from one or more applications; one or more client devices connected to the cloud server via a network, the one or more client devices hosting at least one local engine configured to store and process application data from the one or more applications and to provide output to users; and a virtual engine hosted across edge and cloud configured to virtualize, via a virtualization logic component, one or more system network components, applications, and engine components, creating a virtual layer connected to the one or more client devices and cloud server via the network.
1. A system enabling software engine virtualization and dynamic resource and task distribution across edge and cloud, comprising:
at least one cloud server comprising memory and at least one processor, the at least one cloud server hosting a virtualization logic component and at least one cloud engine of a software engine, the at least one cloud engine configured to store and process application data from one or more application that uses the software engine;
one or more client devices connected to the at least one cloud server via a network, the one or more client devices hosting at least one local engine of the software engine, the at least one local engine configured to store and process application data from the application and to provide output to users;
a virtual engine hosted across edge and cloud, the virtual engine configured to virtualize, via the virtualization logic component, one or more system network components, the application, and components of the at least one cloud engine and the at least one local engine, creating a virtual layer connected to the one or more client devices and the at least one cloud server via the network, and
at least one system resource distribution platform comprising virtual cells linked to a plurality of physical network resources, and configured to dynamically allocate resources and engine tasks.
2. The system of claim 1 , further comprising one or more fog servers comprising memory and at least one processor, the fog servers being located in areas proximate to the one or more client devices and configured to assist the at least one cloud server and the one or more client devices in the processing of application data from the application, wherein the functions of the fog servers are abstracted within the virtual layer.
3. The system of claim 2 , wherein the application is hosted by the one or more client devices, cloud servers, fog servers, or combinations thereof.
4. The system of claim 2 , wherein the virtual engine further comprises one or more function-specific sub-engines corresponding to the application comprising one or more of an audio engine, a physics engine, a graphics engine, or an artificial intelligence (“AI”) engine, and wherein tasks associated with the one or more function-specific sub-engines are performed by the one or more client devices, the one or more fog servers, and the at least one cloud server.
5. The system of claim 1 , wherein the virtual engine further comprises:
at least one optimization component configured to assess engine task and system resource requirements from the application and to optimize the resource and task allocation based on said assessment; and
at least one system resource distribution platform configured to distribute required engine tasks and system resources across edge and cloud on demand based on the optimization of the at least one optimization component.
6. The system of claim 5 , the virtual cells comprise divisions of a virtual world system in which the resource and task allocation is performed.
7. The system of claim 5 , wherein the optimization component utilizes resource allocation parameters comprising one or more of server capabilities; client capabilities; end-to-end response time; application resources demand; demanded and available quality of service; service level agreement; distance between devices and servers; bandwidth capacity; or required level of detail, or combinations thereof.
8. The system of claim 1 , wherein two or more of the virtual cells may be used in combination in order to dynamically allocate resources and engine tasks to the one or more client devices.
9. The system of claim 1 , wherein the virtual engine further comprises one or more function-specific sub-engines.
10. The system of claim 1 , wherein the network comprises millimeter-wave (mmW) or combinations of mmW and sub 6 GHz communication systems, or a wireless local area network.
11. The system of claim 1 , wherein the one or more client devices include one or more mobile devices, personal computers, game consoles, media centers, smart contact lenses, or head-mounted displays.
12. The system of claim 1 , wherein the virtual engine further comprises one or more function-specific sub-engines corresponding to the application comprising one or more of an audio engine, a physics engine, a graphics engine, or an artificial intelligence (“AI”) engine, and wherein tasks associated with the one or more function-specific sub-engines are performed by the one or more client devices and the at least one cloud server.
13. A method enabling software engine virtualization and distribution across edge and cloud, comprising:
providing a virtual engine hosted across one or more cloud servers and one or more client devices connected via a network, the virtual engine comprising a virtualization logic component, wherein the virtual engine is configured to dynamically allocate function-specific engine tasks of an engine for running one or more application between the one or more client devices and the one or more cloud servers;
virtualizing, via the virtualization logic component of the virtual engine, one or more system network components, the application that uses the software engine, and components of the software engine, creating a virtual layer connected to the one or more client devices and the one or more cloud servers via the network; and
dynamically distributing on demand engine tasks and system resources via a distribution component of the virtual engine,
wherein the distribution component comprises virtual cells linked to a plurality of physical network resources, and configured to dynamically allocate resources and engine tasks.
14. The method of claim 13 , further comprising providing one or more fog servers comprising memory and at least one processor, the one or more fog servers being located in areas proximate to the one or more client devices and configured to assist the one or more cloud servers and the one or more client devices in the processing of application data from the application, wherein the functions of the one or more fog servers are abstracted within the virtual layer.
15. The method of claim 14 , wherein the application is hosted by the one or more client devices, the one or more cloud servers, the one or more fog servers, or combinations thereof.
16. The method of claim 13 , further comprising:
assessing, by at least one optimization component in the virtual engine, engine task and system resource requirements from the application;
optimizing, by the at least one optimization component in the virtual engine, the allocation of engine tasks and system resources based on said assessment; and
dynamically distributing the on demand engine tasks and the system resources across the edge and the cloud via the distribution component of the virtual engine based on the optimization performed by the at least one optimization component.
17. The method of claim 16 , wherein the at least one optimization component utilizes resource allocation parameters comprising one or more of server capabilities; client capabilities; end-to-end response time; application resources demand; demanded and available quality of service; service level agreement; distance between devices and servers; bandwidth capacity; or level of detail, or a combination thereof.
18. The method of claim 16 , wherein the virtual cells comprise divisions of the virtual world system in which the allocation of engine tasks and system resources is performed.
19. The method of claim 18 , wherein two or more of the virtual cells may be used in combination in order to dynamically allocate resources and engine tasks to the one or more client devices.
20. The method of claim 13 , wherein the engine comprises one or more function-specific sub-engines.
21. The method of claim 13 , wherein the network comprises millimeter-wave (mmW) or combinations of mmW and sub 6 GHz communication systems, or a wireless local area network.
22. One or more non-transitory computer-readable media having stored thereon instructions configured to, when executed by one or more computers, cause the one or more computers to enable software engine virtualization and dynamic resource and task distribution across edge and cloud by performing steps comprising:
providing a virtual engine hosted across one or more cloud servers and one or more client devices connected via a network, the virtual engine comprising a virtualization logic component, wherein the virtual engine is configured to dynamically allocate function-specific engine tasks of an engine for running one or more application between the one or more client devices and the one or more cloud servers;
virtualizing, via the virtualization logic component of the virtual engine, one or more system network components, the application that uses the engine, and components of the engine, creating a virtual layer connected to the one or more client devices and the one or more cloud servers via the network;
assessing, by at least one optimization component in the virtual engine, engine task and system resource requirements from the application;
optimizing, by the at least one optimization component in the virtual engine, the allocation of engine tasks and system resources based on said assessment; and
dynamically distributing on demand engine tasks and system resources across edge and cloud via a distribution component of the virtual engine based on the optimization performed by the at least one optimization component,
wherein the distribution component comprises virtual cells linked to a plurality of physical network resources, and configured to dynamically allocate resources and engine tasks.