Software Engine Virtualization Across Edge and Cloud for Lower Latency
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Solution Overview
Problem
Existing software engines face inefficiencies in distribution and resource allocation due to high latency in centralized computing and limited resources at client devices, hindering performance in applications like VR, AR, and IoT.
Innovation Solution
A system for software engine virtualization and dynamic task distribution across edge and cloud, utilizing a virtual layer that optimizes resource allocation across client devices, fog servers, and cloud servers, enabling seamless communication and task distribution through a virtualization logic component and optimization component.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If software engines are hosted on centralized servers, then computing capabilities are improved, but latency increases due to distance between user and data centers
Solution Approach 1:
The patent segments the software engine into multiple components that can be distributed across different locations. The virtualization layer divides engine functions between edge devices (for low-latency operations) and centralized cloud servers (for heavy computing tasks), allowing simultaneous optimization of both latency and computing power.
Solution Approach 2:
The patent introduces a virtualization dimension that abstracts the physical location of engine components. By creating a virtual layer that manages resource allocation across edge and cloud infrastructures, the system transcends the traditional binary choice between centralized and distributed hosting, enabling dynamic placement of engine functions based on performance requirements.
2Loss of time
If software engines are moved to client devices, then latency is reduced due to proximity, but resource limitations hinder performance
Solution Approach 1:
The patent introduces a virtualization layer as an intermediary between client devices and centralized servers. This virtual layer enables client devices to access and utilize remote computing resources while maintaining low-latency local execution for time-sensitive operations, effectively bridging the gap between local and remote capabilities.
Solution Approach 2:
The patent implements dynamic resource allocation where the virtualization layer can shift engine components between edge devices and cloud servers based on real-time performance requirements. This dynamic approach allows the system to optimize for latency when needed and leverage cloud computing power when local resources are insufficient.
3Productivity
If entire software engines are virtualized and distributed, then resource allocation efficiency is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal virtualization layer that can manage multiple software engines and diverse resource types (compute, storage, networking) through a common interface. This multi-functional approach consolidates complexity into a single management layer while enabling efficient resource allocation across the entire distributed system.
Data Source
AI summary
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.