Virtual Edge Device Emulation for Low-Latency IoT Workloads
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Solution Overview
Problem
Centralized cloud computing environments are inadequate for managing time-sensitive data processing from IoT devices that are geographically distant or in disconnected regions due to latency issues, and customers face challenges in determining suitable data processing jobs for deployment on edge devices.
Innovation Solution
A virtual edge device is provisioned to emulate a physical edge device within an isolated computing environment, allowing customers to test workloads and execute them efficiently, with a system that includes containerization of services and a user interface for management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If data processing is performed at centralized cloud locations, then infrastructure management is simplified, but latency increases for geographically distant IoT devices
Solution Approach 1:
The patent segments the centralized cloud infrastructure into distributed edge computing nodes deployed geographically close to IoT devices. This segmentation allows data processing to occur locally at edge locations rather than requiring all data to travel to centralized cloud data centers, thereby reducing latency while maintaining infrastructure management benefits through virtualized, standardized edge nodes that can be provisioned and managed centrally.
Solution Approach 2:
The patent introduces a new dimensional approach by deploying edge computing infrastructure across multiple geographic dimensions rather than relying solely on centralized vertical scaling. Virtual edge devices are distributed across various edge locations, creating a multi-dimensional processing architecture that reduces spatial distance between data sources and processing resources, thus lowering latency without sacrificing centralized management capabilities.
2Loss of time
If edge devices are deployed for local data processing, then latency is reduced, but determining suitable workloads for deployment becomes difficult
Solution Approach 1:
The patent creates virtual copies of edge devices that replicate the hardware and software characteristics of physical edge devices. These virtual edge devices serve as testbeds where customers can provision and test workloads in a controlled environment before deploying to actual edge hardware. This copying mechanism eliminates the difficulty of assessing workload suitability by providing a realistic simulation of edge device performance and constraints.
Solution Approach 2:
The patent enables preliminary workload testing and validation on virtual edge devices before actual deployment to physical edge devices. Customers can provision workloads, measure performance, and verify compatibility in advance, thereby eliminating the uncertainty of determining workload suitability. This preliminary action on virtual instances provides confidence and data for successful physical edge device deployment.
3Reliability
If virtual edge devices are provisioned to emulate physical edge devices, then workload compatibility is ensured, but system complexity increases
Solution Approach 1:
The patent provisions virtual edge devices that are virtualized copies of physical edge devices, replicating their hardware specifications, operating systems, and software environments. This copying ensures workload compatibility by providing an identical execution environment, thereby guaranteeing that workloads tested on virtual devices will run successfully on physical devices without compatibility issues.
Solution Approach 2:
The patent creates universal virtual edge device templates that can be replicated and deployed across multiple locations and physical device types. These standardized virtual images provide multi-functionality, serving as both testing environments and deployment targets. The universal nature of these virtual templates simplifies the overall system by providing a single, standardized interface for workload provisioning regardless of the underlying physical hardware diversity.
Data Source
AI summary
Techniques are disclosed for provisioning and managing a virtual edge device that is configured to emulate a physical edge device that executes within an isolated computing environment. The isolated computing environment may be separate from a centralized cloud computing environment that provides a plurality of services for executing customer workloads. In one example, a computer system receives a request to provision a virtual edge device. The computer system identifies a physical computing device to be provisioned as the virtual edge device based on the request. The computer system generates a set of data containers that containerizes a set of services configured to execute subsequent workloads, and then the system provisions the physical computing system with the set of data containers. In response to the customer request, the computer system provides a user interface operable for accessing and managing the virtual edge device.