Multi-Tier Edge-Cloud Virtualization for Latency Reduction
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Solution Overview
Problem
Cloud-based systems face limitations in real-time data delivery due to network overhead and latency, particularly in IoT applications with strict latency requirements, and privacy concerns arise from sending sensitive data to remote data centers.
Innovation Solution
The implementation of a multi-tier edge-cloud virtualization environment that allocates resources efficiently by instantiating virtual nodes on cloud and edge resources based on data freshness constraints, optimizing resource utilization and meeting quality of service requirements through a Centralized Resource Provisioning and Allocation Manager (CRPAM) that jointly considers resource provisioning and allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud-based systems are used for data processing, then computing resources are consolidated and managed centrally, but network latency and overhead increase, reducing real-time data delivery performance
Solution Approach 1:
The system segments the centralized cloud computing environment into distributed edge computing nodes positioned closer to data sources. This segmentation allows local processing at edge nodes while maintaining centralized coordination, thereby reducing network latency for real-time data delivery while preserving resource consolidation benefits.
Solution Approach 2:
The patent introduces a spatial dimension to resource allocation by deploying virtual nodes across multiple geographic locations (edge nodes near data sources and cloud nodes centrally). This multi-dimensional deployment strategy enables the system to simultaneously achieve low latency through local edge processing and efficient resource utilization through centralized cloud coordination.
2Power
If data is sent to remote data centers for processing, then centralized computing power is utilized, but data privacy concerns arise from transmitting sensitive information
Solution Approach 1:
The patent introduces edge nodes as intermediary processing points between data sources and remote cloud data centers. These edge nodes perform initial data processing and filtering locally, transmitting only essential processed information to the cloud. This intermediary approach enables utilization of centralized computing power while minimizing exposure of sensitive raw data during transmission.
3Reliability
If virtual nodes are allocated dynamically based on data freshness constraints, then quality of service requirements are met, but resource allocation complexity increases
Solution Approach 1:
The patent implements dynamic virtual node allocation that adapts to changing data freshness requirements in real-time. The system continuously monitors data age constraints and automatically adjusts virtual node placement and resource provisioning accordingly. This dynamic approach ensures quality of service compliance while the automated nature of the adjustment reduces manual complexity.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor data freshness metrics and automatically adjust resource allocation decisions. By continuously measuring actual data age against required freshness constraints and using this feedback to refine virtual node placement, the system achieves reliable quality of service while reducing allocation complexity through automated closed-loop control.
Data Source
AI summary
Techniques are provided for resource allocation and provisioning in a multi-tier edge-cloud virtualization environment. An exemplary method comprises: obtaining an application request for processing a given data type in a multi-tier environment; processing application requests received within a decision window to allocate resources for virtual nodes to process the application requests received within the decision window, wherein the allocated resources for each virtual node is on a corresponding one of cloud resources and a given edge node; instantiating the allocated virtual nodes to process the application requests; and providing the application requests to the instantiated virtual nodes, wherein the instantiated virtual nodes obtain the data of the given data type from a data repository. The virtual node waits to process a given application request for output data of any predecessor requests and sends the output data of the given application request to any additional virtual nodes holding successor requests to the given application request.