Edge Computing Resource Sharing Platform
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Solution Overview
Problem
5G edge computing resources have limited capacity and cannot be easily upgraded or replaced, leading to potential service breakdowns during capacity bursts, and existing solutions often result in resource wastage and inefficiency due to over-provisioning for worst-case scenarios.
Innovation Solution
A method and system for sharing edge computing resources, allowing lessee edge computing resources to request and connect with lessor edge computing resources on a demand basis through a sharing platform, utilizing a marketplace platform that manages availability, authentication, and financial transactions to optimize resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If edge computing resources are over-provisioned to handle worst-case scenarios, then service reliability is improved, but resource wastage increases
Solution Approach 1:
The patent merges multiple edge computing resources from different lessors into a unified shared pool that can be dynamically allocated to lessees. This consolidation allows resources to be pooled together and shared across multiple service providers, ensuring reliability through aggregated capacity while eliminating the need for each provider to over-provision independently, thus reducing overall resource wastage.
Solution Approach 2:
The patent implements dynamic resource allocation where edge computing resources can be flexibly assigned and reassigned based on real-time demand. The system continuously monitors resource utilization and capacity requirements, allowing lessees to access additional resources during capacity bursts and release them when not needed, transforming static over-provisioning into dynamic on-demand allocation that maintains reliability without permanent excess capacity.
2Reliability
If edge computing resources are increased to handle capacity bursts, then service availability is improved, but infrastructure cost increases
Solution Approach 1:
The patent creates a universal edge computing resource pool where infrastructure assets can serve multiple lessees and multiple use cases simultaneously. A single edge computing resource can be allocated to different lessees at different times based on demand, making the infrastructure multi-functional and eliminating the need for dedicated excess capacity for each potential scenario, thereby improving service availability without proportionally increasing total infrastructure.
Solution Approach 2:
The system enables automatic resource provisioning and management through the sharing platform that handles resource allocation, monitoring, and scaling without manual intervention. The platform automatically detects capacity bursts and allocates resources from the shared pool to affected lessees, allowing the infrastructure to self-adjust to demand fluctuations without requiring pre-configured excess capacity for every possible scenario.
3Adaptability or versatility
If edge computing resources are made upgradeable and replaceable, then adaptability is improved, but system complexity increases
Solution Approach 1:
The patent introduces a sharing platform as an intermediary layer between physical edge computing resources and lessees. This platform abstracts the complexity of resource management, provisioning, and allocation, handling all upgrade and replacement operations centrally. Individual edge resources can be upgraded or replaced without affecting lessees, as the platform manages the transitions, thereby improving adaptability while containing system complexity within the platform rather than distributing it across the entire ecosystem.
4Reliability
If more edge nodes are deployed to handle sudden capacity bursts, then service reliability is improved, but resource utilization efficiency decreases
Solution Approach 1:
The patent ensures continuous utilization of edge computing resources by maintaining a shared pool where resources are constantly allocated to lessees based on demand. Rather than deploying idle edge nodes that sit unused until capacity bursts occur, the system continuously puts resources to work serving various lessees, and only scales up by activating additional resources when actual demand requires it, thereby maintaining both reliability and high utilization efficiency through continuous productive use of the infrastructure.
Data Source
AI summary
A method and a system of sharing an edge computing resource is disclosed. In an embodiment, the method may include receiving from one or more lessor edge computing resources, one or more first requests for presenting an availability of the one or more lessor edge computing resources, and receiving from a lessee edge computing resource, a second request for availing at least one lessor edge computing resource. The method may further include, upon receiving the second request, presenting the one or more first requests corresponding to the one or more lessor edge computing resources, to the lessee edge computing resource. The method may further include receiving from the lessee edge computing resource, a selection of a first request from the one or more first requests, and creating a connection between the lessee edge computing resource and the lessor edge computing resource corresponding to the received selection.