Dynamic Computing Resource Allocation for Edge Nodes
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Solution Overview
Problem
Data centers and enterprises face underutilization of computing resources, particularly backup resources and resources that are idle during non-peak hours, and there is a lack of efficient technology to link these resources with geographic-specific business requirements for edge computing applications.
Innovation Solution
A method and system for dynamically allocating computing resources by creating an available resource list that includes the number and time periods of resources provided by multiple providers, allowing requesters to lease resources based on specific geographic locations and usage needs, ensuring secure and efficient utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If backup computing resources are maintained for future use or replacement, then system reliability is improved, but resource utilization deteriorates
Solution Approach 1:
The system enables self-service by allowing backup computing resources to automatically serve external requesters through a marketplace mechanism. Resources that would otherwise sit idle automatically generate value by being allocated to users who need temporary or flexible computing capacity, resolving the contradiction between maintaining reliability and improving utilization.
Solution Approach 2:
The patent makes backup computing resources universal by enabling them to serve multiple purposes: their original backup function for the owning organization and additional revenue-generating function for external users. This multi-functionality allows the same resources to simultaneously improve reliability and productivity.
2Reliability
If computing resources are allocated to handle peak demand, then service quality is improved, but resource waste during off-peak periods increases
Solution Approach 1:
The system implements dynamic resource allocation where computing resources can be flexibly allocated based on real-time demand conditions. During peak periods, resources are allocated to maintain service quality; during off-peak periods, the same resources dynamically shift to serving external requesters, eliminating waste while maintaining service quality when needed.
Solution Approach 2:
The patent ensures continuity of useful action by keeping computing resources continuously productive throughout all time periods. Instead of resources being idle during off-peak hours, the system continuously allocates them to external users who need computing capacity, eliminating the waste of energy while ensuring service quality during peak demand periods.
3Loss of time
If distributed edge computing nodes are deployed to reduce latency, then user experience is improved, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the computing resource marketplace into distributed edge nodes located in different geographic regions. Each edge node independently manages local resources and serves local requesters, reducing time delay through proximity while the modular segmented architecture prevents overall system complexity from becoming unmanageable.
Data Source
AI summary
Embodiments of the present disclosure relate to a method for allocating computing resources, an electronic device, and a corresponding computer program product. The method may include: obtaining an available resource list associated with a computing resource requester according to determination that a resource use request from the computing resource requester is received, wherein the available resource list includes the number and available time periods of computing resources that can be provided by at least one computing resource provider. In addition, the method further includes: allocating computing resources to the computing resource requester based on the available resource list and the resource use request, so that the computing resource requester uses the allocated computing resources to run a workload. The embodiments of the present disclosure can flexibly allocate the computing resources, thereby realizing full utilization of the computing resources.