Network Allocation Service for Edge and Non-Edge Networks
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Solution Overview
Problem
Multi-access edge computing (MEC) networks often face insufficient resources, leading to degradation in quality of service (QoS) metrics such as latency, error rate, and throughput, which can result in denial of service to end devices due to limited computational, memory, storage, and communication resources.
Innovation Solution
A network allocation service that determines whether to select an MEC network or a non-MEC network to satisfy application service requests by obtaining real-time resource utilization and capacity information, and selecting a network that meets performance metrics, thereby preventing unnecessary resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If MEC network resources are allocated to all end devices, then service coverage is improved, but resource insufficiency leads to QoS degradation
Solution Approach 1:
The system dynamically changes network selection parameters based on real-time resource conditions. When MEC resources are sufficient, it selects MEC network for low latency; when resources are insufficient, it switches to non-MEC network to maintain QoS, thus adapting to varying resource availability while preserving service quality
Solution Approach 2:
The network allocation service implements dynamic network selection that adapts to changing resource conditions. It continuously monitors MEC resource utilization and dynamically switches between MEC and non-MEC networks based on current capacity, transforming a static allocation problem into a dynamic optimization process
2Speed
If MEC network is selected for all requests, then latency is reduced, but resource exhaustion occurs when resources are insufficient
Solution Approach 1:
The network allocation service acts as an intermediary between end devices and MEC networks. It evaluates resource conditions and determines the optimal network path, preventing direct connections to overloaded MEC networks that would cause service failures, thus protecting service availability while managing latency
Solution Approach 2:
Instead of always selecting MEC network for low latency, the system inverts the approach by selecting non-MEC network when MEC resources are insufficient. This reverse logic prioritizes service availability over minimal latency, preventing resource exhaustion while maintaining acceptable performance
3Productivity
If network allocation service dynamically selects networks, then resource usage is optimized, but system complexity increases
Solution Approach 1:
The network allocation service implements self-service by automatically monitoring MEC resource conditions and making autonomous network selection decisions. It queries resource availability, evaluates against QoS requirements, and selects appropriate networks without manual intervention, optimizing resource utilization while managing complexity through automation
Data Source
AI summary
A method, a device, and a non-transitory storage medium are described in which a network allocation service is provided. The network allocation service may use available network resource information of an application service layer network of a first type, such as a multi-access edge computing network, and application service demand information of an application to determine whether a performance metric of the application service would be satisfied. The performance metric may include a threshold service time that includes a processing time associated with a processing of an application service request and response, by the application service layer network, and a transit time associated the application service response from the application service layer network to an end device. The network allocation service may select the first type or a second type of application service layer network depending on the outcome of the determination.