Multi-Access-Point Edge Service Allocation With QoS and Usage History
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Solution Overview
Problem
Existing methods for service distribution in multi-access edge computing (MEC) networks do not adequately consider computing resources and latency, leading to inefficient service allocation.
Innovation Solution
A method for service provision in edge networks involving multiple access points, where a terminal transmits a service request message, undergoes authentication, and access points determine service availability and cost based on quality of service (QoS) conditions, resource requirements, and historical service usage to optimize service delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If service distribution is based only on available computing resources and inter-node latency time, then service allocation can be simplified, but service delivery efficiency and optimality deteriorate
Solution Approach 1:
The patent introduces multiple evaluation parameters beyond basic computing resources and latency time, including service execution cost, QoS constraints, and historical service usage patterns. This multi-parameter evaluation system transforms the service allocation process from a simple resource-matching approach to a comprehensive optimization framework that considers economic, technical, and historical factors simultaneously
Solution Approach 2:
The patent implements feedback mechanisms by considering historical service usage data and QoS constraint satisfaction patterns. The system learns from past service deployments and uses this information to improve future allocation decisions, creating a closed-loop optimization process that continuously refines service distribution based on actual performance outcomes
2Reliability
If multiple access points are evaluated based on comprehensive criteria including QoS and historical data, then service optimality improves, but the complexity of service distribution increases
Solution Approach 1:
The patent segments the service evaluation process into distinct components: QoS constraint verification, service execution cost calculation, historical usage analysis, and access point capability assessment. Each component is evaluated independently and then integrated through a weighted decision-making framework, making the complex evaluation process more manageable and systematic
Solution Approach 2:
The patent transforms multiple qualitative and quantitative factors into standardized evaluation parameters that can be systematically compared. By converting diverse criteria (QoS constraints, historical performance, resource availability) into unified parameter metrics, the system enables comprehensive evaluation while maintaining computational tractability through parameter normalization and weighting
Data Source
AI summary
Provided is a method for providing a service in an edge network system including a plurality of access points including steps of transmitting, by a terminal, a service request message including a name of a service to be provided to a first access point, transmitting, by the first access point, a service request response message including an estimated service execution time and data for authentication to the terminal, performing authentication between the terminal and the first access point based on the data for authentication for the estimated service execution time, and providing, by the first access point, a content corresponding to the service request message to the terminal, when the authentication between the terminal and the first access point is successful.