Task Broker for MEC Edge Server Admission Control
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Solution Overview
Problem
Current edge computing systems face significant latency issues due to the need for system-level admission control in task offloading, which is inefficient for delay-sensitive and repetitive tasks, especially with the increasing number of IoT devices.
Innovation Solution
Introducing a task broker at the host management level that analyzes resource requirements and uses a forecasting mechanism to provisionally admit or reject task offloading requests, skipping the initial admission phase and implementing a distributed approach to minimize delay, while maintaining compliance with ETSI MEC architecture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system-level admission control is implemented for task offloading, then task allocation reliability is improved, but task admission delay increases
Solution Approach 1:
The patent segments the admission control function into two levels: system-level admission control for reliability and edge-level task broker for speed. The task broker at the edge server handles repetitive tasks locally, while the system-level orchestrator handles non-repetitive or resource-intensive tasks, creating a hierarchical structure that balances reliability and latency requirements
Solution Approach 2:
The task broker acts as an intermediary between the UE application and the system-level orchestrator. It pre-processes task offloading requests by analyzing resource requirements and forecasting system decisions, providing provisional admissions for repetitive tasks without always involving the system-level orchestrator, thus reducing admission delay while maintaining allocation reliability
2Measurement precision
If system-level admission control is implemented for task offloading, then task allocation accuracy is improved, but processing speed deteriorates
Solution Approach 1:
The task broker performs preliminary analysis of resource requirements and forecasting of system-level decisions before actual task allocation. By pre-evaluating task characteristics and predicting system responses, the task broker can make provisional admission decisions for repetitive tasks, achieving fast processing while maintaining allocation accuracy through subsequent system-level validation when needed
Solution Approach 2:
The system dynamically adjusts the admission control process based on task characteristics. For repetitive tasks with predictable resource requirements, the task broker handles admission locally with fast processing. For non-repetitive or resource-intensive tasks, the system dynamically routes to system-level admission control for accurate allocation, creating a flexible processing path that adapts to different task types
3Speed
If distributed task broker approach is used, then processing speed is improved, but system complexity increases
Solution Approach 1:
The task broker is designed as a universal component that can handle multiple task types (repetitive and non-repetitive) and perform multiple functions (resource analysis, forecasting, provisional admission). This multi-functional design reduces the need for separate specialized components, managing system complexity while enabling fast distributed processing for appropriate task types
Data Source
AI summary
A method of managing task offloading to edge servers in a multi-access edge computing (MEC) system includes receiving, by a task broker implemented at a host management level of the MEC system, a task offloading request from a UE application, analyzing, by the task broker, resource requirements of a task of the task offloading request and running a forecasting mechanism that determines whether the task offloading request will eventually be dropped or not by a system management level of the MEC system. The task broker, based on the determination of the forecasting mechanism, either rejects or provisionally admits the task offloading request.