MEC Application Hosting Across Distributed Edge Resources
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing MEC infrastructure faces challenges in managing resource allocation due to exponential growth in data usage, applications, and services, leading to limitations in simultaneous processing and potential inefficiencies in resource utilization.
Innovation Solution
A system and method for managing MEC application hosting, utilizing an MEC controller to optimize storage and compute resources based on insights from MEC and application service providers, involving an MEC controller, analytics storage unit, MEC data engines, MEC hosts, and application analytic engine to coordinate application hosting and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If MEC infrastructure processes all incoming data simultaneously, then data processing completeness is improved, but resource limitations make this impossible
Solution Approach 1:
The patent segments the MEC infrastructure into multiple distributed MEC hosts (first MEC host, second MEC host, third MEC host) that can independently process different portions of incoming data. This segmentation allows the system to handle larger data volumes by distributing processing across multiple nodes, effectively overcoming the resource limitations of a single MEC host while maintaining processing completeness.
2Reliability
If MEC hosts are distributed across different locations, then service availability is improved, but data transmission distance increases
Solution Approach 1:
The patent implements local quality by deploying MEC hosts at multiple geographic locations (first MEC host, second MEC host, third MEC host) to provide region-specific services. Each MEC host is optimized to serve its local area, reducing the average transmission distance for users in that region while maintaining overall service availability through the distributed architecture.
3Device complexity
If application hosting is centralized in one MEC host, then resource management is simplified, but resource utilization efficiency decreases
Solution Approach 1:
The patent implements dynamic resource management through the MEC controller, which can dynamically allocate and migrate applications between different MEC hosts based on real-time resource availability and demand. This dynamic approach allows the system to optimize resource utilization efficiency by moving workloads to appropriate hosts while maintaining manageable complexity through centralized control logic.
4Productivity
If MEC controller manages multiple MEC hosts, then resource optimization is improved, but system complexity increases
Solution Approach 1:
The patent implements universality by designing the MEC controller with multi-functional capabilities to manage diverse MEC hosts with different resource characteristics. The controller can perform multiple functions including application migration, resource allocation, performance monitoring, and load balancing across heterogeneous hosts, thereby achieving comprehensive resource optimization while managing system complexity through a unified control mechanism.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In one embodiment, a method includes receiving, by a mobile edge computing (MEC) controller and from an application analytic engine, a registration request for an application. The registration request includes a request for MEC key performance indicators (KPIs). The method also includes communicating, by the MEC controller, MEC data associated with a first MEC host and a second MEC host to the application analytic engine. The method further includes receiving, by the MEC controller, MEC policies from the application analytic engine, determining to host the application in the first MEC host based on the MEC policies, and communicating the MEC policies to the first MEC host.