Mobile Edge Computing Server Access Point Distribution
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Solution Overview
Problem
In 5G networks, user mobility leads to challenges in maintaining low latency and high Quality of Service (QoS) for Mobile Edge Computing (MEC) services due to increased inter-MECS migrations, which are costly and inefficient, especially when users move across different geographical areas, causing service continuity issues and high communication overhead.
Innovation Solution
The method involves collecting vehicle-traffic statistics to dynamically define Mobile Edge Computing Areas (MECA) that align with main traffic flows, reducing inter-MECS migrations by strategically distributing Access Points (AP) within these areas based on traffic flow, QoE metrics, and available capacity, allowing for seamless ECC and application migration within the same MECA without the need for costly inter-MECS transfers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users are allowed to move freely across different geographical areas in the network, then user mobility and coverage are improved, but inter-MECS migrations increase causing service continuity issues and high communication overhead
Solution Approach 1:
The service area is segmented into multiple Mobile Edge Computing Areas (MECA), each associated with a specific MECS. Users are assigned to a MECA based on their location and traffic flow patterns. This segmentation allows users to move within a MECA without triggering inter-MECS migrations, reducing communication overhead while maintaining mobility.
Solution Approach 2:
The patent introduces an intermediary mechanism (MECA assignment and traffic flow analysis) between the user and the MECS selection process. By analyzing traffic flow statistics and assigning users to appropriate MECAs, the system mediates the migration process to minimize inter-MECS transfers and reduce communication overhead.
2Reliability
If services are migrated between different MECS to follow user movement, then service continuity is maintained, but migration costs increase due to heavy communication between ECCs and startup of new virtual machines
Solution Approach 1:
The system performs preliminary analysis of traffic flow statistics to predict user movement patterns and pre-assign users to appropriate MECAs before migration occurs. This preliminary action allows the system to prepare for potential migrations in advance, reducing the need for costly emergency migrations and virtual machine startups.
Solution Approach 2:
The patent implements local quality by allowing users to move freely within their assigned MECA without triggering migrations, while only initiating migrations when users cross MECA boundaries. This localized approach maintains service continuity within MECAs and reduces overall migration costs by minimizing inter-MECS transfers.
3Area of stationary object
If Access Points are distributed throughout the service area to cover all regions, then coverage is improved, but the number of inter-MECS migrations increases
Solution Approach 1:
The service area is divided into multiple MECAs with overlapping coverage zones. Access Points are distributed within these segmented areas, allowing users to maintain connectivity and move within MECA boundaries without triggering inter-MECS migrations, thus reducing migration frequency while maintaining comprehensive coverage.
Solution Approach 2:
The patent adds a spatial dimension to AP distribution by strategically placing Access Points at boundaries between MECAs. This dimensional approach allows APs to serve multiple MECAs, enabling users near boundaries to switch between MECAs without requiring full inter-MECS migration, thereby reducing migration frequency while maintaining coverage.
Data Source
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AI summary
A method in a telecommunications network, the network including at least one service area, the method comprising: at the network, distributing a mobile edge computing server within a corresponding one of the service areas; at the mobile edge computing server, distributing at least one access point within the corresponding service area; and at the mobile edge computing server, determining a mobile edge computing area within the corresponding service area; wherein at least one of the access points is located within a corresponding one of the mobile edge computing areas.