Edge Local Breakout for Low-Latency Microservice Routing
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Solution Overview
Problem
Conventional local breakout (LBO) methods require core network functions at the cell site, leading to increased data traffic load, network congestion, and high latency due to reliance on centralized core networks, which are not suitable for mobile stations moving between cells.
Innovation Solution
Implementing edge-based micro-services using edge infrastructure to selectively divert packets to edge computing nodes, bypassing the core network, thereby reducing latency and network load by routing traffic directly to edge compute nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional local breakout is implemented at cell sites, then network latency is reduced and network load decreases, but mobile stations moving between cells experience IP address changes that disrupt data sessions
Solution Approach 1:
The patent introduces a mobile edge computing platform as an intermediary between the core network and cell sites. This platform maintains user context information and enables seamless handover between cells by coordinating with multiple cell sites, thereby preserving data session continuity while allowing local breakout at cell sites to reduce latency.
Solution Approach 2:
The patent extends the architecture from a single cell site local breakout to a multi-cell dimension by deploying edge computing platforms that span multiple cells. This allows the system to maintain IP addresses across cell boundaries while still enabling local breakout, resolving the contradiction between latency reduction and session continuity.
2Device complexity
If core network functions are placed inside cell sites for conventional LBO, then network simplification is achieved, but infrastructure cost increases due to expensive core network equipment at each cell site
Solution Approach 1:
The patent merges multiple cell site operations by deploying a shared mobile edge computing platform that serves multiple cell sites. This consolidation allows local breakout functionality to be achieved across multiple cells without replicating expensive core network equipment at each site, thereby reducing overall infrastructure costs while maintaining network simplification benefits.
Solution Approach 2:
The patent segments network functions by separating control plane functions (remaining in centralized core network) from user plane functions (deployed at edge). This segmentation allows local breakout to simplify data traffic paths while avoiding the need to deploy complete core network stacks at each cell site, reducing infrastructure costs.
3Ease of operation
If traffic is routed through centralized core network, then network management is simplified, but network congestion increases and latency increases
Solution Approach 1:
The patent applies local quality by enabling different traffic handling approaches for different types of traffic. Local breakout is applied specifically to edge computing traffic that benefits from low latency, while other traffic can continue to flow through the centralized core network. This selective approach improves network throughput for edge services without compromising overall network management simplicity.
Data Source
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AI summary
The present disclosure describes local breakout for edge computing systems, wherein the local breakout selectively routes the traffic from/to a user equipment between an edge compute node or some other service such as a core network, cloud computing service, or the like. Packets related to microservices that are offered by the edge compute node are routed to the edge compute node instead of routing those packets to the core network, and packets that are not related to the microservices provided by the edge compute node are routed to the core network or to another network such as a data network or cloud computing service. In these ways, the local breakout mechanisms provide low latency and reduced network resource consumption for the microservices and decreased data traffic load on the core network.