Edge Workload Routing for 5G Handover Latency
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Solution Overview
Problem
5G networks face challenges in maintaining low latency and high performance due to limitations in physical and logical infrastructure, particularly in edge data centers, which can lead to increased latency during handovers between radio cells, affecting applications with low latency requirements.
Innovation Solution
The implementation of network-defined edge routing using a set of interconnected edge data centers with segment routing and element-aware segment identification, allowing for the computation of paths that meet traffic class requirements and optimizing edge routing control, enabling the movement or replication of application workloads to minimize latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traffic is routed through traditional network infrastructure during handovers, then network coverage and connectivity are maintained, but latency increases and performance requirements are not met
Solution Approach 1:
The network is segmented into multiple edge data centers distributed across different locations, each capable of hosting application workloads. During handovers, traffic is routed to the nearest edge data center segment, reducing transmission distance and latency while maintaining connectivity through the segmented network architecture.
Solution Approach 2:
A traffic routing mechanism acts as an intermediary between traditional network infrastructure and edge data centers. This intermediary intelligently directs traffic through optimal paths via interconnected edge data centers, reducing latency during handovers while maintaining the reliability of the underlying network infrastructure.
2Device complexity
If application workloads are hosted in centralized data centers, then infrastructure complexity is reduced, but latency during handovers increases
Solution Approach 1:
Application workloads are replicated across multiple geographically distributed edge data centers, each providing low-latency services to local users. During handovers, users are served by their nearest edge data center, minimizing latency while the distributed architecture manages complexity through localized service delivery.
Solution Approach 2:
The network architecture transitions from a single centralized dimension to a multi-dimensional distributed architecture using interconnected edge data centers. This dimensional expansion allows traffic to be routed through optimal paths in the distributed network, reducing handover latency while the standardized interconnection model manages infrastructure complexity.
3Loss of time
If network infrastructure is expanded to reduce latency, then performance improves, but infrastructure complexity increases
Solution Approach 1:
Interconnected edge data centers are designed as universal nodes capable of hosting multiple application workloads and serving multiple functions. This multi-functionality reduces the need for dedicated infrastructure for each application, managing physical infrastructure complexity while maintaining low latency through the universal edge computing platform.
Solution Approach 2:
Application workloads are pre-positioned in multiple edge data centers before handovers occur. This preliminary distribution of workloads across the edge network ensures that when handovers occur, traffic can be immediately routed to the nearest edge data center, reducing latency without requiring complex real-time infrastructure reconfiguration.
Data Source
AI summary
Techniques are described for a network providing application workload routing and application workload interworking. For example, a controller may move or replicate an application workload hosted on an original edge compute to a different edge compute in a different edge data center that is locally accessible by the device and route the network traffic to the new edge compute using paths mapped to respective traffic classes.