Edge Cloud Platform Deployment via SDN Segmentation
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Solution Overview
Problem
Current edge computing solutions face challenges in rapidly deploying and managing dynamic services at the edge of networks to meet the demands of Over the Top (OTT) services and other applications, while ensuring high availability and compliance with service level agreements (SLAs) to avoid penalties.
Innovation Solution
A cloud platform is deployed with intelligent, independent edge components that automatically manage computing, networking, and storage resources, including legacy components, using software-defined networking (SDN) and network overlay technologies to provide Edge as a Service (EaaS), enabling zero-touch provisioning and high availability through automated scaling, failover, and lifecycle management of control plane elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If cloud computing resources are deployed at the network edge to reduce congestion and improve response time, then service speed and responsiveness are improved, but device complexity and deployment difficulty increase
Solution Approach 1:
The cloud platform is segmented into modular functional components (control plane, data plane, management interfaces) that can be independently deployed and managed at the network edge. This modular architecture allows incremental deployment and reduces overall system complexity while maintaining fast local response times for edge services.
Solution Approach 2:
An edge computing platform acts as an intermediary layer between core network infrastructure and end-user devices. This intermediary manages the complexity of edge deployment by providing standardized interfaces and automated provisioning, enabling rapid service deployment without directly complicating the underlying network infrastructure.
2Productivity
If dynamic services are rapidly deployed at the network edge to meet OTT service demands, then productivity and service deployment speed are improved, but reliability and service availability may deteriorate
Solution Approach 1:
The edge computing platform implements pre-configured failover mechanisms and redundant service copies before failures occur. When deploying dynamic services, the system automatically provisions backup instances and establishes failover paths in advance, ensuring that service availability is maintained even as deployment speed increases and services are rapidly scaled.
Solution Approach 2:
The platform incorporates continuous health monitoring and automated feedback loops that track service performance and availability at the edge. This feedback mechanism enables real-time detection of service degradation and triggers automated remediation actions, allowing rapid service deployment while maintaining reliability through continuous validation and adjustment.
3Ease of operation
If automated management systems are implemented to manage edge resources, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The edge computing platform implements self-service automation where the system automatically provisions, configures, and manages computing, storage, and networking resources without manual intervention. This self-service capability simplifies operation for users while the underlying automation handles the complexity of resource orchestration, effectively decoupling ease of operation from system complexity.
Data Source
AI summary
The technique includes determining parameters of a cloud platform associated with an edge computing service associated with a network. The technique includes deploying the cloud platform, including configuring equipment external to the network and configuring equipment of the network.