Network Service Migration for Real-Time Performance Control
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Solution Overview
Problem
Existing NFV and SDN technologies face challenges in efficiently managing network services to ensure flexibility, cost-effectiveness, and service reliability, particularly in real-time operations and dynamic service migrations.
Innovation Solution
The implementation of methods and systems that enable real-time operation control by analyzing network service performance, automatically adjusting network configurations, and migrating services between devices based on measured versus expected performance thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If network services are manually managed and monitored, then operational control and performance analysis are achieved, but operational complexity and time consumption increase
Solution Approach 1:
The system enables automatic service migration without manual intervention. The controller autonomously monitors service performance metrics, compares them against thresholds, and executes migration decisions based on predefined policies, allowing the network system to self-manage and optimize its own operation.
Solution Approach 2:
The system continuously monitors service performance metrics and uses this feedback to trigger automatic migrations. The controller receives performance data, analyzes it against threshold criteria, and adjusts service placement accordingly, creating a closed-loop control system that adapts to changing network conditions.
2Reliability
If real-time performance monitoring and automatic adjustment are implemented, then service reliability is improved, but system complexity and computational overhead increase
Solution Approach 1:
The system pre-establishes performance thresholds and migration policies before issues arise. By defining expected service levels and automatic response rules in advance, the system can rapidly respond to performance degradation without complex real-time decision-making, reducing computational overhead during critical moments.
Solution Approach 2:
The system monitors changes in service performance parameters (such as latency, throughput, packet loss) and triggers migrations when parameters cross predefined thresholds. This parameter-driven approach simplifies the control logic by reducing complex performance assessment to straightforward threshold comparisons.
3Adaptability or versatility
If network services are dynamically migrated between devices, then flexibility and resource optimization are achieved, but service disruption and operational risk increase
Solution Approach 1:
The system performs preliminary actions by establishing migration policies and thresholds in advance, and by preparing migration pathways before service disruption occurs. This allows migrations to execute smoothly without unexpected interruptions, as the infrastructure and procedures are pre-configured to handle the transition.
Solution Approach 2:
The system implements beforehand cushioning by monitoring service performance continuously and triggering migrations proactively before failures occur. By acting in anticipation of potential service degradation rather than reacting to catastrophic failures, the system cushions against service disruption and maintains continuous operation.
Data Source
AI summary
Methods, systems, and apparatuses, for real-time operation control, among other things. There may be adjustments to a first device in which a first network service operates. The adjustment to the device may include moving a second network service of the first device to a second device. The first network service and the second network service may be associated with virtual machines.