Dynamic Link Aggregation for Cloud Workload Adaptation
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Solution Overview
Problem
Existing link aggregation management in cloud computing environments is inefficient due to the need for manual reconfiguration of network infrastructure to adapt to changing workloads, which can lead to suboptimal network performance and increased administrative burdens.
Innovation Solution
Implement a dynamic configuration of link aggregation groupings based on real-time monitoring of network utilization and performance data, automatically adjusting network interface cards, network switches, and DNS settings to align with the characteristics of cloud computing workloads, thereby establishing an optimal link aggregation arrangement without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual reconfiguration of network infrastructure is performed to adapt to changing workloads, then network performance can be optimized, but administrative burden increases and response time decreases
Solution Approach 1:
The system enables automatic link aggregation management where the network infrastructure self-configures based on monitored workload characteristics. The patent implements automated detection of workload patterns, dynamic determination of optimal link aggregation arrangements, and automatic reconfiguration without human intervention, allowing the system to serve itself and eliminate manual administrative tasks.
Solution Approach 2:
The patent implements dynamic link aggregation management where the network configuration automatically adapts to changing workload conditions. The system continuously monitors network utilization and performance data, dynamically determines optimal link aggregation arrangements, and automatically reconfigures network interface cards and switches in real-time to match current workload demands, transforming static manual configuration into dynamic automated adaptation.
2Reliability
If manual reconfiguration is used to adapt network infrastructure to changing workloads, then network performance can be optimized, but response time to workload changes decreases
Solution Approach 1:
The system implements continuous monitoring of network utilization and performance data to gather feedback on actual workload conditions. This feedback loop enables the system to detect workload changes in real-time, analyze the impact on network performance, and automatically adjust link aggregation configurations accordingly, ensuring the network responds immediately to changing conditions without manual intervention delays.
Solution Approach 2:
The patent implements proactive link aggregation management where the system continuously monitors workload characteristics and prepares optimal network configurations in advance. By detecting workload patterns and predicting future network demands, the system can pre-configure link aggregation arrangements before performance degradation occurs, enabling seamless adaptation to changing workloads without response delays.
3Adaptability or versatility
If dynamic configuration is implemented, then network flexibility and adaptability improve, but system complexity increases
Solution Approach 1:
The patent implements a universal link aggregation management system that consolidates multiple functions into a single automated platform. The system performs workload monitoring, performance analysis, configuration determination, and automatic reconfiguration across network interface cards, switches, and other infrastructure components, replacing multiple manual administrative tasks with one multi-functional automated solution that simplifies overall system management despite increased operational complexity.
Data Source
AI summary
Disclosed aspects relate to managing link aggregation with respect to a shared pool of configurable computing resources. A set of workloads of the shared pool of configurable computing resources can be monitored to identify a set of networking data. Based on the set of networking data, a link aggregation arrangement for dynamic adjustment may be determined. The link aggregation arrangement may be established by dynamic adjustment with respect to the shared pool of configurable computing resources.


