VM Placement Optimizing Storage and Network Metrics

The patent merges network layer metrics and storage layer metrics into a unified multi-objective optimization framework. The placement system simultaneously considers network throughput, latency, storage I/O performance, and application requirements to determine optimal VM placement, resolving the contradiction by integrating previously separate optimization criteria into a comprehensive approach that balances both network and storage performance

The patent changes the optimization parameters from solely network-based metrics to a multi-dimensional set including storage performance metrics (I/O throughput, latency), network metrics, and application-specific requirements. This parameter expansion allows the system to evaluate placement options based on a broader set of criteria, preventing suboptimal placements that would compromise storage performance while maintaining network efficiency

The patent combines network latency optimization with storage I/O performance optimization and application requirement satisfaction in a unified multi-objective framework. By simultaneously considering multiple performance dimensions rather than optimizing for network latency alone, the system achieves better overall application performance while maintaining acceptable network responsiveness

The patent performs preliminary gathering of storage performance data, network performance data, and application requirement data before making placement decisions. This advance information collection enables the optimization algorithm to evaluate multiple criteria upfront and select placement locations that will deliver balanced performance across all dimensions, preventing subsequent performance degradation

The patent creates a universal placement optimization system that handles multiple metrics through a single multi-objective optimization framework. This unified approach consolidates what would otherwise require separate optimization processes into one system that simultaneously evaluates network metrics, storage metrics, and application requirements, improving placement accuracy while managing complexity through integration rather than multiplication of separate systems

The system automatically gathers performance data from storage arrays and network infrastructure, and autonomously performs optimization calculations without requiring manual configuration or intervention. This self-service capability handles the increased complexity of multi-metric optimization automatically, allowing accurate placement decisions without proportionally increasing operational complexity for users