Cloud Management System for Dynamic Network Resource Scaling
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Solution Overview
Problem
Organizations face challenges in determining the optimal time and method to utilize external cloud services to manage network resource scaling, balancing internal resource utilization with external cloud bursting, due to complexities in market conditions and economic considerations.
Innovation Solution
A cloud management system that creates application models with defined substitution points and policies, using a scoring function to select the best resource type for scaling, allowing for dynamic resource allocation between internal and external networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If organizations rely on internal IT infrastructures to accommodate network activity increases, then they maintain control and security over their systems, but they cannot scale efficiently when internal resources are over-utilized
Solution Approach 1:
The patent segments the IT infrastructure into internal and external cloud components. The hybrid cloud architecture divides workloads between on-premises resources and external cloud services, allowing organizations to scale specific functions externally while maintaining core control internally. This segmentation enables independent scaling of different application components without requiring complete infrastructure overhaul.
Solution Approach 2:
The patent implements multi-functionality by enabling the same application to operate in multiple environments (internal and external cloud). The system can dynamically route workloads between internal infrastructure and external cloud services based on demand, making the infrastructure universally adaptable to different scaling scenarios without requiring separate systems for each mode.
2Productivity
If organizations enter into cloud service contracts to expand IT infrastructures, then they gain access to economies of scale and dynamic resource allocation, but they face challenges in determining optimal timing and methods for utilizing external services
Solution Approach 1:
The patent implements dynamic resource allocation through automated policies that continuously monitor internal resource utilization and automatically provision or de-provision external cloud resources based on real-time demand. This dynamic approach eliminates manual decision-making about when to use external services, allowing the system to adapt automatically to changing workload conditions while optimizing cost and performance.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor internal infrastructure performance metrics and automatically trigger external cloud resource provisioning when thresholds are exceeded. The feedback loop continuously evaluates resource utilization, cost implications, and performance requirements to make intelligent decisions about optimal resource allocation between internal and external environments.
3Adaptability or versatility
If organizations dynamically scale IT infrastructures using cloud services, then they can accommodate fluctuating network activity, but they face challenges in managing the complexity of market conditions and economic considerations
Solution Approach 1:
The patent implements self-service automation where the system autonomously manages the complexity of cloud resource provisioning, cost optimization, and performance balancing without requiring manual intervention. Automated policies and algorithms handle the operational complexity of dynamic scaling, market condition analysis, and economic trade-off evaluation, making the system easy to operate despite its sophisticated underlying mechanisms.
Data Source
AI summary
A method of network resource management comprising, with a processor, creating a model of an application, defining a number of substitution points within the model, expressing the substitution points as abstract models with a set of sub-types, and codifying a number of policies that express which sourcing option to use for each substitution point.