Cloud Capacity Manager Dynamic Resource Allocation
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Solution Overview
Problem
Computer systems face challenges in balancing costs with fluctuating resource demands, as purchasing capacity to meet peak demands is costly and results in underutilization during non-peak times, while purchasing for average demand leads to performance issues during peaks.
Innovation Solution
A cloud capacity on demand manager that borrows and lends capacity across servers in a server cloud, enabling flexible resource allocation by temporarily utilizing unused capacity from other servers during peak times and reclaiming resources when no longer needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a company purchases a computer system that is capable of meeting peak demand, then the performance during peak times is improved, but the cost increases and much of the capacity goes unused during non-peak times
Solution Approach 1:
The patent implements dynamic capacity adjustment by enabling or disabling additional processors based on demand conditions. The system transitions from a static fixed capacity model to a dynamic model where capacity can be activated only when needed, allowing the company to meet peak demand when it occurs while avoiding the cost of maintaining unused capacity during normal operation periods.
Solution Approach 2:
The patent changes the capacity parameter from a fixed state to a variable state. By modifying the operational state of additional processors between enabled and disabled configurations, the system adapts its effective capacity to match actual demand patterns, resolving the contradiction between having sufficient capacity for peaks and avoiding waste during non-peak periods.
2Quantity of substance
If a company purchases a computer system that is capable of meeting average demand, then the cost is reduced, but the performance of the computer system suffers during peak times
Solution Approach 1:
The patent prepares additional processors in advance by installing them in the system but keeping them in a disabled state. This preliminary configuration allows the system to quickly activate extra capacity when peak demand occurs, ensuring performance reliability during peaks while maintaining lower average costs by not permanently maintaining the full capacity.
3Quantity of substance
If additional processors are installed but initially disabled to provide capacity on demand, then the cost is reduced during non-peak times, but the system complexity increases
Solution Approach 1:
The patent implements self-service capacity management where the system automatically monitors its own load and manages the enabling/disabling of additional processors without requiring manual intervention. This automated approach handles the complexity internally while presenting a simple interface to users, allowing cost reduction through on-demand capacity activation without increasing operational complexity.
Data Source
AI summary
A cloud capacity on demand manager manages capacity on demand for servers in a server cloud. The cloud capacity on demand manager may borrow capacity from one or more servers and lend the capacity borrowed from one server to a different server in the server cloud. When the server cloud is no longer intact, capacity borrowed from servers no longer in the server cloud is disabled, and servers no longer in the server cloud reclaim capacity that was lent to the server cloud.