IT Resource Allocation via Physical Location Mapping
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Solution Overview
Problem
Existing cloud computing systems face challenges in dynamically assigning IT resources to pools to increase available capacity, as existing solutions treat resource assignments as static and fail to efficiently manage resource movement across different locations within a datacenter.
Innovation Solution
An IT allocation system that maps physical locations within a datacenter to specific resource pools, allowing resources to be automatically reassigned based on their location, either through wired or wireless networking, enabling dynamic reassignment without disconnecting from the network and easing management burdens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If physical resources are assigned to specific pools statically, then the assignment is simple and stable, but the pool elasticity and resource utilization are reduced
Solution Approach 1:
The patent implements dynamic resource allocation by enabling resources to move between pools based on demand. The allocation mechanism transitions from static assignments to dynamic reassignment, where resources can be automatically moved between pools without complicated manual procedures, thus improving pool elasticity while maintaining manageable complexity through automated processes.
Solution Approach 2:
The system enables resources to self-assign to appropriate pools based on predefined criteria and conditions. The allocation mechanism automatically determines which pool a resource should join based on current system state and resource characteristics, eliminating the need for complex manual intervention while maintaining adaptability.
2Reliability
If resources are moved between pools manually with awareness of allocation internals, then the datastore remains synchronized, but the management burden increases and productivity decreases
Solution Approach 1:
The patent implements automated feedback mechanisms that monitor resource locations and pool states continuously. When a resource moves between pools, the system automatically detects the movement and updates the datastore accordingly, ensuring synchronization without requiring manual awareness of allocation internals. This maintains reliability while dramatically improving productivity by eliminating manual tracking efforts.
Solution Approach 2:
The manual mechanical process of tracking and updating resource allocations is replaced with an automated electronic system. The allocation mechanism uses software-based tracking and automatic updates to maintain datastore synchronization, substituting human manual operations with automated computational processes that are both more reliable and more efficient.
3Productivity
If dynamic allocation is implemented without physical location mapping, then resource distribution is flexible, but the ability to optimize based on physical constraints is lost
Solution Approach 1:
The patent applies local quality by considering physical location characteristics when allocating resources to pools. Different pools are associated with specific physical locations or data centers, and resources are allocated based on both logical requirements and physical constraints. This enables optimization for local factors such as latency, bandwidth, and physical proximity while maintaining overall dynamic allocation flexibility.
Solution Approach 2:
The patent adds a physical location dimension to the traditional logical resource allocation model. By mapping pools to physical locations and considering spatial constraints in addition to logical requirements, the system optimizes resource distribution across multiple dimensions - both logical pool membership and physical location - thereby improving overall distribution efficiency while maintaining adaptability.
Data Source
AI summary
An approach for allocating information technology (IT) resources in a networked computing environment (e.g., a cloud computing environment) based on physical location mapping is provided. Specifically, an IT allocation system assigns resources to a specific cloud pool based on the physical location of the resources. By mapping a given physical location (e.g., a defined region of a grid defining a datacenter) to a specific pool, and by enabling the tracking of a resource to a location within the datacenter, the approach can automatically assign a resource to a cloud pool based upon its physical location. Thus, the IT allocation system provides additional pool elasticity while easing the management burden.