Geographic Network Allocation for Distributed Resource Efficiency
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Solution Overview
Problem
Conventional cloud computing networks face inefficiencies in resource distribution due to the decentralization of resource use, necessitating a shift from static network hub-based allocation to dynamic geographic location-based allocation, which can be optimized by segregating resources by type and considering actual locations to enhance efficiency.
Innovation Solution
A system that dynamically selects network allocation sites based on geographic location using a linear programming algorithm, segregating resources by type and applying geographic limitations to ensure optimal efficiency, incorporating guardrails to manage infrastructure constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a static network hub-based allocation model is used, then start-up costs are lowered and current network infrastructure is utilized efficiently, but resource allocation efficiency deteriorates due to decentralization of resource use
Solution Approach 1:
The patent implements dynamic selection of network allocation sites based on real-time geographic location data and resource type characteristics. The system continuously evaluates and reassigns resources to optimal locations rather than using fixed hub assignments, enabling the allocation model to adapt to changing deployment patterns and maximize efficiency while managing infrastructure costs
Solution Approach 2:
The patent segments resources by type (e.g., compute, storage, database) and determines optimal network allocation sites for each resource type based on its specific characteristics and deployment patterns. This localized optimization approach allows different resource types to be allocated from geographically optimal locations rather than from a single static hub, improving overall allocation efficiency
2Device complexity
If distributed resources are treated as homogenous resources, then resource management is simplified, but allocation efficiency deteriorates due to ignoring resource type variations
Solution Approach 1:
The patent divides distributed resources into distinct resource types (compute, storage, database, etc.) and applies type-specific allocation strategies. Each resource type is evaluated independently to determine its optimal network allocation site based on characteristics relevant to that specific type, enabling optimized allocation without overwhelming complexity through systematic categorization
3Loss of energy
If network allocation sites are selected based on static hub locations, then infrastructure utilization is optimized, but resource distribution efficiency deteriorates due to ignoring actual geographic locations
Solution Approach 1:
The patent changes the selection criteria for network allocation sites from static hub location parameters to dynamic parameters that include actual geographic locations of resources and users, resource type characteristics, and efficiency metrics. This parameter transformation enables the system to select optimal allocation sites based on real-world deployment patterns rather than fixed infrastructure locations
Data Source
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AI summary
Systems and methods are for increasing the efficiencies of distributed resources in a network through the selection of network allocation sites that maximize efficiency of the distributed resources. The system segregates each of these into a resource type. The system then determines based on a geographic location (as opposed to a network location), the ideal network allocation site for use in allocating the distributed resources of the given type. The network allocation site represents the geographic location that forms the epicenter of distribution of the distributed resources.