Affinity-Based Peer-to-Peer Resource Allocation System
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Solution Overview
Problem
Existing peer-to-peer distribution systems face challenges in efficiently allocating resources among user devices based on affinity indicators, leading to inefficiencies in resource matching and transfer.
Innovation Solution
A real-time peer-to-peer affinity-based resource allocation system that uses a weighted prioritization algorithm to generate a prioritized queue of resource requests and iteratively compares affinity indicators of provider devices with requesting devices to allocate resources securely and efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a peer-to-peer distribution system allocates resources without affinity-based prioritization, then the system structure remains simple, but resource matching efficiency deteriorates
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing affinity indicators for each device, and maintaining a prioritized queue of resource requests before actual resource allocation occurs. This allows the system to quickly match resources during runtime without complex real-time calculations, thereby improving resource matching efficiency while keeping the system structure manageable.
Solution Approach 2:
The patent introduces an allocation computer as an intermediary between requesting devices and provider devices. This intermediary manages the complex affinity-based prioritization logic, maintaining a prioritized queue and making allocation decisions based on affinity indicators. By centralizing this logic in an intermediary component, the system achieves efficient resource matching without distributing complex algorithms across all peer devices.
2Measurement precision
If the system uses iterative affinity comparison to match provider devices with requesting devices, then resource allocation accuracy improves, but processing time increases
Solution Approach 1:
The system applies partial action by iteratively comparing affinity indicators starting from the highest priority request and stopping once a sufficient match is found. The iterative comparison process does not exhaustively evaluate all possible combinations but rather performs partial comparisons until the affinity threshold is met, thereby achieving adequate matching accuracy without excessive processing time.
Solution Approach 2:
Affinity indicators are pre-calculated and stored for each device before resource allocation requests occur. This preliminary computation of affinity metrics allows the iterative comparison process to work with pre-prepared data rather than calculating affinities in real-time, significantly reducing processing time while maintaining matching accuracy.
3Productivity
If the system prioritizes high-affinity resource requests, then resource utilization efficiency improves, but wait time for low-priority requests increases
Solution Approach 1:
The system implements dynamic priority adjustment where the prioritized queue is continuously updated based on incoming requests and resource availability. Low-priority requests are not permanently stuck but can move up in priority as higher-priority requests are fulfilled or as resources become available. This dynamic reordering ensures efficient resource utilization for high-affinity matches while eventually serving lower-priority requests, balancing both goals.
Solution Approach 2:
The allocation system operates continuously, constantly monitoring resource availability and updating the prioritized queue. Rather than batch-processing requests, the system maintains continuous useful action by immediately allocating resources when matches are found and continuously re-evaluating the queue, ensuring that low-priority requests eventually receive service without excessive waiting while high-priority requests are handled efficiently.
Data Source
AI summary
An allocation computer may receive and store requirements in the peer-to-peer affinity-based distribution system. The allocation computer may generate from the received requirements, a prioritized queue of the received requirements, wherein the prioritized queue is generated by assigning weights to affinity indicators present in the received requirements. A plurality of fulfilment devices among the user devices, that are ready to transfer resources are identified. Each fulfilment device is associated with multiple affinity indicators. An allocation computer may for fulfilling a first requirement in the prioritized queue, match affinity indicators of a first fulfilment device with the affinity indicators present in the first requirement. The affinity matching is performed iteratively for each affinity indicators of the first fulfilment device. Resources from the first fulfilment device may be allocated to requesting device.