Service Request Allocation Through Idle-Resource Device Subsets
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Solution Overview
Problem
Existing service request allocation methods require frequent real-time calculations to update load information, leading to inefficiencies in load balancing among service devices.
Innovation Solution
A method that divides a service device set into subsets based on idle resources, determines a target subset using allocation weights, and selects a target service device within that subset to allocate service requests, reducing the need for real-time load updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If service requests are allocated using traditional load balancing methods (polling or minimum load), then load information of each service device must be updated in real time, but this results in low allocation efficiency due to large numbers of real-time calculations
Solution Approach 1:
The patent segments the service device set into multiple service device subsets based on idle resource levels. Instead of evaluating all service devices individually for each request, the system divides them into groups (e.g., high idle resource, medium idle resource, low idle resource subsets), reducing the scope of real-time evaluation and improving allocation efficiency while maintaining load balancing accuracy.
Solution Approach 2:
The patent performs preliminary classification of service devices into subsets based on idle resources before actual service request allocation. This pre-grouping action eliminates the need for real-time individual device evaluation during request processing, as the allocation can directly reference the pre-established subsets and their corresponding allocation weights.
2Reliability
If load information is updated in real time for each service request allocation, then load balancing is maintained, but the calculation overhead increases significantly
Solution Approach 1:
The patent implements periodic updates of service device subsets and allocation weights instead of continuous real-time updates. The system periodically re-evaluates idle resources and recalculates allocation weights at predetermined intervals, reducing calculation overhead while maintaining adequate load balancing. This periodic approach replaces frequent real-time calculations with less frequent batch updates.
Solution Approach 2:
The system performs load information evaluation and subset classification in advance, before actual service request processing. This preliminary action allows the allocation system to use pre-calculated allocation weights and subset assignments, eliminating the need for intensive real-time calculations during request handling while preserving load balancing effectiveness.
3Measurement precision
If service devices are evaluated individually for each request, then precise allocation is achieved, but the complexity of the allocation process increases
Solution Approach 1:
The patent simplifies the allocation process by segmenting service devices into subsets with similar characteristics (idle resource levels). Instead of evaluating each device individually, the system evaluates subsets as groups, reducing the complexity of the allocation process. The allocation weight is calculated at the subset level, making the overall process more manageable and less complex.
Solution Approach 2:
The patent introduces service device subsets as an intermediary layer between individual service devices and the allocation decision. This intermediate grouping structure simplifies the allocation process by providing a middle level of abstraction, where allocation weights are assigned to subsets rather than individual devices, reducing the overall complexity of the allocation mechanism.
Data Source
AI summary
A service request allocation method is provided, performed by a computer device, the method including receiving a service request that needs to be processed; dividing a service device set into a plurality of service device subsets, the plurality of service device subsets being grouped based on an idle resource of each service device in the service device set; determining a target service device subset that matches the service request according to an allocation weight corresponding to each service device subset; selecting a target service device from the target service device subset; and allocating the service request to the target service device, the target service device being configured to perform a service corresponding to the allocated service request.