Request Processing Resource Constraints for Server Efficiency
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Solution Overview
Problem
Data servers face challenges in processing multiple concurrent requests efficiently, leading to unpredictable delays and inefficiencies due to resource constraints, which can result in incomplete results and increased costs for storage and processing.
Innovation Solution
Implementing predefined resource constraints on request processing, allowing for partial result generation and status information storage to enable resumption of requests, using both detailed and approximate state information to manage storage costs and processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the data server processes multiple concurrent requests without resource constraints, then the requests can be completed fully, but substantial delays occur and resource allocation becomes unfair
Solution Approach 1:
The patent applies partial action by allowing requests to be processed partially up to defined resource constraints rather than requiring complete processing. When resource limits are reached, the server terminates the request and returns partial results, enabling fair resource allocation across multiple concurrent requests while still providing useful output to clients.
2Reliability
If the data server allocates resources to complete all requests, then full results are obtained, but resource efficiency decreases and other requests suffer delays
Solution Approach 1:
The system processes requests partially by imposing resource constraints (CPU time, memory, I/O operations) and terminates requests when constraints are reached, returning partial results. This improves resource efficiency and throughput while maintaining acceptable result quality for many applications.
Solution Approach 2:
The patent changes the parameter of request processing from all-or-nothing to constrained partial processing by introducing resource limit parameters (CPU seconds, memory usage, I/O operations). This allows the server to manage multiple requests concurrently with fair resource allocation while maintaining overall system productivity.
3Reliability
If the data server stores detailed state information for terminated requests to enable resumption, then accurate resumption is possible, but storage costs increase
Solution Approach 1:
The system changes the state information storage from detailed to approximate by tracking only essential parameters (resource usage counters, processing stage) rather than complete request state. This reduces storage costs significantly while still enabling effective resumption of requests, as the approximate state is sufficient to continue processing from where it was terminated.
Data Source
AI summary
A server system having one or more processors and memory receives a first request from an application and processes at least a portion of the first request in accordance with a predefined set of resource constraints. In accordance with a determination that the predefined set of resource constraints has been met prior to completing processing the first request, the server system terminates processing of the first request prior to completing processing of the first request, generates a first intermediate result; and provides a response to the application. The response includes the first intermediate result, and request status information enabling the application to request resumption of the first request.