Anticipatory Preprocessing for Server Application Latency Reduction
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Solution Overview
Problem
Client-server software applications experience delays due to server processing time, leading to user dissatisfaction and potential abandonment of applications.
Innovation Solution
Implement anticipatory preprocessing by servers to generate and transmit additional application states based on expected finite client responses, reducing latency by preparing states before actual user input is received.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the server processes client requests in real-time, then processing accuracy is maintained, but latency increases causing user dissatisfaction
Solution Approach 1:
The server performs preliminary processing by generating additional application states in advance based on anticipated client responses. When a client sends a request, the server checks if pre-generated states are available and returns them immediately, eliminating the need for real-time processing and reducing latency.
2Loss of time
If the server generates additional states in advance, then latency is reduced, but server load increases
Solution Approach 1:
Instead of generating all possible application states in advance, the server selectively generates only those states that are likely to be requested by the client. This partial preprocessing approach reduces computational overhead while still achieving latency reduction for the most probable scenarios.
Solution Approach 2:
The system implements a caching mechanism where previously generated application states are stored and reused for subsequent requests. This self-service approach allows the server to avoid regenerating states that have already been computed, reducing redundant computational work.
3Speed
If the server stores multiple pre-generated states, then response speed increases, but memory consumption increases
Solution Approach 1:
The server extracts and stores only the essential application states that are most likely to be requested, rather than maintaining all possible states in memory. This selective extraction approach reduces memory consumption while preserving the ability to provide fast responses for anticipated requests.
Data Source
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Figure 3A
AI summary
A server that hosts an application transmits a state of the application to a client. The server determines that a response to the state is expected and that the response will be one of a finite number of possible responses. The server then generates one or more additional states utilizing at least one possible response from the finite set and provides the additional state(s) to the client. In some implementations, the server provides the additional state when the response is actually received. However, in other implementations, the server provides the additional state when generated and the client presents it when user input that equals the response is received. Additionally, in various implementations, the server may generate an additional state for each of the possible responses. However, in various other implementations, the server may generate additional states for a selected number of the possible responses.