SDN Request Handling via Automatic Client Scheduling
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Solution Overview
Problem
Existing request handling systems in software-defined networks (SDNs) face challenges in efficiently managing spikes in requests, leading to server overloading and performance degradation, as conventional approaches either require costly scaling of resources or fail to evenly distribute request loads across time slots.
Innovation Solution
Implementing automatic scheduling in SDN environments by monitoring request characteristics and adjusting control parameters for client devices to modify their request timing, thereby reducing variance and peak demand, rather than relying on server-side scaling or client-driven update timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server-side resource scaling is implemented to handle request spikes, then system reliability is improved, but device complexity and cost increase
Solution Approach 1:
Instead of scaling server resources to handle request spikes (traditional approach), the patent inverts the problem by having client devices adjust their request timing. The server monitors request characteristics and assigns control parameters to clients, who then autonomously modify their request schedules to avoid peak periods, thereby maintaining server reliability without additional server resources.
Solution Approach 2:
The patent implements self-service by enabling client devices to autonomously adjust their own request timing based on control parameters received from the server. Each client device monitors its own request patterns and automatically modifies its scheduling without requiring manual intervention or complex server-side load balancing mechanisms.
2Manufacturing precision
If uniform update timing is enforced across all client devices, then manufacturing precision is improved, but object-generated harmful factors increase due to request spikes
Solution Approach 1:
The patent applies local quality by assigning individualized control parameters to different client devices based on their specific request patterns and characteristics. Instead of uniform timing enforcement, each client receives customized scheduling adjustments that maintain precision for that particular device while avoiding the harmful request spikes that would result from synchronized updates across all devices.
Solution Approach 2:
The system transitions from static uniform update timing to dynamic adaptive scheduling. The server continuously monitors request characteristics and adjusts control parameters in real-time, allowing client devices to dynamically modify their update timing based on current system conditions, thereby maintaining precision while avoiding request spikes.
3Ease of operation
If client-driven update timing is allowed, then ease of operation is improved, but productivity deteriorates due to uneven request distribution
Solution Approach 1:
The patent implements feedback by having the server continuously monitor request characteristics from all client devices and use this information to adjust control parameters assigned to individual clients. This closed-loop system maintains client scheduling flexibility while ensuring that aggregate request distribution remains balanced, thereby preserving both ease of operation and productivity.
Data Source
AI summary
Example methods and systems for request handling with automatic scheduling are described. In one example, a computer system may receive, from multiple client devices, respective multiple requests that are generated and sent according to a first set of control parameters. Based on the multiple requests, request characteristic(s) may be monitored to determine whether an automatic scheduling condition is satisfied. In response to determination that the automatic scheduling condition is satisfied, the computer system may assign a second set of control parameters to the respective client devices and instruct the client devices to generate and send respective multiple subsequent requests according to the second set of control parameters to cause a modification of the request characteristic(s).