Predictive Connection Manager Reducing Latency
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Solution Overview
Problem
Service provider networks face challenges in handling peak service requests, leading to high latencies and inefficient resource utilization due to unpredictable user access patterns, especially during morning and lunchtime usage peaks.
Innovation Solution
The Predictive Connection Manager Service (PCMS) analyzes historical usage data to generate predictive models that anticipate service requests, proactively establishing connections and caching data to reduce latency and resource bottlenecks, and implements rate limiting to manage high request volumes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If service providers handle peak service requests with traditional network infrastructure, then service requests can be processed, but latency increases and resource utilization becomes inefficient
Solution Approach 1:
The system performs preliminary actions by proactively establishing network connections and caching data before peak usage periods occur. The predictive connection manager analyzes historical usage patterns to anticipate future requests and pre-establishes connections to backend services, so when users actually access services during peak times, the connections are already ready, reducing latency and improving resource utilization efficiency.
2Reliability
If the network handles all service requests during peak times, then user access is maintained, but network resources become overloaded and response times increase
Solution Approach 1:
The system proactively establishes connections and caches data before peak usage periods, so when requests arrive during peak times, the infrastructure is already prepared and can handle requests efficiently without becoming overloaded.
Solution Approach 2:
The predictive connection manager acts as an intermediary between users and backend services. It sits in the network path, analyzes usage patterns, and manages connection establishment and data caching, thereby mediating the interaction during peak periods to maintain service availability while improving request handling efficiency.
3Loss of time
If the system waits for user requests before establishing connections, then resource consumption is minimized, but response time increases during peak usage
Solution Approach 1:
The system performs preliminary connection establishment and data caching actions based on predictive models of future usage patterns. By anticipating when users will need connections and pre-establishing them, the system reduces response time during peak usage periods while managing resource consumption through intelligent prediction rather than continuous operation.
Data Source
AI summary
Techniques for a Predictive Connection Manager Service (PCMS) to predict when client applications will send service requests to backend services, and proactively establishes connections, caches data, or takes other actions, to reduce latencies between receipt of and response to these service requests. The PCMS analyzes historical usage data for the client applications to identify usage patterns, and uses those usage patterns to proactively scale resources to handle service requests. The PCMS can be implemented as a pass-through proxy for client applications to reduce frictions for managing how users interact with backend services. For instance, the PCMS can install client-side drivers such that updates or patches for the drivers need only be installed on the PCMS rather than on each client device. Further, the PCMS provides interfaces through which users can develop custom drivers for backend services, and also manages software drivers for different service provider networks, thus offering multi-provider connectors.