Prefetching Model Optimizes WAN Latency
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Solution Overview
Problem
In wide area networks (WANs), determining what data to prefetch and when to perform prefetching operations is challenging, as unnecessary prefetching wastes resources, while frequent prefetching decreases system performance, leading to conflicts between cost management and application performance.
Innovation Solution
Implementing a prefetching model that defines data to be prefetched based on specific applications and users, with criteria such as time of day, processor load, and network activity, to optimize data retrieval and reduce latency by prefetching during off-peak times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data prefetching is performed frequently to reduce latency, then application performance is improved, but system resources are wasted and overall performance decreases
Solution Approach 1:
The system performs preliminary actions by prefetching data before it is actually requested by applications. The prefetching model identifies data that is likely to be needed soon and retrieves it in advance during off-peak times, reducing perceived latency when the data is actually needed while avoiding continuous prefetching that would waste resources.
Solution Approach 2:
The prefetching system is dynamic and adaptive, adjusting its behavior based on current system conditions. The model evaluates multiple factors including time of day, processor load, network activity, and data access patterns to dynamically determine what data to prefetch and when, rather than using a fixed prefetching schedule.
2Loss of time
If data prefetching is performed to reduce perceived latency, then application performance is improved, but bandwidth is consumed during peak times
Solution Approach 1:
The system performs data retrieval in advance during off-peak periods when bandwidth is more available and less expensive. By prefetching data before peak usage times, the system reduces perceived latency for users without consuming excessive bandwidth during critical peak periods.
Solution Approach 2:
The prefetching model employs periodic action by scheduling prefetching operations during specific periods (off-peak times) rather than continuously. The model monitors system conditions and performs prefetching during periods when processor load is lower and network activity is reduced, thereby optimizing bandwidth usage patterns.
Data Source
AI summary
A data prefetching technique uses predefined prefetching criteria and prefetching models to identify and retrieve prefetched data. A prefetching model that defines data to be prefetched via a network may be stored. It may be determined whether prefetching initiation criteria have been satisfied. Data for prefetching may be identified based on the prefetching model when the prefetching initiation criteria have been satisfied. The identified data may be prefetched, via the network, based on the prefetching model.