Network Request Prioritization via Traffic Elasticity Analysis
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Solution Overview
Problem
Current network optimization strategies fail to effectively prioritize network requests and file transfers due to the volatility of wireless networks, leading to inconsistent user experiences and improper TCP parameter settings, which can result in poor performance or catastrophic failures in web page loading and application functionality.
Innovation Solution
A system that measures the elasticity of data objects and network parameters to dynamically optimize network requests and file transfers by generating optimized values for TCP parameters, such as maximum burst size and concurrent connections, ensuring efficient bandwidth utilization and avoiding failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network requests are made with default TCP parameters, then the system can operate with simple configuration, but network performance deteriorates due to improper parameter settings causing poor performance or catastrophic failures
Solution Approach 1:
The system automatically determines elasticities and generates optimized TCP parameter settings without requiring manual configuration. The network optimization component autonomously measures elasticities of data objects and network parameters, then generates and applies optimized parameter values, allowing the system to self-optimize network performance without user intervention or complex configuration
Solution Approach 2:
The system dynamically changes TCP parameters based on measured elasticities. By determining the elasticity of data objects with respect to TCP parameters like maximum burst size and concurrent connections, the system generates optimized parameter values that adapt to specific network conditions and data object characteristics, transforming fixed default parameters into dynamic optimized settings
2Reliability
If wireless network volatility is not accounted for, then the system operates with simpler assumptions, but user experience deteriorates due to inconsistent performance
Solution Approach 1:
The system incorporates feedback loops that measure actual network performance and elasticity characteristics, then use this information to generate optimized parameter settings. By continuously determining elasticities through measurement and using this feedback to adjust TCP parameters, the system adapts to wireless network volatility and maintains consistent user experience across varying network conditions
Solution Approach 2:
The system transitions from static default parameters to dynamic optimized parameters that adapt to changing network conditions. By measuring elasticities under different network states and generating parameter settings that reflect current conditions, the system makes TCP parameters dynamic rather than fixed, enabling adaptation to wireless network volatility
3Productivity
If TCP parameters are not optimized, then the system uses standard packet transfer methods, but bandwidth utilization deteriorates leading to inefficient data transfer
Solution Approach 1:
The system performs preliminary elasticity measurements and generates optimized parameter settings before actual data transfers occur. By determining elasticities in advance and pre-generating optimized TCP parameter values, the system prepares optimal transfer settings that maximize bandwidth utilization before data transmission begins, rather than using generic parameters during transfer
Solution Approach 2:
The system changes TCP parameters to optimize bandwidth utilization based on measured elasticities. By generating optimized values for parameters like maximum burst size and concurrent connections specific to each data object and network condition, the system transforms standard packet transfer into optimized transfers that efficiently exploit available bandwidth
Data Source
AI summary
Network requests are made to download a data object with different settings of network parameters. Download outcomes of the data object as requested by the network requests are determined. An elasticity of downloading the data object is determined with respect to a specific network parameter in the network parameters. The elasticity is used to generate a network optimization policy that identifies an optimal value for the specific network parameter to be implemented by user devices and/or other devices/elements for downloading the data object.