Streaming Software Installation via Dynamic Recipe Pre-fetching
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Solution Overview
Problem
Conventional streaming installation methods fail to efficiently handle non-linear execution scenarios of software applications, leading to poor performance and increased complexity in the software development process.
Innovation Solution
A computer-implemented method that uses a recipe file to nonlinearly order application chunks, aggregates access information to identify missing chunks, and generates a revised recipe file for pre-fetching, thereby improving streaming installation performance by crowdsourcing cache miss data from multiple client devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pre-fetching content is engineered assuming strict linear execution, then installation speed is improved under ideal conditions, but performance deteriorates in real-world non-linear execution scenarios
Solution Approach 1:
The system performs preliminary actions by pre-fetching application chunks before they are actually needed during execution. The recipe file specifies which chunks to pre-fetch and when, allowing the system to prepare content in advance based on predicted execution paths, thereby improving both speed and reliability.
Solution Approach 2:
The system dynamically adapts the pre-fetching strategy based on actual execution behavior. By monitoring which chunks are accessed during runtime and updating the recipe file accordingly, the system adjusts its pre-fetching decisions to match real-world non-linear execution patterns rather than relying on static linear assumptions.
2Productivity
If streaming installation is designed into the application to handle non-linear execution, then installation performance is improved, but device complexity increases
Solution Approach 1:
The recipe file serves as an intermediary between the application and the streaming installation system. It contains pre-computed information about which chunks to fetch and when, allowing the application to be installed and executed without built-in streaming logic. The recipe file absorbs the complexity of non-linear execution handling, keeping the application itself simple.
Solution Approach 2:
The system uses runtime monitoring to automatically generate updated recipe files based on actual chunk access patterns. This self-service approach eliminates the need for manual recipe file creation and updates, reducing the complexity burden on developers while maintaining high installation performance.
3Reliability
If application chunks are copied to local location for installation, then installation completeness is ensured, but installation time increases
Solution Approach 1:
The application is divided into discrete chunks that can be fetched independently. The recipe file specifies which chunks are essential for initial execution and which can be fetched later. This segmentation allows the system to install and start the application with only the necessary chunks, ensuring completeness for startup while minimizing total installation time.
Solution Approach 2:
The system performs preliminary fetching of only the critical chunks needed for initial execution rather than copying the entire application. The recipe file identifies which chunks must be present before execution can begin, allowing the system to prepare only those specific chunks in advance, thereby reducing overall installation time while maintaining reliability.
Data Source
AI summary
High-performance streaming installation of software applications can be achieved by pre-fetching chunks of application files. Pre-fetching can be directed by a recipe file that can handle a wide variety of application behaviors. If a missing chunk is encountered during execution of the application, a cache miss record can be created and forwarded to a telemetry server. Cache miss records can be aggregated to generate a revised recipe file so that future installations of the application avoid the missing chunk scenario. Using the revised recipe file can cause fewer interruptions, result in less delay and otherwise improve performance.