Video Streaming Release Scheduling for Peak Load Control
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Solution Overview
Problem
Existing video streaming systems face challenges in managing network bandwidth and server resources due to simultaneous user streaming, and viewers struggle to control the pace and timing of their content consumption, leading to a lack of desirable content and inefficient resource utilization.
Innovation Solution
A system that allows users to customize the pacing and timing of video streaming by specifying release intervals and schedules for episodes, using artificial intelligence to recommend optimal release times based on user preferences and calendar events, thereby reducing peak loading and enhancing viewer experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple users stream video content simultaneously, then content availability for users is improved, but network bandwidth and server resources are excessively consumed
Solution Approach 1:
The patent implements periodic release intervals where content is made available to users at scheduled times rather than continuously or simultaneously. This distributes the streaming load over time, reducing peak network bandwidth consumption while ensuring content remains available when users need it.
Solution Approach 2:
The system allows users to select and schedule content for future release times. Users make their viewing preferences known in advance, and the system pre-schedules content delivery accordingly. This preliminary planning enables the system to allocate network resources more efficiently by knowing when content will be needed.
2Ease of operation
If users can access all content immediately, then viewer satisfaction is improved, but peak loading on streaming infrastructure increases
Solution Approach 1:
The system provides dynamic content release scheduling where users can customize their viewing pace and timing preferences. The release schedule adapts to user preferences and can be adjusted in real-time, allowing users to access content at optimal times without overwhelming server infrastructure with simultaneous requests.
Solution Approach 2:
The system incorporates user feedback mechanisms where users can indicate their viewing preferences and pace requirements. This feedback is used to personalize the content release schedule for each user, ensuring they receive content at times that satisfy their viewing needs while distributing the load across the user base to reduce peak server resource demands.
3Productivity
If content is released at fixed intervals, then network resource utilization is improved, but user control over viewing pace is reduced
Solution Approach 1:
The system provides a universal scheduling framework that can accommodate multiple user preferences and viewing patterns. Users can select from various release interval options (e.g., daily, weekly, custom intervals) and the system adapts the fixed interval structure to match individual user needs, maintaining both efficient resource utilization and user control flexibility.
Data Source
AI summary
Systems and methods are disclosed configured to enable dynamic control of content streaming and/or to control content streaming so as to reduce peak system loads. A user electronic timetable is accessed from memory and is amazed to identify future unscheduled time periods. A first learning engine classifies timetable entries into subject types. A watchlist comprising a plurality of content items of respective time lengths is accessed. A second learning engine utilizes the classification and the time lengths to generate a scheduling recommendation of at least one item of content on the user watchlist. The scheduling recommendation is transmitted over a network to the user device. If the recommendation is accessed, a timetable entry is generated corresponding to the scheduling recommendation The at least one item of content on the user watchlist is streamed to the first device of the user in accordance with the accepted scheduling recommendation.