Synchronized Event Data Structures for Live-Event Networks
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Solution Overview
Problem
Challenges exist in providing synchronized information efficiently across computing systems with different types of devices, particularly in sharing up-to-date information about live events involving multiple computing devices.
Innovation Solution
The establishment of synchronized groups that allow multiple computing devices to interact and receive notifications related to live events, with mechanisms for generating and updating data records and packages based on event conditions, and managing interactions within these groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If synchronized groups are established to share live event data across multiple computing devices, then information synchronization and real-time updates are improved, but system complexity and data management overhead increase
Solution Approach 1:
The system segments live event data into structured data records with specific parameters (event type, timestamp, participant information, etc.). Each computing device maintains local data structures that are updated incrementally based on synchronized events, rather than managing complete duplicate copies of all event data. This segmentation reduces the complexity of data management while maintaining synchronization reliability.
Solution Approach 2:
The patent introduces synchronized groups as intermediary structures that mediate data sharing between multiple computing devices. These groups act as logical containers that manage data records and control which devices receive which event notifications. The intermediary layer abstracts the complexity of peer-to-peer synchronization, providing a managed approach to maintaining data consistency across devices.
2Loss of information
If data records are generated and updated for every live event condition, then information completeness and accuracy are improved, but data processing time and computational resources increase
Solution Approach 1:
The system applies local quality by generating and updating data records selectively based on specific event conditions and device contexts. Not all computing devices receive or process all event data - instead, data records are tailored to the specific needs and roles of each device within the synchronized group. This reduces unnecessary data processing while maintaining information completeness for relevant participants.
Solution Approach 2:
The patent implements partial action by generating data records only for significant event conditions rather than continuously updating all possible parameters. Data records are created selectively when events occur that meet specific criteria, avoiding the overhead of continuous full-state synchronization. This approach maintains information accuracy for critical events while reducing processing time for less significant updates.
3Ease of operation
If multiple computing devices interact simultaneously in synchronized groups, then collaboration and real-time interaction are improved, but network traffic and communication overhead increase
Solution Approach 1:
The system uses periodic action by updating data records and pushing notifications at specific event triggers rather than maintaining continuous real-time streams. When live events occur, structured data records are generated and distributed to synchronized group members. This event-driven periodic update model reduces network traffic compared to continuous synchronization while maintaining the ability to provide real-time interaction when events occur.
Solution Approach 2:
The patent implements discarding and recovering by managing data record lifecycles within synchronized groups. Data records are created, distributed to relevant devices, and then archived or discarded based on retention policies. Less critical event data is discarded after serving its immediate notification purpose, while important data is retained for reference. This approach reduces ongoing network traffic by eliminating redundant data transmissions while preserving essential information.
Data Source
AI summary
Systems and methods for synchronizing event data structures in computer networks are disclosed. A system can receive, via a network from a first computing device corresponding to a first profile, a first network communication to generate a synchronized group identifying a second profile of a second computing device. The system can generate the synchronized group, and in response to receiving a second network communication from the second computing device, generate a data record including data record parameters specified in the second network communication. A data package to present a content item corresponding to the data record is generated in response to determining that the second profile is identified in the synchronized group, and a feed of the synchronized group is provided in response to corresponding network communications.