Ad Hoc Collaboration State Management for Branching Storylines
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Solution Overview
Problem
Existing online collaboration environments face challenges in maintaining low latency, high availability, and scalability, especially in long-term network-based collaborations where participants interactively manage branching storylines, as they often require centralized state management and flexible participation.
Innovation Solution
A system where participating computing devices manage their local state during collaboration sessions, with central management of session updates, enabling ad hoc participation and voting on branching storylines, allowing users to determine the storyline's progression through a mobile app connected to a cloud-based infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized state management is used for long-term collaboration sessions, then session consistency and reliability are improved, but latency increases and scalability deteriorates
Solution Approach 1:
The system segments state management into two parts: local state is managed independently by each participant's device, while only collaborative state changes are centralized. This segmentation allows local operations to proceed without centralized coordination, reducing latency, while maintaining session consistency through centralized collaborative state management.
Solution Approach 2:
The collaboration server acts as an intermediary that manages only the collaborative state changes rather than all state. It mediates between participants by receiving collaborative state updates from one participant and distributing them to others, maintaining consistency without being a bottleneck for all operations.
2Reliability
If centralized state management is used for long-term collaboration sessions, then session consistency is improved, but system scalability worsens
Solution Approach 1:
By segmenting state management responsibilities, the system reduces the burden on the centralized server. Each participant's device handles its own local state independently, allowing the system to scale to more participants without proportionally increasing server complexity or resource requirements.
Solution Approach 2:
Each participant's device performs self-service by autonomously managing its local state without requiring centralized coordination for every operation. This self-service capability enables the system to scale more efficiently as each node is more independent and requires less centralized management overhead.
3Loss of time
If local state management is implemented at participant devices, then latency is reduced and scalability is improved, but session consistency and availability worsen
Solution Approach 1:
The system implements feedback mechanisms where local state changes are communicated to the collaboration server, which then distributes relevant changes to other participants. This feedback loop ensures that all participants eventually reach a consistent state while allowing local operations to proceed with low latency.
Solution Approach 2:
The collaboration server serves as an intermediary that receives local state changes from participants and distributes collaborative state updates to maintain consistency. It mediates between independent local state management and the need for session-wide consistency, reconciling the two approaches.
4Ease of operation
If ad hoc participation is allowed with flexible join/leave, then ease of operation is improved, but maintaining session state and consistency becomes more complex
Solution Approach 1:
Participant devices autonomously handle their own state management, including joining and leaving sessions, without requiring complex centralized coordination. Each device independently manages its local state and communicates only necessary collaborative changes to the server, simplifying the overall system architecture despite flexible participation.
Solution Approach 2:
The system extracts the complex state management responsibilities from the centralized server and places them at the edge devices. This extraction reduces the server's complexity while enabling flexible ad hoc participation, as each device independently handles its own state without requiring sophisticated centralized state management.
Data Source
AI summary
According to an exemplary embodiment, multiple users participate in a session to watch source media content (e.g., a movie or a video). Typically, an end user accesses the session via a mobile app executing on the user's mobile device, while the session itself is hosted in a server-based collaboration infrastructure. The source media content comprises at least one branching storyline. At a branch, a storyline in the source media content (typically a series of connected video clips) branches in at least two directions. According to the approach herein, and to facilitate the collaboration, upon reaching the branch, the participants in the session vote to determine the direction the story should then take going forward. Votes cast by the participants then determine which path the story advances. In so doing, the participants—working collaboratively—act as the producers or directors of the movie. In this manner, the system provides an entertaining and collaborative session that is highly interactive and enables the users themselves to determine how the story plays out.