Hybrid Star-Mesh Network for Synchronous Media Annotation
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Solution Overview
Problem
Existing network communication systems face challenges in synchronously sharing large media data files among multiple users, leading to bandwidth and processing resource constraints, especially in scenarios like presentations or conferences where real-time access is crucial.
Innovation Solution
The system establishes a primary star network with a server and failover mesh network, using an object data model to synchronize content across nodes. If a node detects a failure in the primary network, it can request data through the mesh network, ensuring continuous synchronous content sharing even under resource scarcity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a star network is used for synchronous data sharing, then data can be distributed from a central hub to multiple users, but the load on the hub increases proportionally with the number of users, eventually overwhelming network resources
Solution Approach 1:
The system segments the centralized star network into multiple distributed mesh network clusters. Each cluster handles a subset of users locally, reducing the load on any single hub. When clusters need to share data, they do so through peer-to-peer connections rather than routing all traffic through central hubs, thereby distributing the network load and preventing any single point from being overwhelmed.
Solution Approach 2:
The patent introduces gateway devices as intermediaries between mesh clusters and external networks. These gateways handle routing and data transfer between clusters, replacing the need for a centralized hub to manage all user connections. This intermediary layer distributes the processing load across multiple gateways rather than concentrating it in a single hub.
2Productivity
If mesh networks are used to distribute data among devices, then network resource load is reduced, but devices must frequently send pings to track available devices, creating data noise that increases exponentially with network size
Solution Approach 1:
The system merges the functionality of multiple small mesh clusters into a larger networked system of clusters. By combining local mesh networking with inter-cluster gateway connections, the system achieves both the resource efficiency of distributed mesh networks and the coordinated device tracking of structured network architectures, reducing the need for exponential ping traffic.
Solution Approach 2:
The patent adds a new dimension to network organization by creating a hierarchical structure where mesh clusters are organized into larger network clusters with gateways. This multi-level organization allows devices to track peers within their local cluster efficiently, while gateway devices manage inter-cluster routing, thereby reducing the overall complexity and ping traffic required to maintain the entire network.
3Speed
If large media data files are distributed to multiple users simultaneously, then real-time access is enabled, but bandwidth and processing resource demands become unachievable
Solution Approach 1:
The system creates multiple local copies of media data files distributed across different mesh network clusters rather than distributing them through a centralized hub. Each cluster maintains local copies of frequently accessed content, enabling users to access data from their local cluster's resources rather than requiring high-bandwidth transfers from a central source, thereby reducing overall network bandwidth consumption while maintaining real-time access speed.
Data Source
AI summary
Synchronous content sharing of media assets via an object data model propagated through a star network or a mesh network. Each user device updates a local object data model including information on the status of the media asset delivery, to achieve synchronization with the source data. Updates to the local object data model may be the result of direct connection between a user device and an application server via a network, or the result of indirect connections through peers in mesh networks, where the local object data model is shared through hops between peers in the mesh network if the direct connection is unavailable.