Distributed Data Stream Combining for Scalable Communication
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Solution Overview
Problem
Conventional network-based communication systems face limitations in scalability, quality, mobility, and reliability due to processing constraints at datacenters, leading to issues such as restricted user participation, data packet loss, and susceptibility to errors and failures during conference calls.
Innovation Solution
Network devices are enabled to locally combine and manage data streams from other participants in a communication session without relying on a datacenter, allowing for increased scalability, mobility, and reliability by establishing and maintaining multi-device communication sessions independently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a datacenter processes and combines all data streams centrally, then conference call facilitation is achieved, but the number of participating users is limited due to processing constraints
Solution Approach 1:
The patent divides the centralized datacenter processing function into distributed network device processing. Each network device independently combines data streams from other devices, eliminating the single datacenter processing bottleneck and enabling unlimited user participation.
Solution Approach 2:
The patent transitions from a two-dimensional centralized processing model (all streams through one datacenter) to a multi-dimensional distributed processing model where multiple network devices perform combining functions simultaneously, increasing system capacity.
2Quantity of substance
If a datacenter processes multiple data streams, then conference calls are enabled, but data packet loss occurs as user count increases
Solution Approach 1:
By segmenting the processing load across multiple network devices rather than concentrating it in one datacenter, each device handles fewer streams with lower risk of packet loss, improving overall system reliability.
Solution Approach 2:
Network devices act as intermediaries that locally combine data streams before distribution, reducing the processing burden and packet loss risk on any single device while maintaining data integrity.
3Ease of operation
If data streams are sent to a datacenter and back to users, then conference calls are facilitated, but network latency and errors increase
Solution Approach 1:
The patent extracts the data stream combining function from the centralized datacenter and places it at the network device level, eliminating unnecessary data travel to and from the datacenter and reducing latency.
Solution Approach 2:
Network devices perform data stream combining locally without requiring centralized datacenter processing, enabling self-service operation that reduces network traversal and latency.
4Ease of operation
If a centralized datacenter hosts conference calls, then communication sessions are established, but system reliability decreases due to single point of failure
Solution Approach 1:
The patent segments the session hosting function across multiple network devices rather than relying on a single datacenter, eliminating the single point of failure and improving connection stability.
Solution Approach 2:
The system changes the operational parameter from centralized hosting to distributed hosting, where each network device can independently maintain session state, providing redundancy and fault tolerance.
Data Source
AI summary
The present application details methods and systems for facilitating within a network-based communication system, a communication session between a group of network devices. For example, the network device receives incoming data streams from other network devices in the communication session. The network device also sends an outgoing data stream to the other network devices in the communication session. Further, the network device combines the incoming data stream with the outgoing data stream and presents the combined data stream to a user.