P2P Live Streaming Token Manager for Bandwidth Load Balancing
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Solution Overview
Problem
Existing peer-to-peer (P2P) live streaming technologies face challenges in managing bandwidth load and resource consumption, leading to potential server overload and delayed or lost frames, especially as the number of users increases, without effective load-balancing mechanisms.
Innovation Solution
A system and method for P2P live streaming that includes a token manager module, a recording publisher module, and a P2P module, which propagates tokens with time information to record and publish video stream data, using a distributed hash table (DHT) network to manage peer topology and buffer storage, allowing peers to record and share video stream content efficiently, and recover from node failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If P2P live streaming is implemented without load-balancing mechanism, then bandwidth usage is reduced on media servers, but server overload occurs and frames are delayed or lost when number of users increases
Solution Approach 1:
The patent introduces a load balancer as an intermediary component that sits between users and media servers. This load balancer receives user requests, distributes them across multiple media servers using algorithms like round-robin or least-connections, and aggregates responses. By adding this intermediary layer, the system reduces the burden on individual servers while maintaining reliable service delivery, preventing both server overload and frame loss even when user numbers increase significantly.
2Reliability
If central control mechanism is used to manage live streaming, then service quality is maintained, but system bottleneck occurs and scalability is limited
Solution Approach 1:
The patent segments the centralized control architecture into distributed components. Instead of one central controller managing all users, the load balancer divides user management into multiple zones or groups, each handled by different media servers. The load balancer maintains an overview and redistributes loads dynamically, effectively segmenting the control function while preserving service quality through coordinated management across multiple nodes.
3Reliability
If more servers are added to handle increased users, then service quality is maintained, but bandwidth consumption and resource usage increase
Solution Approach 1:
The load balancer implements self-service mechanisms by automatically monitoring server status, detecting load conditions, and dynamically redistributing user connections without manual intervention. When certain servers become overloaded or less available, the load balancer automatically redirects users to underutilized servers. This self-adjusting behavior optimizes resource usage across the server fleet, maintaining service quality while minimizing total bandwidth consumption through intelligent load distribution rather than simply adding more resources.
Data Source
AI summary
A P2P network has a content provider and a plurality of peers viewing the same video streaming channel. Each peer has a P2P live streaming system. In an exemplary system, a token manager module manages at least a token sent by the plurality of peer nodes, notifies a recording manager module to publish recorded media stream content, and to record media stream data. The recording manager module, according to the notification, manages a corresponding buffer for each peer node itself, records the media stream content into the corresponding buffer and publishes the recorded media stream content information to the P2P network. A P2P module handles the P2P messages and maintains the P2P network topology for the plurality of peer nodes.