Multimedia Stream Processing via Centralized Edge Scheduling
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Solution Overview
Problem
Current Peer-to-Peer (P2P)/Content Delivery Network (PCDN) systems require users to install multiple Software Development Kits (SDKs) for processing multimedia data streams, leading to increased resource configuration burdens and inefficient utilization of edge resource nodes, as each SDK can only access relevant edge resource nodes independently, resulting in resource waste and limited communication between cloud services.
Innovation Solution
A multimedia data stream processing method that segments multimedia data into sub-streams and uses a centralized scheduling device to allocate and schedule these sub-streams across edge resource nodes, allowing terminal devices to communicate with different cloud services via a universal communication protocol without integrating SDKs, thereby fully utilizing edge resources and enabling seamless communication between various cloud services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple SDKs are installed for processing multimedia data streams in P2P/PCDN systems, then the processing capability is improved, but the resource configuration burden on terminal devices increases
Solution Approach 1:
The patent introduces a server as an intermediary between terminal devices and edge resource nodes. The server handles the complexity of SDK integration and private protocol processing, while terminal devices only need to use a universal communication protocol. This mediator approach resolves the contradiction by centralizing the complex processing functions on the server side, thereby improving multimedia data stream processing capability without increasing the resource configuration burden on terminal devices.
2Reliability
If each SDK accesses relevant edge resource nodes independently, then the processing specificity is improved, but the utilization efficiency of edge resource nodes deteriorates
Solution Approach 1:
The patent merges the independent access paths of multiple SDKs into a unified server-mediated access mechanism. The server consolidates requests from terminal devices and intelligently distributes them to appropriate edge resource nodes. This merging approach maintains the specificity of processing by ensuring each request reaches the appropriate node, while simultaneously improving utilization efficiency by enabling centralized resource allocation and avoiding redundant or conflicting access patterns.
Solution Approach 2:
The patent changes the access parameter from direct SDK-to-node connections to server-mediated connections. By altering the communication architecture from decentralized direct access to centralized indirect access, the system achieves both specific processing (through server routing logic) and high utilization efficiency (through centralized resource management and load balancing).
3Measurement precision
If multiple private protocols are used for communication, then the communication precision is improved, but the adaptability between different cloud services deteriorates
Solution Approach 1:
The server acts as a protocol translation intermediary, receiving requests through a universal communication protocol from terminal devices and translating them into the appropriate private protocols for communication with edge resource nodes. This intermediary mechanism preserves communication precision by maintaining protocol-specific details where needed, while simultaneously enabling adaptability by allowing diverse services to communicate through a common interface.
Solution Approach 2:
The patent implements a universal communication protocol at the terminal device level that can work with multiple different cloud services and private protocols. The server provides multi-functional protocol conversion capabilities, enabling a single universal interface to support multiple specific protocols. This universality resolves the contradiction by allowing precise protocol-specific communication when needed while maintaining broad adaptability across different services.
Data Source
AI summary
Provided is a multimedia data stream processing method, an electronic device and a storage medium, relating to the field of artificial intelligence, and specifically, to the technical fields of cloud computing, media cloud technology, and the like, which may be applied to scenes such as smart cloud. The multimedia data stream processing method includes: allocating a plurality of sub-streams of a multimedia data stream to a plurality of edge resource nodes, where the multimedia data stream is segmented into a plurality of slices and each of the plurality of sub-streams includes a part of the plurality of slices of the multimedia data stream; and scheduling the plurality of edge resource nodes to provide the plurality of sub-streams of the multimedia data stream for a terminal device.