Deterministic Distributed Network Coding for Multicast
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Solution Overview
Problem
Current solutions for the multicast connection problem in computer networks require centralized coordination and knowledge of network topology, leading to complex and delayed deterministic network codes with exponential scalability, which is impractical for distributed environments.
Innovation Solution
The implementation of deterministic linear coding in a distributed manner without requiring centralized coordination or knowledge of network topology, where coding coefficients are deterministically chosen based on local information and adjusted using feedback through bidirectional or reverse links, allowing for polynomial scalability and flexibility in network changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If deterministic network codes are used to solve the multicast connection problem, then information delivery reliability is improved, but system complexity and delay increase exponentially
Solution Approach 1:
The patent segments the network coding problem by allowing each node to independently determine its coding coefficients based only on local information (in-degree and out-degree), rather than requiring global network topology knowledge. This local segmentation of decision-making reduces the exponential complexity while maintaining deterministic information delivery.
Solution Approach 2:
Each network node autonomously determines its own coding coefficients using locally available information without requiring centralized coordination or global network knowledge. The nodes self-configure their behavior based on their local in-degree and out-degree, eliminating the need for complex centralized control systems.
2Reliability
If deterministic network codes with centralized coordination are used, then coding reliability is improved, but scalability deteriorates
Solution Approach 1:
The patent divides the centralized coordination function into distributed local decisions at each node. Each node independently selects coding coefficients based on its local characteristics (in-degree and out-degree), enabling the system to scale to large networks without requiring global coordination overhead.
Solution Approach 2:
The patent applies local quality by making coding coefficient selection dependent on local node properties (in-degree and out-degree) rather than global network state. This allows each node to adapt its coding behavior to its local position in the network while maintaining overall system reliability.
3Ease of operation
If random linear network coding is used in a distributed manner, then ease of operation is improved, but reliability deteriorates due to possible errors
Solution Approach 1:
Instead of using random coding coefficients that may produce errors, the patent inverts the approach by using deterministic coefficients that are carefully selected based on local node degrees. This inversion of the randomness-determinism tradeoff achieves both ease of distributed operation and high reliability through systematic coefficient selection.
Data Source
AI summary
A network and a communication method are described. The network comprises: source nodes, receiver nodes, and coding nodes. The coding nodes are connected with input links for communication of input signals to the coding nodes and output links for communication of output signals from the coding nodes. The output signals are a linear combination of the input signals. The coefficients of the linear combination are deterministically chosen based on local information available locally at the coding node.