Distributed Big Data Query Architecture With IPv6 Header Encoding
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Solution Overview
Problem
Existing methods for representing and processing big data sets are labor-intensive, prone to errors, and do not fully exploit the potential of IPv6 for efficient and reliable addressing and configuration of machines, especially in real-time applications like autonomous driving and precise manufacturing control.
Innovation Solution
A method using a glossary of words with assigned technical moods, counting word occurrences in empirical data sources, and encoding this information in IPv6 datagrams' headers for automated and hardware-efficient representation of big data, allowing real-time processing and configuration of machine devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual instruction creation and transmission is used, then flexibility in data representation is achieved, but labor intensity increases and errors are introduced
Solution Approach 1:
The system automatically generates IPv6 datagrams by extracting word occurrence data from empirical data sources and encoding it directly into the datagram header, eliminating the need for manual instruction creation while maintaining flexible data representation capabilities
Solution Approach 2:
The patent replaces manual mechanical processes of instruction creation with automated computer-based extraction and encoding mechanisms that process empirical data sources and generate configuration instructions programmatically
2Productivity
If big data sets are represented using traditional methods, then comprehensive data representation is achieved, but hardware efficiency decreases and real-time processing becomes difficult
Solution Approach 1:
The patent segments big data representation into discrete word occurrence counts that are encoded individually in IPv6 datagram headers, allowing efficient processing of large datasets through standardized, modular data units that can be handled by conventional hardware
Solution Approach 2:
The system changes the representation parameters by encoding word occurrence frequencies directly as numerical values in the IPv6 datagram header structure, transforming complex data representations into efficient numerical parameters that enable real-time processing on standard hardware
3Quantity of substance
If IPv6 extension headers are used to carry information, then data transmission capacity increases, but unintended information may be carried and security is compromised
Solution Approach 1:
The patent extracts and utilizes only the necessary portion of IPv6 extension headers (specifically the flow information field) for carrying controlled data, separating useful information from potentially harmful unintended data that could be carried in other header sections
Solution Approach 2:
The system introduces a controlled intermediary mechanism through standardized word occurrence encoding that mediates between data transmission capacity requirements and security requirements, ensuring that only intended information is carried through the IPv6 header structure
Data Source
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AI summary
The present invention is directed towards a method and an apparatus for automated and hardware efficient addressing of machines with automated analysis of instructions, which are transmitted to the machine in IPv6 datagrams. The present invention provides the advantage that even big data sets can be represented in an efficient way such that the complexity is broken down and a variety of parameters are compressed such that a comprehensive representation of huge data amounts is possible. With an increasing availability of data algorithms computer systems typically lack the ability to process and represent huge data sets in real time. In response to this the present inventions suggests and efficient and yet appropriate way for coding and transmitting the large data sets on limited hardware devices. The invention is furthermore directed towards a respectively arranged system along with a computer program product and a computer-readable medium.