SMS Center Message Compression for Bandwidth-Constrained Networks
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Solution Overview
Problem
The increasing volume of data communicated through mobile and other communication networks leads to bandwidth insufficiency, causing delays or preventing communication due to the high resource consumption.
Innovation Solution
A method and system for compressing short text data, such as SMS messages, by using dictionaries sorted by symbol probability, where each symbol is encoded based on its proximity in the text, reducing bandwidth usage between devices and network facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is transmitted through communication networks without compression, then communication can proceed without additional processing complexity, but bandwidth consumption increases causing delays and preventing communication
Solution Approach 1:
The patent changes the parameter of data representation by transforming text into compressed form using probability-based encoding. Each symbol is replaced with a code based on its probability of occurrence, fundamentally altering the data's physical state from uncompressed to compressed, thereby reducing bandwidth usage while managing processing complexity through algorithmic efficiency
Solution Approach 2:
The patent creates compressed copies of the original data that can be transmitted instead of the full-size data. The compression algorithm generates a compact representation that preserves the essential information while occupying less bandwidth, allowing the system to work with copies rather than the original data throughout the communication process
2Productivity
If compression algorithms process all symbols with uniform dictionaries, then the system is simpler to implement, but compression efficiency decreases for context-dependent symbols
Solution Approach 1:
The patent applies local quality by selecting different dictionaries based on the local context of each symbol being encoded. Instead of using a single uniform dictionary, the system chooses from multiple dictionaries depending on the position and surrounding symbols, making the compression adapt to local patterns and thereby improving overall compression efficiency
Solution Approach 2:
The patent introduces dynamics by making the dictionary selection adaptive and context-dependent. The system dynamically selects which dictionary to use for encoding each symbol based on the current context, allowing the compression algorithm to adapt to varying patterns in the data rather than applying a static, one-size-fits-all approach
Data Source
AI summary
The present disclosure is directed towards systems and methods for compressing messages, such as Short Message Service (SMS) or text messages between fixed or mobile devices through communications networks. The data of, for example, SMS messages is compressed and forwarded through a communication network to an appliance having a processing unit. The appliance decompresses the message and controls its delivery through network communication devices, where the decompressed SMS message is forwarded to its destination.