Run-length encoding (RLE) is a compression algorithm used on data with several repeated sequences. For organizations with many large files (e.g., templates with repeated content), RLE can be used to reduce the amount of storage space for each file. The result is energy cost savings for storage infrastructure with more space for additional corporate documents.
What Is RLE Compression?
Compression algorithms are nothing new. Created in 1983, RLE is one of the oldest compression algorithms. At the time, storage devices were much more expensive than they are today. RLE compression takes repeating data and stores it as a single value. The single value can be used to recreate the image when it’s retrieved.
By using a single value for repeating characters, RLE reduces the amount of storage space for a single file. The elements used in storage take up less space, so users have more storage for images and documents. Administrators can run RLE on large storage devices, including network attached storage (NAS).
How RLE Compression Works
RLE works best for data with several repeated values. To illustrate the way RLE compression works, suppose that you have data with 10 values of 200. Without compression, the system must store the value 200 10 times. Using RLE compression, the system stores the number 10 alongside the value 200. This indicates that the user has a file with the value 200 10 times, so the file can be rebuilt when retrieved.
This example is simplistic, but most images and documents have the same repeated values thousands of times. Administrators can reduce the storage space necessary to save these documents while preserving data integrity. RLE compression can save several gigabytes in data storage across a NAS, but it’s only useful if the organization has documents with repeated data. Otherwise, it can actually increase storage requirements.
Advantages of RLE Compression
Compression algorithms reduce the amount of storage necessary for large files. For data centers, RLE compression can save a considerable amount in storage costs. Local administrators for on-premises storage silos like network attached storage (NAS) or a storage area network (SAN) can also save thousands of dollars in storage costs and get energy savings.
Another benefit of RLE compression is that it reduces transfer speeds and bandwidth usage. When data is compressed, it can transfer over the internet using less bandwidth. Users retrieve their data faster, and corporations hosting data save on bandwidth costs. RLE compression is also a lightweight strategy, so it does not take much CPU usage when data is compressed or decompressed.
Limitations of RLE Compression
RLE compression is best for data with repetitive values. If your data does not have repetitive bytes, RLE compression can actually slow down applications. Repetitive data is stored with indicators to point to repetitive data. If you don’t have repetition, then you add more bytes to file storage, which in turn increases file sizes.
Simple data and images are common use cases for RLE compression. For more advanced data like video transfers, RLE compression is not efficient. Video compression algorithms are more effective in transferring data over the internet since videos often have fewer repetitive sequences.
Applications of RLE Compression
Most RLE compression strategies work with basic data. Although large images use other compression techniques, simple images with few colors might benefit from RLE compression when transferred over a network. For example, black and white images can work well with RLE compression.
RLE compression can be used on basic documents with repeated characters. For example, if you have a template with repeated text, RLE compression might be the best option for you. Binary data or files with repetitive text can use RLE compression to minimize data storage.
Conclusion
If you have files with repetitive information, RLE is an older compression technique requiring little CPU overhead. RLE compression can speed up file transfers on your corporate network and the internet. If you’re looking for a way to transfer files more quickly and they have repetitive data, you can look into RLE compression as an option.
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