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Erasure Coding

What is Erasure Coding?

Erasure coding is a sophisticated data protection and recovery technique used in computer storage systems to safeguard data against loss or corruption. It works by breaking data into fragments, expanding these fragments with redundant data pieces, and storing them across different locations or storage media. This method allows for the reconstruction of data from a subset of the available fragments, ensuring data integrity and availability even in the event of multiple failures.

Origin of Erasure Coding

The concept of erasure coding originated from the realm of information theory and coding, primarily developed to address the challenges of reliable communication over unreliable channels. It was introduced by Claude Shannon in the mid-20th century, laying the groundwork for modern error-correcting codes. Over time, the application of erasure coding evolved beyond communication systems to include storage systems, where it became a critical tool for data reliability and efficiency.

Practical Application of Erasure Coding

A quintessential example of erasure coding in action is its deployment in distributed storage systems, such as cloud storage. In these environments, data is stored across multiple servers or locations. By applying erasure coding, the system can tolerate multiple server failures without losing any data. This is particularly beneficial for large-scale systems where traditional replication methods (storing multiple copies of data) would be prohibitively expensive in terms of storage space.

Benefits of Erasure Coding

Erasure coding offers several advantages over traditional data protection methods like mirroring or replication. Firstly, it significantly improves storage efficiency by reducing the amount of extra storage needed for redundancy. Secondly, it enhances data reliability and availability, as it allows for data recovery even with multiple component failures. Lastly, erasure coding is adaptable to varying levels of protection, enabling systems to balance between storage overhead and fault tolerance based on specific requirements.


While both erasure coding and RAID (Redundant Array of Independent Disks) provide data redundancy, erasure coding is more flexible and efficient, particularly in distributed systems. RAID is limited by the number of disk failures it can handle (typically one or two), whereas erasure coding can be designed to tolerate multiple failures with less redundancy overhead.

Erasure coding is highly effective for static or infrequently modified data, as the process of encoding and decoding can be resource-intensive. It's ideal for archival storage, cloud storage, and large-scale data applications. However, for highly transactional data or systems requiring low-latency access, other methods might be more appropriate.

Implementing erasure coding can introduce computational overhead, as data needs to be encoded before storage and decoded upon retrieval. However, with advancements in computing power and optimized algorithms, the performance impact has been significantly mitigated, making it a viable option for many storage systems.


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