# EC-Kad: An Efficient Data Redundancy Scheme for Cloud Storage
## 2 Related Work
[19] proposed a hybrid high-reliability RAID architecture called H2-RAID, which was aimed at improving the reliability of SSD RAID systems by combining solid-state drives (SSDs) and hard disk drives (HDDs). The core of the research is to address the inherent write durability issue of SSDs and enhance system reliability by introducing an HDD as a backup while minimizing performance loss. The use of RAID storage technology for the reconstruction and recovery of file data in storage systems can reduce the data reconstruction time and optimize system performance in the event of file system failure, thereby improving data integrity and reliability [20; 21; 22]. On small-scale datasets, RAID can, to some extent, ensure redundant storage of data and reduce storage overhead, but it requires dedicated hardware support, which increases the complexity of the hardware and configuration, and when facing large-scale heterogeneous resource storage and reconstruction, data redundancy will increase. Moreover, if multiple hard drives fail simultaneously, then some RAID configurations may not be able to recover data. A global optimization model has been proposed [23] which allows different subsystems to adopt different redundancy strategies to optimize the reliability of the entire system. [PERSON] et al. [24] proposed a high-security big data deduplication method based on dual encryption and an optimized SIMON cryptographic algorithm, aiming to improve the security and storage efficiency of big data in cloud computing environments. [PERSON] et al. [25] proposed a distributed data structure and algorithm for processing object metadata in backup systems with block-level duplicate data deletion. Subsequently, they were implemented as object storage layers for the HYDRAstor backup system. A new cross-client cloud backup solution called Duplicacy was proposed in [26] based on the lock-free duplicate data elimination method. The lock-free method uses content hashing as a file name to store blocks in network or cloud storage for duplicate data removal. Considering the advantages of coding redundancy, many scholars are committed to applying coding redundancy to data storage systems. In distributed storage systems, using network coding to encode and reconstruct data on storage nodes reduces storage redundancy to a certain extent but increases computational and traffic consumption [27; 28; 29]. This network encoding method is particularly suitable for file sharing in wireless networks, such as data transmission in multi-hop networks. Erasure codes have the advantages of high error tolerance, high storage efficiency, and low computational complexity. Academic workers are beginning to apply erasure code technology to cloud storage. [PERSON] et al. [30] proposed the Zebra framework, which dynamically encodes data into multiple levels based on data requirements, with each level using erasure codes of different parameters. [PERSON] et al. [31] proposed an adaptive and scalable caching scheme using erasure codes in distributed cloud edge storage systems, aiming to reduce data access latency by caching data blocks on edge servers. [PERSON] et al. [32] conducted benchmark testing on erasure code schemes in object systems, evaluating the time efficiency, I/O activity, and fault tolerance of erasure codes in cloud storage. [PERSON] et al. [33] proposed an optimized enhanced proactive recovery algorithm (EPRA) for improving data recovery efficiency in erasure-coded (EC) cloud storage systems. [PERSON] et al. [34] proposed an encoding construction based on the generalized matrix transposition method, which implements different security-level regeneration code schemes, and quantitatively analyzed the relationship between the security level and system performance parameters. [PERSON] et al. [35] proposed a novel network coding scheme, NEC-CRC, which combined KK code and LRMC code with CRC error detection code, effectively preventing error propagation.