# EC-Kad: An Efficient Data Redundancy Scheme for Cloud Storage
## 2 Related Work  
In this era of information explosion, cloud storage has emerged as a powerful enabler for technological innovation. Beyond the initial web industry pioneers, an increasing number of enterprises, organizations and individuals are now turning to the cloud to store and manage their digital information. However, the growing diversity of user data and access patterns has introduced significant challenges for the management and maintenance of cloud storage systems. These challenges include balancing costs, ensuring reliability and availability and maintaining responsiveness. As cloud storage systems are designed to handle vast amounts of data, the relentless scale of growth makes it increasingly difficult to address these multifaceted issues effectively. Well-known cloud storage systems like GFS, HDFS, Ceph and EMC Atoms all use replication to provide data redundancy. For example, HDFS, a widely used cloud file system today, adopts triplication (three-way replication) by default, and EMC Atoms allows reserving more replicas with additional payment. Despite these advantages, replication does have some drawbacks. The huge amount of digital information (from exabytes to zettabytes) makes it undesirable to store several replicas for all of the data. Extra copies occupy a great deal of storage space (200% overhead for triplication), consume additional network bandwidth for replicating and updating the data and raise consistency issues that can affect the service performance of the whole system. As a cloud storage solution, the traditional storage method, magnetic tape storage, has been widely used in institutions and research centers around the world. A tape library cloud storage system simulator called TALICS3 was introduced in [14], aiming to provide system administrators and reliability engineers with a design tool for evaluating the performance and reliability of tape libraries in distributed cloud environments through discrete event simulation technology. The core of the research is to help design and optimize large-scale data storage systems by simulating the behavior of tape libraries. Against the backdrop of rapid development in cloud computing and big data, [PERSON] et al. [15] provided a detailed introduction to the technological progress of magnetic storage devices in improving recording density. It also comprehensively evaluates the current status and future of magnetic storage devices by combining market data and economic analysis. [PERSON] et al. [16] analyzed the impact of the geometric characteristics of the TBS mode, such as the azimuth and subframe length, on the position estimation resolution, system delay and tracking performance. Four TBS modes were designed to significantly improve the tracking accuracy of magnetic tape storage systems. While magnetic tape storage performs well in low-interference environments, in high-interference environments for practical applications, the data read and write speeds are relatively slow, making it suitable for storing cold data (infrequently accessed data). In addition, it requires complex management and incurs additional human resource costs, reducing its cost-effectiveness. This makes tape storage less suitable for the cloud era, where data mobility is crucial. [PERSON] et al. [17] investigated the performance of a distributed file system (DFS) based on RAID storage in a tapeless storage scenario. The core of the research was to evaluate the performance characteristics of two distributed file systems--CERN EOS and GlusterFS--under different layouts and workloads and explore their feasibility as alternatives to traditional tape storage. A hybrid framework with a three-tier structure was proposed in [18], including a system monitoring layer, a hybrid storage management layer and a physical resource layer. Experiments were conducted using different configurations of RAID-1-6 to evaluate their performance in terms of fault tolerance, fault range and capacity. [PERSON] et al.