You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Distributed storage systems (DSSs) have gained a lot of interest recently, thanks to their robustness and scalability compared to single-device storage. Majority of the related research has exclusively concerned the network layer. At the same time, the number of users of, e.g., peer-to-peer (p2p) and device-to-device (d2d) networks as well as proximity based services is growing rapidly, and the mobility of users is considered more and more important. This motivates, in contrast to the existing literature, the study of the physical layer functionality of wireless distributed storage systems. In this paper, we take the first step towards protecting the storage repair transmissions from physical layer errors when the transmission takes place over a fading channel. To this end, we introduce the notion of a space-time storage code, drawing together the aspects of network layer and physical layer functionality and resulting in cross-layer robustness. It is also pointed out that existing space-time codes are too complex to be utilized in storage networks when the number of helpers involved is larger than the number of receive antennas at the newcomer or data collector, hence creating a call for less complex transmission protocols.

Cited Abstract(s):
[1]: Regenerating codes are a class of codes proposed for providing reliability of data and efficient repair of failed nodes in distributed storage systems. In this paper, we address the fundamental problem of handling errors and erasures at the nodes or links, during the data-reconstruction and node-repair operations. We provide explicit regenerating codes that are resilient to errors and erasures, and show that these codes are optimal with respect to storage and bandwidth requirements. As a special case, we also establish the capacity of a class of distributed storage systems in the presence of malicious adversaries. While our code constructions are based on previously constructed Product-Matrix codes, we also provide necessary and sufficient conditions for introducing resilience in any regenerating code.

[2]: We consider a distributed storage system employing some existing regenerate codes where the storage nodes are scattered in a wireless network. The data collector connects to the storage nodes via orthogonal channels and downloads data symbols from these nodes. In the existing data reconstruction schemes for distributed storage systems, the data collector downloads all symbols from a subset of the storage nodes. Such a full-downloading approach becomes inefficient in wireless networks since due to fading, the wireless channels may not offer sufficient bandwidths for full downloading. Moreover, full-downloading is also less power efficient than partial downloading. In this paper, given a coding scheme employed by the wireless distributed storage system, we propose a partial downloading scheme that allows downloading a portion of the symbols from any storage node. We formulate a cross-layer wireless resource allocation problem for data reconstruction in distributed storage systems employing such partial downloading. To derive the fundamental properties of partial downloading as well as to reduce the complexity of wireless resource allocation, we derive necessary and sufficient conditions for data reconstructability for partial downloading, in terms of the numbers of downloaded symbols from the storage nodes. We also propose channel and power allocation schemes for partial downloading in wireless distributed storage systems. Simulation results are provided to demonstrate the significant power savings by the proposed partial downloading scheme compared to the full-downloading methods for distributed storage.

[3]:
Most storage-related research focuses on the (logical) network layer, while the physical layer functionality is usually ignored due to the fact that many storage systems in big data centers are wired. Nonetheless, the authors are aware of some interesting works considering the physical layer. In [2] , a so-called partial downloading scheme is proposed that allows for data reconstruction with limited bandwidth by downloading only parts of the contents of the helper nodes. In [3] , the use of a forward error correction code (, LDPC code) is proposed in order to correct bit errors caused by fading. In [1] , optimal storage codes are constructed for the error and erasure scenario. The present paper deviates from the previous work in that it addresses the actual of the transmitted repair data in order to fight the effects caused by fading.