Coding, Computing, and Communication in Distributed Storage Systems

Conventional studies in communication networks mostly focus on securely and reliably transmitting data from a source node (or multiple source nodes) to multiple destinations. A more general problem appears when the destination nodes are interested in obtaining functions of the data available in distributed source nodes. For obtaining a function, transmitting all the data to a destination node and then computing the function might be inefficient. In order to exploit the network resources efficiently, the general problem offers distributed computing in combination with coding and communication. This problem has applications in distributed systems, e.g., in wireless sensor networks, in distributed storage systems, and in distributed computing systems. Following this general problem formulation, we study the optimal and secure recovery of the lost data in storage nodes and in reconstructing a version of a file in distributed storage systems. The significance of this study is due to the fact that the new trends in communications including big data, Internet of things, low latency, and high reliability communications challenge the existing centralized data storage systems. Distributed storage systems can rectify those issues by distributing thousands of storage nodes (possibly around the globe), and then benefiting users by bringing data to their proximity. Yet, distributing the storage nodes brings new challenges. In these distributed systems, where storage nodes are connected through links and servers, communication plays a main role in their performance. In addition, a part of network may fail or due to communication failure or delay there might exist multi versions of a file. Moreover, an intruder can overhear the communications between storage nodes and obtain some information about the stored data. Therefore, there are challenges on reliability, security, availability, and consistency. To increase reliability, systems need to store redundant data in storage nodes and employ error control codes. To maintain the reliability in a dynamic environment where storage nodes can fail, the system should have an autonomous repair process. Namely, it should regenerate the failed nodes by the help of other storage nodes. The repair process demands bandwidth, energy, or in general transmission costs. We propose novel techniques to reduce the repair cost in distributed storage systems. First, we propose surviving nodes cooperation in repair, meaning that surviving nodes can combine their received data with their own stored data and then transmit toward the new node. In addition, we study the repair problem in multi-hop networks and consider the cost of transmitting data between storage nodes. While