Error-Correcting Coding Strategies for Data Storage and Networks

• Applicant: Professorin Dr.-Ing. Antonia Wachter-Zeh
• Subject Area: Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
• Term: from 2016 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 317311578

Data storage and data transmission has become an essential part of our modern every-day life. However, storage media and transmission systems are highly susceptible to errors which often hinder the data recovery process and sometimes even make it impossible. The goal of this project is to make data storage and data transmission more reliable and efficient by means of algebraic coding theory. In particular, we consider three modern applications of error-correcting codes: network coding, coding for memories, and coding for distributed data storage. In networks like the internet, errors occur, e.g., due to interference with other users, or packets are lost due to congestion.Data storage media like flash memories (used in USB flash drives or solid state drives) suffer from manufacturing imperfections, wearout, and fluctuating read/write errors. In distributed data storage (necessary, e.g., for cloud storage systems), the most common problem are failures of servers and the task is to reconstruct the lost data efficiently.In the area of network coding, we want to construct new codes for the assignment of the coefficients of the linear combinations at the nodes of the network as well as for error-correction. This includes in particular the reduction of the necessary field size and new decoding strategies with quasi-linear time complexity.The second part of the project considers coding for non-volatile memories (e.g., flash memories). Here, we will consider the problem of (partially) stuck memory cells. A cell is (partially) stuck if it cannot change its value or only take certain values. The goal is to store as much information as possible in memories that contain defect cells under the assumption that the decoder does not know the positions of the stuck cells. Further, we will consider coding for new storage technologies such as 3-D flash memories.The third work package deals with coding for distributed data storage systems. In particular, we will work on the class of locally repairable codes (LRCs). These codes are designed to minimize the number of servers from which data has to be downloaded when recovering a failed server. The construction of new codes and the efficient decoding of LRCs will be an important objective of this project.

• DFG Programme: Independent Junior Research Groups