יום רביעי, 4.3.2020, 11:30
Applications such as distributed learning and edge computing strive to maximize the number of service requests (e.g., for data access) that can be concurrently executed by the system. Redundancy, in the form of simple replication and erasure coding, has emerged as an efficient and robust way to enable simultaneous access of different data objects by many users competing for the system’s resources. Here, replication and coding of data affect the rates at which users can be simultaneously served. In this talk, we will first introduce the notion of the service rate region of a redundancy scheme, and present some examples where this region is known. We will then explain the recently recognized connections with batch and switch codes and combinatorial optimization on graphs. We will discuss some systems issues as well.
Emina Soljanin is a professor of Electrical and Computer Engineering at Rutgers. Before moving to Rutgers in January 2016, she was a (Distinguished) Member of Technical Staff for 21 years in various incarnations of the Mathematical Sciences Research Center of Bell Labs. Her interests and expertise are wide, currently ranging from distributed computing to quantum information science. She is an IEEE Fellow, an outstanding alumnus of the Texas A&M School of Engineering, the 2011 Padovani Lecturer, a 2016/17 Distinguished Lecturer, and 2019 President for the IEEE Information Theory Society.