Federated learning enables training a global model from data located at the client nodes,
without data sharing and moving client data to a centralized server. Performance of …

Coded distributed computing (CDC) can alleviate the communication load in distributed
computing systems by leveraging coding opportunities via redundant computation. While the …

In caching system, it is desirable to design a coded caching scheme with the transmission
load and subpacketization as small as possible, in order to improve efficiency of …

Distributed computing has become one of the most important frameworks in dealing with
large computation tasks. In this paper, we propose a systematic construction of coded …

Large gains in the rate of cache-aided broadcast communication are obtained using coded
caching, but to obtain this most existing centralized coded caching schemes require that the …

Coded distributed computing (CDC) is an efficient method to reduce the communication load
in general distributed computing frameworks such as MapReduce. In these systems, one …

Consider a multi-cell mobile edge computing network, in which each user wishes to
compute the product of a user-generated data matrix with a network-stored matrix. This is …

Considering the increasing demand for large-scale MapReduce distributed computing,
coded distributed computing (CDC) has become a promising technology to reduce the …

Coded distributed computing (CDC), originally proposed by Li et al., leverages coded
multicast messages to exchange computed intermediate values among the distributed …

Li et al. introduced coded distributed computing (CDC) scheme to reduce the
communication load in general distributed computing frameworks such as MapReduce …