Many distributed optimization algorithms achieve existentially-optimal running times,
meaning that there exists some pathological worst-case topology on which no algorithm can …

More and more networks are becoming reconfigurable: not just the routing can be
programmed, but the physical layer itself as well. Various technologies enable this …

In this work, we study the complexity of fundamental distributed graph problems in the
recently popular setting where information about the input graph is available to the nodes …

In prior work, Gupta et al.(SPAA 2022) presented a distributed algorithm for multiplying
sparse $ n\times n $ matrices, using $ n $ computers. They assumed that the input matrices …

We provide CONGEST model algorithms for approximating minimum weighted vertex cover
and the maximum weighted matching. For bipartite graphs, we show that a $(1+\varepsilon) …

The sinkless orientation problem plays a key role in understanding the foundations of
distributed computing. The problem can be used to separate two fundamental models of …

We study matrix multiplication in the low-bandwidth model: There are n computers, and we
need to compute the product of two n× n matrices. Initially computer i knows row i of each …

Consider a distributed task where the communication network is fixed but the local inputs
given to the nodes of the distributed system may change over time. In this work, we explore …

While SDNs enable more flexible and adaptive network operations,(logically) centralized
reconfigurations introduce overheads and delays, which can limit network reactivity. This …

In distributed microservice architecture, low latency and high reliability are crucial as they
directly impact user experience by ensuring robust service continuity across the network …