Search · four archives
Search · four archives
13 papers · ranked by Valyu relevance
Matthias Volk, Borzoo Bonakdarpour, Joost-Pieter Katoen, Saba Aflaki
Randomization is a key concept in distributed computing to tackle impossibility results. This also holds for self-stabilization in anonymous networks where coin flips are often used to break symmetry. Although the use of randomization in self-stabilizing algorithms is rather common, it is unclear what the optimal coin…
Onur Günlü, Eirik Rosnes, Alexandre Graell i Amat, Hsuan-Yin Lin
The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include (1) privacy leakage to an eavesdropper is measured with…
Artur Czumaj, Peter Davies-Peck, Merav Parter
In this paper, we study the power and limitations of component-stable algorithms in the low-space model of massively parallel computation (MPC). Recently Ghaffari, Kuhn and Uitto (FOCS 2019) introduced the class of component-stable low-space MPC algorithms, which are, informally, those algorithms for which the outputs…
Bin Fan, Bin Tang, Zhihao Qu, Baoliu Ye + 1 more
In wireless distributed computing systems, worker nodes connect to a master node wirelessly and perform large-scale computational tasks that are parallelized across them. However, the common phenomenon of straggling (i.e., worker nodes often experience unpredictable slowdown during computation and communication) and…
Derya Malak, Mohammad Reza Deylam Salehi, Berksan Serbetci, Petros Elia + 2 more
'Petros Elia' 'Chintha Tellambura' 'Jun Chen'] The work here studies the communication cost for a multi-server multi-task distributed computation framework, as well as for a broad class of functions and data statistics. Considering the framework where a user seeks the computation of multiple complex (conceivably…
Dennis Komm, Rastislav Královič, Richard Královič, Tobias Mömke
We study the relationship between the competitive ratio and the tail distribution of randomized online problems. To this end, we identify a broad class of online problems for which the existence of a randomized online algorithm with constant expected competitive ratio r implies the existence of a randomized online…
Amit Shahar, Yuval Alfassi, Daniel Keren, Hector Zenil
The empirical entropy is a key statistical measure of data frequency vectors, enabling one to estimate how diverse the data are. From the computational point of view, it is important to quickly compute, approximate, or bound the entropy. In a distributed system, the representative (“global”) frequency vector is the…
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh, Deniz Gündüz + 2 more
'Songze Li' 'Linqi Song'] We consider the distributed stochastic gradient descent problem, where a main node distributes gradient calculations among n workers. By assigning tasks to all workers and waiting only for the k fastest ones, the main node can trade off the algorithm’s error with its runtime by gradually…
Michal Dory, Mohsen Ghaffari, Saeed Ilchi
We describe a simple deterministic $O \varepsilon ^{-1}\log \Delta $ round distributed algorithm for $2\alpha +11 + \varepsilon $ approximation of minimum weighted dominating set on graphs with arboricity at most $\alpha$. Here $\Delta$ denotes the maximum degree. We also show a lower bound proving that this round…
Alvaro Estebanez, Diego R. Llanos, David Orden, Belen Palop + 1 more
'Rafael Sachetto Oliveira'] Loops are a rich source of parallelism. Unfortunately, many loops cannot be safely parallelized at compile time because the compiler is not able to guarantee that there will be no dependence violations. Thread-Level Speculation (TLS) techniques, either hardware or software-based, allow the…
Yongcheng Yang, Yifei Huang, Xiaohuan Qin, Shenglian Lu + 3 more
'Yanlin Geng' 'Youlong Wu' 'Ling Liu'] Coded distributed computing (CDC) is a powerful approach to reduce the communication overhead in distributed computing frameworks by utilizing coding techniques. In this paper, we focus on the CDC problem in $(H,L)$-combination networks, where H APs act as intermediate pivots and…
Dušan Jakovetić, Nataša Krejić, Greta Malaspina
We consider two formulations for distributed optimization wherein N nodes in a generic connected network solve a problem of common interest: distributed personalized optimization and consensus optimization. A new method termed DINAS (Distributed Inexact Newton method with Adaptive step size) is proposed. DINAS employs…
Franziska Eberle, Anupam Gupta, Nicole Megow, Benjamin Moseley + 1 more
'Rudy Zhou'] The configuration balancing problem with stochastic requests generalizes well-studied resource allocation problems such as load balancing and virtual circuit routing. There are given m resources and n requests; each request has multiple possible configurations, each of which increases the load of each…