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We address the design of distributed systems with synchronous dataflow programming languages. As modular design entails handling both architectural and functional modularity, our first contribution is to extend an existing synchronous…

Programming Languages · Computer Science 2012-11-13 Gwenaël Delaval , Alain Girault , Marc Pouzet

Reuse of data in new contexts beyond the purposes for which it was originally collected has contributed to technological innovation and reducing the consent burden on data subjects. One of the legal mechanisms that makes such reuse possible…

Computers and Society · Computer Science 2023-09-06 Asia J. Biega

Database replication is an important component of reliable, disaster tolerant and highly available distributed systems. However, data replication also causes communication and processing overhead. Quantification of these overheads is…

Databases · Computer Science 2020-08-13 Muhammad Karam Shehzad , Jam Muhammad Yousif , Muhammad Saqib Ilyas , Adnan Iqbal

Distributed Hash Tables offer a resilient lookup service for unstable distributed environments. Resilient data storage, however, requires additional data replication and maintenance algorithms. These algorithms can have an impact on both…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Matthew Leslie

Data from different sources rarely conform to a single formatting even if they describe the same set of entities, and this raises concerns when data from multiple sources must be joined or cross-referenced. Such a formatting mismatch is…

Databases · Computer Science 2022-03-08 Arash Dargahi Nobari , Davood Rafiei

Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling…

Artificial Intelligence · Computer Science 2024-01-02 Maja Rudolph , Stefan Kurz , Barbara Rakitsch

Concurrent pattern calculus (CPC) drives interaction between processes by comparing data structures, just as sequential pattern calculus drives computation. By generalising from pattern matching to pattern unification, interaction becomes…

Logic in Computer Science · Computer Science 2015-07-01 Thomas Given-Wilson , Daniele Gorla , Barry Jay

Coding theoretic approached have been developed to significantly reduce the communication load in modern distributed computing system. In particular, coded distributed computing (CDC) introduced by Li et al. can efficiently trade…

Information Theory · Computer Science 2020-08-04 Nicholas Woolsey , Rong-Rong Chen , Mingyue Ji

Modern RDBMSs support the ability to compress data using methods such as null suppression and dictionary encoding. Data compression offers the promise of significantly reducing storage requirements and improving I/O performance for decision…

Databases · Computer Science 2011-09-06 Hideaki Kimura , Vivek Narasayya , Manoj Syamala

We study a proof methodology for verifying the safety of data invariants of highly-available distributed applications that replicate state. The proof is (1) modular: one can reason about each individual operation separately, and (2)…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-08 Sreeja Nair , Gustavo Petri , Marc Shapiro

Homomorphic encryption is a form of encryption which allows computation to be carried out on the encrypted data without the need for decryption. The success of quantum approaches to related tasks in a delegated computation setting has…

Quantum Physics · Physics 2014-11-19 Li Yu , Carlos A. Perez-Delgado , Joseph F. Fitzsimons

Hybrid switching - in which a high bandwidth circuit switch (optical or wireless) is used in conjunction with a low bandwidth packet switch - is a promising alternative to interconnect servers in today's large scale data-centers. Circuit…

Networking and Internet Architecture · Computer Science 2015-12-24 Shaileshh Bojja Venkatakrishnan , Mohammad Alizadeh , Pramod Viswanath

We introduce Flux Matching, a new paradigm for generative modeling that generalizes existing score-based models to a broader family of vector fields that need not be conservative. Rather than requiring the model to equal the data score, the…

Machine Learning · Computer Science 2026-05-11 Peter Pao-Huang , Xiaojie Qiu , Stefano Ermon

We introduce Coordination-free Collaborative Replication (CCR), a new method for maintaining consistency across replicas in distributed systems without requiring explicit coordination messages. CCR automates conflict resolution, contrasting…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-17 Masato Takeichi

Industry-grade database systems are expected to produce the same result if the same query is repeatedly run on the same input. However, the numerous sources of non-determinism in modern systems make reproducible results difficult to…

Databases · Computer Science 2020-04-07 Ingo Müller , Andrea Arteaga , Torsten Hoefler , Gustavo Alonso

We present a new model for distributed shared memory systems, based on remote data accesses. Such features are offered by network interface cards that allow one-sided operations, remote direct memory access and OS bypass. This model leads…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-17 Franck Butelle , Camille Coti

Homomorphic permutation is fundamental to privacy-preserving computations based on batch-encoding homomorphic encryption. It underpins nearly all homomorphic matrix operations and predominantly influences their complexity. Permutation…

Cryptography and Security · Computer Science 2025-11-27 Xirong Ma , Junling Fang , Chunpeng Ge , Dung Hoang Duong , Yali Jiang , Yanbin Li , Willy Susilo , Lizhen Cui

We strive to use session type technology to prove behavioural properties of fault-tolerant distributed algorithms. Session types are designed to abstractly capture the structure of (even multi-party) communication protocols. The goal of…

Logic in Computer Science · Computer Science 2017-05-05 Manuel Adameit , Kirstin Peters , Uwe Nestmann

Dynamic feature selection, where we sequentially query features to make accurate predictions with a minimal budget, is a promising paradigm to reduce feature acquisition costs and provide transparency into a model's predictions. The problem…

Machine Learning · Computer Science 2024-09-10 Soham Gadgil , Ian Covert , Su-In Lee

Summarising distributed data is a central routine for parallel programming, lying at the core of widely used frameworks such as the map/reduce paradigm. In the IoT context it is even more crucial, being a privileged mean to allow long-range…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-07 Giorgio Audrito , Sergio Bergamini