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Distributed Maximum Consensus over Noisy Links
Ehsan Lari, Reza Arablouei, Naveen K. D. Venkategowda, Stefan Werner
https://arxiv.org/abs/2403.18509 https:…

Distributed Maximum Consensus over Noisy Links
We introduce a distributed algorithm, termed noise-robust distributed maximum consensus (RD-MC), for estimating the maximum value within a multi-agent network in the presence of noisy communication links. Our approach entails redefining the maximum consensus problem as a distributed optimization problem, allowing a solution using the alternating direction method of multipliers. Unlike existing algorithms that rely on multiple sets of noise-corrupted estimates, RD-MC employs a single set, enhanc…

Modelling the Raft Distributed Consensus Protocol in mCRL2
Parth Bora (Eindhoven University of Technology), Pham Duc Minh (Eindhoven University of Technology), Tim A. C. Willemse (Eindhoven University of Technology)
https://arxiv.org/abs/2403.18916

Modelling the Raft Distributed Consensus Protocol in mCRL2
The consensus problem is a fundamental problem in distributed systems. It involves a set of actors, or entities, that need to agree on some values or decisions. The Raft algorithm is a solution to the consensus problem that has gained widespread popularity as an easy-to-understand and implement alternative to Lamport's Paxos algorithm. In this paper we discuss a formalisation of the Raft algorithm and its associated correctness properties in the mCRL2 specification language.

GCBF : A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control
Songyuan Zhang, Oswin So, Kunal Garg, Chuchu Fan
https://arXiv.org/abs/2401.14554

GCBF+: A Neural Graph Control Barrier Function Framework for Distributed Safe Multi-Agent Control
Distributed, scalable, and safe control of large-scale multi-agent systems (MAS) is a challenging problem. In this paper, we design a distributed framework for safe multi-agent control in large-scale environments with obstacles, where a large number of agents are required to maintain safety using only local information and reach their goal locations. We introduce a new class of certificates, termed graph control barrier function (GCBF), which are based on the well-established control barrier fu…

Privacy-Preserving Distributed Nonnegative Matrix Factorization
Ehsan Lari, Reza Arablouei, Stefan Werner
https://arxiv.org/abs/2403.18326 https://<…

Privacy-Preserving Distributed Nonnegative Matrix Factorization
Nonnegative matrix factorization (NMF) is an effective data representation tool with numerous applications in signal processing and machine learning. However, deploying NMF in a decentralized manner over ad-hoc networks introduces privacy concerns due to the conventional approach of sharing raw data among network agents. To address this, we propose a privacy-preserving algorithm for fully-distributed NMF that decomposes a distributed large data matrix into left and right matrix factors while sa…

Distributed Intelligent Integrated Sensing and Communications: The 6G-DISAC Approach
Emilio Calvanese Strinati, George C. Alexandropoulos, Madhusudan Giyyarpuram, Philippe Sehier, Sami Mekki, Vincenzo Sciancalepore, Maximilian Stark, Mohamed Sana, Benoit Denis, Maurizio Crozzoli, Navid Amani, Placido Mursia, Raffaele D Errico, Mauro Boldi, Francesca Costanzo, Francois Rivet, Henk Wymeerschx

Distributed Intelligent Integrated Sensing and Communications: The 6G-DISAC Approach
This paper introduces the concept of Distributed Intelligent integrated Sensing and Communications (DISAC), which expands the capabilities of Integrated Sensing and Communications (ISAC) towards distributed architectures. Additionally, the DISAC framework integrates novel waveform design with new semantic and goal-oriented communication paradigms, enabling ISAC technologies to transition from traditional data fusion to the semantic composition of diverse sensed and shared information. This prog…

Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets
Yuchen Yang, Kaihong Lu, Long Wang
https://arXiv.org/abs/2401.14776

Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets
In this paper, the problem of distributed optimization is studied via a network of agents. Each agent only has access to a stochastic gradient of its own objective function in the previous time, and can communicate with its neighbors via a network. To handle this problem, an online distributed clipped stochastic gradient descent algorithm is proposed. Dynamic regrets are used to capture the performance of the algorithm. Particularly, the high probability bounds of regrets are analyzed when the …

UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving
Yifei Li, Ryan Chard, Yadu Babuji, Kyle Chard, Ian Foster, Zhuozhao Li
https://arxiv.org/abs/2403.19257

UniFaaS: Programming across Distributed Cyberinfrastructure with Federated Function Serving
Modern scientific applications are increasingly decomposable into individual functions that may be deployed across distributed and diverse cyberinfrastructure such as supercomputers, clouds, and accelerators. Such applications call for new approaches to programming, distributed execution, and function-level management. We present UniFaaS, a parallel programming framework that relies on a federated function-as-a-service (FaaS) model to enable composition of distributed, scalable, and high-perfor…

Modelling the Raft Distributed Consensus Protocol in mCRL2
Parth Bora (Eindhoven University of Technology), Pham Duc Minh (Eindhoven University of Technology), Tim A. C. Willemse (Eindhoven University of Technology)
https://arxiv.org/abs/2403.18916

Modelling the Raft Distributed Consensus Protocol in mCRL2
The consensus problem is a fundamental problem in distributed systems. It involves a set of actors, or entities, that need to agree on some values or decisions. The Raft algorithm is a solution to the consensus problem that has gained widespread popularity as an easy-to-understand and implement alternative to Lamport's Paxos algorithm. In this paper we discuss a formalisation of the Raft algorithm and its associated correctness properties in the mCRL2 specification language.