A distributed consensus protocol for clock synchronization in wireless sensor network

By Luca Schenato, Giovanni Gamba. 2007

242 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Ji Liu
2. Xiangru Lian
3. Ce Zhang
4. Philipp Sommer
5. Ji Liu
6. Tao Sun
7. Roger Wattenhofer
8. Cho-Jui Hsieh

Citations in the corpus

• Asynchronous Decentralized Parallel Stochastic Gradient Descent (2017, methodology): “…studied by the control community for solving the consensus problem where the goal is to compute the mean of all the data distributed on multiple nodes [Aysal et al., 2009, Boyd et al., 2005, Carli et al., 2010, Fagnani and Zampieri, 2008, Olfati-Saber et al., 2007, Schenato and Gamba, 2007].”
• Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent (2017, methodology): “…there are work on the consensus problem for which decentralized algorithms are studied to compute the mean of all the data distributed on multiple nodes [Aysal et al., 2009, Boyd et al., 2005, Carli et al., 2010, Fagnani and Zampieri, 2008, Olfati-Saber et al., 2007, Schenato and Gamba, 2007].”
• Gradient clock synchronization in wireless sensor networks (2009, background): “It is inspired by a long list of theoretical papers, originating in the distributed computing community [9, 13, 24, 17], lately also being adopted by the control theory community [21].”
• Design and analysis of distributed averaging with quantized communication (2014, background): “Consensus processes play an important role in many other problems such as Google’s PageRank [16], clock synchronization [27], and formation control [14].”
• Average TimeSynch: A consensus-based protocol for clock synchronization in wireless sensor networks (2011, unknown): “Preliminary results about this work have appeared in [2],[21] and [20].”
• Decentralized Federated Averaging (2021, background): “Decentralized algorithmswere originally developed to calculate the mean of data that are stored over multiple sensors [21], [22], [23], [24].”
• Consensus in multi-agent systems: a review (2021, background): “Consensus means the interaction between groups of agents in a team, via sensors or a communication network, to reach an agreement on a common value or state (Olfati-Saber and Shamma 2005; Schenato and Gamba 2007; Olfati-Saber et al. 2006).”
• Convergence Speed in Distributed Consensus and Averaging (2009, unknown): “Motivated by this negative result, we approach the averaging problem differently: we introduce an averaging algorithm based on “load balancing” ideas (Section 8.2), and prove a polynomial bound on its convergence time (Section 8.3).”