Journal Article10.1109/TSIPN.2021.3062985
Differentially Private Distributed Resource Allocation via Deviation Tracking
Tie Ding,Shanying Zhu,Cailian Chen,Jinming Xu,Xinping Guan +4 more
- 02 Mar 2021
- Vol. 7, pp 222-235
29
TL;DR: In this article, a completely distributed algorithm via deviation tracking was proposed to solve the constrained resource allocation problem and preserve differential privacy for cost functions by masking states and directions with decaying Laplace noise.
read more
Abstract: This paper studies the distributed resource allocation problem where all the agents cooperatively minimize the sum of their cost functions. To prevent private information from being disclosed, agents need to keep their cost functions private against potential adversaries and other agents. We first propose a completely distributed algorithm via deviation tracking that deals with constrained resource allocation problem and preserve differential privacy for cost functions by masking states and directions with decaying Laplace noise. Adopting constant stepsizes, we prove that the proposed algorithm converges linearly in mean square. The linear convergence is established under the standard assumptions of Lipschitz gradients and strong convexity instead of the assumption of bounded gradients that is usually imposed in most existing works. Moreover, we show that the algorithm preserves differential privacy for every agent's cost function and establish the trade-off between privacy and convergence accuracy. Furthermore, we apply the proposed algorithm to economic dispatch problem in IEEE 14-bus system to verify the theoretical results.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A Multi-Agent Collaborative Environment Learning Method for UAV Deployment and Resource Allocation
Zhaojun Dai,Yan Zhang,Wancheng Zhang,Xinran Luo,Zunwen He +4 more
- 01 Jan 2022
TL;DR: Simulation results indicate that the proposed resource allocation algorithm for the UAV networks based on multi-agent collaborative environment learning is able to effectively improve the network utility compared with the multi- agent deep reinforcement learning algorithm without information interaction.
47
Privacy-Protected Decentralized Dual Averaging Push With Edge-Based Correlated Perturbations Over Time-Varying Directed Networks
TL;DR: In this paper , the authors proposed a privacy-protected decentralized dual averaging push algorithm that employs edge-based correlated perturbation signals to the process of information transmission for protecting privacy, which can overcome the impact of the imbalance caused by time-varying directed networks.
8
Security-Based Resilient Robust Model Predictive Control for Polytopic Uncertain Systems Subject to Deception Attacks and RR Protocol
TL;DR: In this article , a robust robust model predictive control (RMPC) problem for a class of discrete-time polytopic uncertain systems with deception attacks and the round-robin (RR) protocol is considered.
7
Asynchronous Algorithms for Decentralized Resource Allocation Over Directed Networks
TL;DR: In this article , the authors considered a class of decentralized resource allocation problems over directed networks, where each node only communicates with its in-neighbors and attempts to minimize its own cost when network-wide resource constraints as well as local capacity limits are satisfied.
6
Privacy-Preserving Decentralized Dual Averaging for Online Optimization Over Directed Networks
01 Jan 2023
TL;DR: In this article , the authors proposed an effective differentially private decentralized dual averaging algorithm, which takes into account the usages of perturbation with Laplace noise and gradient rescaling strategies to preserve differential privacy and eliminate the unbalancedness of directed networks, respectively.
6
References
•Book
Power Generation, Operation, and Control
Allen J. Wood,Bruce Wollenberg +1 more
- 01 Jan 1984
TL;DR: In this paper, the authors present a graduate-level text in electric power engineering as regards to planning, operating, and controlling large scale power generation and transmission systems, including characteristics of power generation units, transmission losses, generation with limited energy supply, control of generation, and power system security.
9.3K
Differential privacy: a survey of results
Cynthia Dwork
- 25 Apr 2008
TL;DR: This survey recalls the definition of differential privacy and two basic techniques for achieving it, and shows some interesting applications of these techniques, presenting algorithms for three specific tasks and three general results on differentially private learning.
EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization
TL;DR: A novel decentralized exact first-order algorithm (abbreviated as EXTRA) to solve the consensus optimization problem and uses a fixed, large step size, which can be determined independently of the network size or topology.
1.2K
Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs
TL;DR: This paper introduces a distributed algorithm, referred to as DIGing, based on a combination of a distributed inexact gradient method and a gradient tracking technique that converges to a global and consensual minimizer over time-varying graphs.
Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks
Tuyen X. Tran,Dario Pompili +1 more
TL;DR: Simulation results show that the proposed novel heuristic algorithm performs closely to the optimal solution and that it significantly improves the users’ offloading utility over traditional approaches.