Distributed energy management of interconnected microgrids that is based on model predictive control (MPC) relies on the cooperation of all agents (microgrids). This paper discusses the case in which some of the agent...
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Distributed energy management of interconnected microgrids that is based on model predictive control (MPC) relies on the cooperation of all agents (microgrids). This paper discusses the case in which some of the agents might perform one type of adversarial actions (attacks) and they do not comply with the decisions computed by performing a distributed MPC algorithm. In this regard, these agents could obtain a better performance at the cost of degrading the performance of the network as a whole. A resilient distributed method that can deal with such issues is proposed in this paper. The method consists of two parts. The first part is to ensure that the decisions obtained from the algorithm are robustly feasible against most of the attacks with high confidence. In this part, we formulate the economic dispatch problem, taking into account the attacks as a chance-constrained problem, and employ a two-step randomization-based approach to obtain a feasible solution with a predefined level of confidence. The second part consists in the identification and mitigation of the adversarial agents, which utilizes hypothesis testing with Bayesian inference and requires each agent to solve a mixed-integer problem to decide the connections with its neighbors. In addition, an analysis of the decisions computed using the stochastic approach and the outcome of the identification and mitigation method is provided. The performance of the proposed approach is also shown through numerical simulations.
This paper considers the resilient multi-dimensional consensus problem in networked systems, where some of the agents might be malicious (or faulty). We propose a multi-dimensional consensus algorithm, where at each t...
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This paper considers the resilient multi-dimensional consensus problem in networked systems, where some of the agents might be malicious (or faulty). We propose a multi-dimensional consensus algorithm, where at each time step each healthy agent computes a "safe kernel" based on the information from its neighbors, and modifies its own state towards a point inside the kernel. Assuming that the number of malicious agents is locally (or globally) upper bounded, sufficient conditions on the network topology are presented to guarantee that the benign agents exponentially reach an agreement within the convex hull of their initial states, regardless of the actions of the misbehaving ones. It is also revealed that the graph connectivity and robustness required to achieve the resilient consensus increases linearly with respect to the dimension of the agents' state, indicating the existence of a trade-off between the low communication cost and system security. Numerical examples are provided in the end to validate the theoretical results. Copyright (C) 2020 The Authors.
This paper considers the resilient multi-dimensional consensus problem in networked systems, where some of the agents might be malicious (or faulty). We propose a multidimensional consensus algorithm, where at each ti...
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This paper considers the resilient multi-dimensional consensus problem in networked systems, where some of the agents might be malicious (or faulty). We propose a multidimensional consensus algorithm, where at each time step each healthy agent computes a “safe kernel” based on the information from its neighbors, and modifies its own state towards a point inside the kernel. Assuming that the number of malicious agents is locally (or globally) upper bounded, sufficient conditions on the network topology are presented to guarantee that the benign agents exponentially reach an agreement within the convex hull of their initial states, regardless of the actions of the misbehaving ones. It is also revealed that the graph connectivity and robustness required to achieve the resilient consensus increases linearly with respect to the dimension of the agents’ state, indicating the existence of a trade-off between the low communication cost and system security. Numerical examples are provided in the end to validate the theoretical results.
Economic dispatch of interconnected microgrids that is based on distributed model predictive control (DMPC) requires the cooperation of all agents (microgrids). This paper discusses the case in which some of the agent...
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ISBN:
(纸本)9783907144008
Economic dispatch of interconnected microgrids that is based on distributed model predictive control (DMPC) requires the cooperation of all agents (microgrids). This paper discusses the case in which some of the agents might not comply with the decisions computed by performing a DMPC algorithm. In this regard, these agents could obtain a better performance at the cost of degrading the performance of the network as a whole. A resilient distributed method that can deal with such issues is proposed and studied in this paper. The method consists of two parts. The first part is to ensure that the decisions obtained from the algorithm are robustly feasible against most of the attacks with high confidence. In this part, we employ a two-step randomization-based approach to obtain a feasible solution with a predefined level of confidence. The second part consists in the identification and mitigation of the adversarial agents, which utilizes hypothesis testing with Bayesian inference and requires each agent to solve a mixed-integer problem to decide the connections with its neighbors. In addition, an analysis of the decisions computed using the stochastic approach and the outcome of the identification and mitigation method is provided. The performance of the proposed approach is also shown through numerical simulations.
A cryptocurrency is a digital asset designed to work as a medium of exchange that uses cryptography to secure its transactions, to control the creation of additional units, and to verify the transfer of assets. Crypto...
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ISBN:
(纸本)9781538676417
A cryptocurrency is a digital asset designed to work as a medium of exchange that uses cryptography to secure its transactions, to control the creation of additional units, and to verify the transfer of assets. Cryptocurrencies are a type of digital currencies, alternative currencies and virtual currencies. Cryptocurrencies use decentralized control as opposed to centralized electronic money and central banking systems. The decentralized control of each cryptocurrency works through a blockchain, which is a public transaction database,functioning as a distributed ledger. Neural Networks field has many techniques to perform predictions. They are widely used to predict the future values of stock exchange indicators variables. In this paper we will try to use Artificial Neural Network to predict cryptocurrencies close prices, and we'll study the difference in price change with the normal stock exchanges.
We extend the Faulty RAM model by Finocchi and Italiana (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the ...
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We extend the Faulty RAM model by Finocchi and Italiana (2008) by adding a safe memory of arbitrary size S, and we then derive tradeoffs between the performance of resilient algorithmic techniques and the size of the safe memory. Let delta and alpha denote, respectively, the maximum amount of faults which can happen during the execution of an algorithm and the actual number of occurred faults, with alpha <= delta. We propose a resilient algorithm for sorting n entries which requires O (n log n + alpha(delta/S +log S)) time and uses Theta (S) safe memory words. Our algorithm outperforms previous resilient sorting algorithms which do not exploit the available safe memory and require O (n log n + alpha delta) time. Finally, we exploit our sorting algorithm for deriving a resilient priority queue. Our implementation uses Theta (S) safe memory words and Theta (n) faulty memory words for storing n keys, and requires O (log n + delta/S) amortized time for each insert and deletemin operation. Our resilient priority queue improves the O (log n + delta) amortized time required by the state of the art. (C) 2015 Elsevier B.V. All rights reserved.
We develop a k-d tree variant that is resilient to a pre-described number of memory corruptions while still using only linear space. We show how to use this data structure in the context of clustering in high-radiatio...
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