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807 results on '"Assi, Chadi"'

103. Investigation of Power-Aware IEEE 802. 11 Performance in Multi-hop Ad Hoc Networks

Author

Alawieh, Basel, Assi, Chadi, Mouftah, Hussein, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhang, Hongke, editor, Olariu, Stephan, editor, Cao, Jiannong, editor, and Johnson, David B., editor

Published
2007
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104. A Study on the Binary Exponential Backoff in Noisy and Heterogeneous Environment

Author

Shamy, Khoder, Assi, Chadi, Guang, Lei, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhang, Hongke, editor, Olariu, Stephan, editor, Cao, Jiannong, editor, and Johnson, David B., editor

Published
2007
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105. Interlayer Attacks in Mobile Ad Hoc Networks

Author

Guang, Lei, Assi, Chadi, Benslimane, Abderrahim, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cao, Jiannong, editor, Stojmenovic, Ivan, editor, Jia, Xiaohua, editor, and Das, Sajal K., editor

Published
2006
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107. Impact of Resource Sharability on Dual Failure Restorability in Optical Mesh Networks

Author

Assi, Chadi, Huo, Wei, Shami, Abdallah, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Boutaba, Raouf, editor, Almeroth, Kevin, editor, Puigjaner, Ramon, editor, Shen, Sherman, editor, and Black, James P., editor

Published
2005
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108. Centralized Versus Distributed Re-provisioning in Optical Mesh Networks

Author

Assi, Chadi, Huo, Wei, Shami, Abdallah, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lorenz, Pascal, editor, and Dini, Petre, editor

Published
2005
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110. EVOLIoT

Author

Dib, Mirabelle, primary, Torabi, Sadegh, additional, Bou-Harb, Elias, additional, Bouguila, Nizar, additional, and Assi, Chadi, additional

Published
2022
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142. A Data Mining/ANFIS and Adaptive Control for Detection and Mitigation of Attacks on DC MGs

Author

Abazari, Ahmadreza, Zadsar, Masoud, Ghafouri, Mohsen, Atallah, Ribal, and Assi, Chadi

Abstract

The integration of information and communication technologies (ICTs) has provided modern smart grids, such as direct current (DC) microgrids (MGs), with various advantages, e.g., the possibility of large-scale integration of renewable energy sources and complex control schemes. This extensive deployment of ICTs, however, makes DC MGs prone to a variety of cyber threats, e.g., false data injection (FDI) attacks. On this basis, this paper develops online detection and mitigation schemes to counter FDI attacks against DC MGs. Initially, in the offline training of the detection scheme, the density-based spatial clustering of applications with noise (DBSCAN) method is used for extracting prescriptive features of DC MG measurements and clustering them in healthy and under-attack operations under several uncertainties in DC MG operations. These features are used to train an adaptive network-based fuzzy inference system (ANFIS) architecture for the online identification of FDI attacks. Afterward, the trained ANFIS is used to detect FDI attacks and obtain the attack vectors benefiting from the real-time measurements estimated by an optimal state observer. Finally, an adaptive model predictive controller (AMPC) is developed to update the power-sharing commands—and mitigate the FDI attack—using the ANFIS’s obtained attack vectors. The effectiveness of the proposed framework is evaluated for several realistic FDI attack scenarios and different uncertainties. To show the scalability of the proposed detection and mitigation methods, a DC MG with eight converters is also studied in the presence of FDI attacks and uncertainties using real-time simulations.

Published
2023
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143. Online Altitude Control and Scheduling Policy for Minimizing AoI in UAV-Assisted IoT Wireless Networks.

Author

Samir, Moataz, Assi, Chadi, Sharafeddine, Sanaa, and Ghrayeb, Ali

Subjects
REINFORCEMENT learning, MARKOV processes, INTERNET of things, ALTITUDES, STOCHASTIC processes
Abstract

This article considers unmanned aerial vehicle (UAV) assisted Internet of Things (IoT) networks, where low resource IoT devices periodically sample a stochastic process and need to upload more recent information to a Base Station (BS). Among the myriad of applications, there is a need for timely delivery of data (for example, status-updates) before the data becomes outdated and loses its value. Since transmission capabilities of IoT devices are limited, it may not always be feasible to transmit over one hop transmission to the BS. To address this challenge, UAVs with virtual queues are deployed as middle layer between IoT devices and the BS to relay recent information over unreliable channels. In the absence of channel conditions, the optimal online scheduling policy is investigated as well as dynamic UAV altitude control that maintains a fresh status of information at the BS. The objective of this paper is to minimize the Expected Weighted Sum Age of Information (EWSA) for IoT devices. First, the problem is formulated as an optimization problem that is however generally hard to solve. Second, an online model free Deep Reinforcement Learning (DRL) is proposed, where the deployed UAV obtains instantaneous channel state information (CSI) in real time along with any adjustment to its deployment altitude. Third, we formulate the online problem as a Markov Decision Process (MDP) and Proximal Policy Optimization (PPO) algorithm, which is a highly stable state-of-the-art DRL algorithm, is leveraged to solve the formulated problem. Finally, extensive simulations are conducted to verify findings and comprehensive comparisons with other baseline approaches are provided to demonstrate the effectiveness of the proposed design. [ABSTRACT FROM AUTHOR]

Published
2022
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