Robust Distributed Averaging on Networks with Adversarial Intervention

We study the interaction between a network designer and an adversary over a dynamical network. The network consists of nodes performing continuous-time distributed averaging. The goal of the network designer is to assist the nodes reach consensus by changing the weights of a limited number of links in the network. Meanwhile, an adversary strategically disconnects a set of links to prevent the nodes from converging. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. We utilize Pontryagin's Maximum Principle (MP) to tackle both problems and derive the optimal strategies. Although the canonical equations provided by the MP are intractable, we provide an alternative characterization for the optimal strategies that highlights a connection with potential theory. Finally, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for this zero-sum game.Comment: 8 pages, 2 figures, submitted to CDC 201

Adaptive Resource Allocation in Jamming Teams Using Game Theory

In this work, we study the problem of power allocation and adaptive modulation in teams of decision makers. We consider the special case of two teams with each team consisting of two mobile agents. Agents belonging to the same team communicate over wireless ad hoc networks, and they try to split their available power between the tasks of communication and jamming the nodes of the other team. The agents have constraints on their total energy and instantaneous power usage. The cost function adopted is the difference between the rates of erroneously transmitted bits of each team. We model the adaptive modulation problem as a zero-sum matrix game which in turn gives rise to a a continuous kernel game to handle power control. Based on the communications model, we present sufficient conditions on the physical parameters of the agents for the existence of a pure strategy saddle-point equilibrium (PSSPE).Comment: 6 pages, 2 figures, submitted to RAWNET/WNC3 201

Organic fouling in forward osmosis: A comprehensive review

Organic fouling in the forward osmosis process is complex and influenced by different parameters in the forward osmosis such as type of feed and draw solution, operating conditions, and type of membrane. In this article, we reviewed organic fouling in the forward osmosis by focusing on wastewater treatment applications. Model organic foulants used in the forward osmosis literature were highlighted, which were followed by the characteristics of organic foulants when real wastewater was used as feed solution. The various physical and chemical cleaning protocols for the organic fouled membrane are also discussed. The study also highlighted the effective pre-treatment strategies that are effective in reducing the impact of organic fouling on the forward osmosis (FO) membrane. The efficiency of cleaning methods for the removal of organic fouling in the FO process was investigated, including recommendations on future cleaning technologies such as Ultraviolet and Ultrasound. Generally, a combination of physical and chemical cleaning is the best for restoring the water flux in the FO process. 2020 by the authors.This research was funded by an NPRP grant (NPRP10-0117-170176) from the Qatar National Research Fund (a member of Qatar Foundation). This is the format recommended by the funding organization. Candidate S.Y. would like to acknowledge scholarship support from the University of Technology Sydney under UTS President's Scholarship and International Research Scholarship (IRP). In addition, this publication was possible by an NPRP grant (NPRP10-0117-170176) from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the authors.Scopu

Functional aplasia of the contralateral A1 segment influences clinical outcome in patients with occlusion of the distal internal carotid artery

Background: The importance of an A1 aplasia remains unclear in stroke patients. In this work, we analyze the impact of an A1 aplasia contralateral to an acute occlusion of the distal internal carotid artery (ICA) on clinical outcomes. Methods: We conducted a retrospective study of consecutive stroke patients treated with mechanical thrombectomy at 12 tertiary care centers between January 2015 and February 2021 due to an occlusion of the distal ICA. Functional A1 aplasia was defined as the absence of A1 or hypoplastic A1 (>50% reduction to the contralateral site). Functional independence was measured by the modified Rankin Scale (mRS ≤ 2). Results: In total, 81 out of 1068 (8%) patients had functional A1 aplasia contralateral to distal ICA occlusion. Patients with functional contralateral A1 aplasia were more severely affected on admission (median NIHSS 18, IQR 15–23 vs. 17, IQR 13–21; aOR: 0.672, 95% CI: 0.448–1.007, p = 0.054) and post-interventional ischemic damage was larger (median ASPECTS 5, IQR 1–7, vs. 6, IQR 3–8; aOR: 1.817, 95% CI: 1.184–2.789, p = 0.006). Infarction occurred more often within the ipsilateral ACA territory (20/76, 26% vs. 110/961, 11%; aOR: 2.482, 95% CI: 1.389–4.437, p = 0.002) and both ACA territories (8/76, 11% vs. 5/961, 1%; aOR: 17.968, 95% CI: 4.979–64.847, p ≤ 0.001). Functional contralateral A1 aplasia was associated with a lower rate of functional independence at discharge (6/81, 8% vs. 194/965, 20%; aOR: 2.579, 95% CI: 1.086–6.122, p = 0.032) and after 90 days (5/55, 9% vs. 170/723, 24%; aOR: 2.664, 95% CI: 1.031–6.883, p = 0.043). Conclusions: A functional A1 aplasia contralateral to a distal ICA occlusion is associated with a poorer clinical outcome

Information spread in networks: games, optimal control, and stabilization

This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack on the network. To this end, we propose a distributed version of the classical logic-based supervisory control scheme. Given a network of agents whose dynamics contain unknown parameters, the distributed supervisory control scheme is used to assist the agents to converge to a certain set-point without requiring them to have explicit knowledge of that set-point. Unlike the classical supervisory control scheme where a centralized supervisor makes switching decisions among the candidate controllers, in our scheme, each agent is equipped with a local supervisor that switches among the available controllers. The switching decisions made at a certain agent depend only on the information from its neighboring agents. We provide sufficient conditions for stabilization and apply our framework to the distributed averaging problem in the presence of large modeling uncertainty. For infected networks, we study the stability properties of a susceptible-infected-susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary network topologies. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide conditions for the global asymptotic stability of the equilibrium points in both cases over strongly and weakly connected directed networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. Furthermore, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition, for the global convergence to the all-healthy state, that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control

Algorithms for mono- and multi-objective bin packing problems

Le problème de bin packing consiste à déterminer le nombre minimum de conteneurs (bins) nécessaires pour ranger un ensemble d’objets. Ce problème NP- complet fait depuis de nombreuses années l’objet de multiples travaux de recherche, théoriques et pratiques. On le retrouve entre autres dans l’industrie de découpe de tissu, de l’acier, de bois et de verre. La littérature sur le problème de bin packing est riche et les algorithmes et approches de résolution sont très diverses. Cependant, les solutions proposées par ces algorithmes peuvent ne pas être utiles quand on traite des problèmes industriels réels. Dans cette thèse, nous considérons plusieurs types de contraintes liées à des incompatibilités entre objets. Ces contraintes sont inspirées de celles rencontrées lors d’une collaboration industrielle. Le sujet de recherche de cette thèse porte sur la résolution d’une variété de problèmes de bin packing. Nous nous intéressons à des bornes inférieures et supérieures pour les trois problèmes suivants : un problème de bin packing avec conflits dans lequel des relations de compatibilité sont exprimées entre les couples d’objets ; un problème de bin packing bi-objectif dans lequel deux critères sont à minimiser, le nombre de bins utilisés et le nombre de couples en conflit placés dans le même bin ; un problème de bin packing avec objets fragiles dans lequel la somme des tailles des objets placés dans un bin ne dépasse la fragilité d’aucun de ces objets.The bin packing problem consists in minimizing the number of containers (bins) needed to place a set of objects. This NP-complete problem has been, for many years, the subject of multiple theoretical and practical researches. It appears in many industrial applications such as cutting steel, wood and glass. The literature on the bin packing problem is rich and the algorithms and resolution approaches are also very are very diversified. However, solutions offered by these algorithms may not be useful when we deal with real industrial problems. In this thesis, we consider several types of constraints such as compatibility relations between objects. These constraints are issued from real life industrial applications. The research topic of this thesis focuses on solving a variety of bin packing problems. We are interested in lower and upper bounds for three problems: a bin packing problem with conflicts in which some compatibility relations exist between pairs of objects, a problem bi-objective bin packing in which two criteria are to minimize: the number of bins used and the number of conflicting couples of objects placed in the same bin, a problem of bin packing with fragile objects in which the sum of the sizes of objects placed in a bin does not exceed the fragility of any of these objects