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21st IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS)

作者： Elgabli, Anis Elbamby, Mohammed S. Perfecto, Cristina Krouka, Mounssif Bennis, Mehdi Aggarwal, Vaneet King Fahd Univ Petr & Minerals Dept Ind & Syst Engn Interdisciplinary Res Ctr Commun Syst & Sensing I Interdisciplinary Res Ctr Intelligent Secure Syst Dhahran Saudi Arabia Telefon Res Madrid Spain Univ Basque Country UPV EHU Bilbao Sch Engn Bilbao Spain Univ Oulu Ctr Wireless Commun Oulu Finland Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

ISBN: (纸本)9798350363999;9798350364002

Wirelessly streaming high quality 360 degree videos is still a challenging problem. When there are many users watching different 360 degree videos and competing for the computing and communication resources, the streaming algorithm at hand should maximize the average quality of experience (QoE) while guaranteeing a minimum rate for each user. In this paper, we propose a cross layer optimization approach that maximizes the available rate to each user and efficiently uses it to maximize users' QoE. Particularly, we consider a tile based 360 degree video streaming, and we optimize a QoE metric that balances the tradeoff between maximizing each user's QoE and ensuring fairness among users. We show that the problem can be decoupled into two interrelated subproblems: (i) a physical layer subproblem whose objective is to find the download rate for each user, and (ii) an application layer subproblem whose objective is to use that rate to find a quality decision per tile such that the user's QoE is maximized. We prove that the physical layer subproblem can be solved optimally with low complexity and an actor-critic deep reinforcement learning (DRL) is proposed to leverage the parallel training of multiple independent agents and solve the application layer subproblem. Extensive experiments reveal the robustness of our scheme and demonstrate its significant performance improvement compared to several baseline algorithms.

关键词： 360 video Wireless Streaming Video Rate Adaptation Virtual Reality (VR) non convex optimization Asynchronous advantage actor-critic (A3C) Deep Reinforcement Learning (DRL) millimeter wave (mmWave) communications

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Optimized Preference-Aware Multi-Path Video Streaming with Scalable Video Coding

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2020年第1期19卷 159-172页

作者： Elgabli, Anis Liu, Ke Aggarwal, Vaneet Univ Oulu Ctr Wireless Commun Oulu 90014 Finland Chinese Acad Sci Inst Comp Technol Beijing Peoples R China Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

Most client hosts are equipped with multiple network interfaces (e.g., WiFi and cellular networks). Simultaneous access of multiple interfaces can significantly improve the users' quality of experience (QoE) in video streaming. An intuitive approach to achieve it is to use Multi-path TCP (MPTCP). However, the deployment of MPTCP, especially with link preference, requires OS kernel update at both the client and server side, and a vast amount of commercial content providers do not support MPTCP. Thus, in this paper, we realize a multi-path video streaming algorithm in the application layer instead, by considering Scalable Video Coding (SVC), where each layer of every chunk can be fetched from only one of the orthogonal paths. We formulate the quality decisions of video chunks subject to the available bandwidth of the different paths, chunk deadlines, and link preferences as an optimization problem. The objective is to to optimize a QoE metric that maintains a tradeoff between maximizing the playback rate of every chunk and ensuring fairness among chunks. The proposed metric prefers to use bandwidth of the links to optimize a concave utility function of the chunk quality. Even though the formulation is a non-convex discrete optimization, we provide a quadratic complexity algorithm which is shown to be optimal in some special cases. We further propose an online algorithm where several challenges including bandwidth prediction errors, are addressed. Extensive emulated experiments in a real testbed with real traces of public dataset reveal the robustness of our scheme and demonstrate its significant performance improvement compared to other multi-path algorithms.

关键词： Static VAr compensators Streaming media Prediction algorithms Bandwidth Video coding Quality of experience optimization Video streaming multi-path scalable video coding video quality stall duration multi-path TCP non convex optimization

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An Aspect of Bilevel Fixed Charge Fractional Transportation Problem

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International Journal of Applied and Computational Mathematics 2020年第1期6卷 1-19页

作者： Kaushal, Bindu Arora, Ritu Arora, Shalini Department of Applied Sciences and Humanities Indira Gandhi Delhi Technical University For Women New Delhi 110006 India Keshav Mahavidyalaya University of Delhi Delhi India

Bilevel Programming Problem (BLPP) is a hierarchical optimization problem. Here, the constraint set of the upper level problem, called the leader, is ascertained by the lower level problem, called the follower. In this paper, a BLPP is considered where the leader’s problem is a fractional transportation problem and the follower’s problem is a fixed charge transportation problem. Hence, a bilevel fixed charge fractional transportation problem (BLFCFTP) is formulated. The problem is also explained through graphical representation. The problem comes from a food chain industry which is utilizing its used vegetable cooking oil for the production of biodiesel. The mathematical model of the problem is presented and is also explained through graphical representation. The problem pertains to a food chain industry wherein the used vegetable cooking oil is utilized for the production of biodiesel. Another example quotes Indore city where waste is converted into bio-CNG which is used to run public transport. The managerial importance of the work is that it will promote a sustainable and environment friendly practice. This will result in reduction of waste and check environmental pollution. An algorithm to solve BLFCFTP is developed. The examples explaining the algorithm are exhibited by a viable situation. These examples are subsequently deciphered in MATLAB. © 2020, Springer Nature India Private Limited.

关键词： Bilevel programming Fixed charge transportation problem (FCTP) Fractional transportation problem (FTP) non convex optimization Optimal solution

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La programmation DC et DCA pour la sécurité de la couche physique des réseaux sans fil: DC programming and DCA for physical layer security in wireless network

La programmation DC et DCA pour la sécurité de la couche p...

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作者： Nguyen, Phuong Anh Université de Lorraine

学位级别：博士

La sécurité de la couche physique consiste à permettre la transmission des données confidentielles via un réseau sans fil en présence d'utilisateurs illégitimes, sans s'appuy... 详细信息

La sécurité de la couche physique consiste à permettre la transmission des données confidentielles via un réseau sans fil en présence d'utilisateurs illégitimes, sans s'appuyer sur un cryptage de couche supérieure. L'essence de la sécurité de la couche physique est de maximiser le taux de secret, qui est le taux maximal d'informations sans interception par les espions. De plus, la conception de la sécurité de la couche physique prend en compte la minimisation de la puissance de transmission. Ces deux objectifs sont souvent en conflit l'un avec l'autre. Ainsi, la recherche sur les conceptions de sécurité de la couche physique se concentre souvent sur les deux principales classes de problèmes d’optimisation : maximiser le taux de secret sous contrainte de puissance de transmission et minimiser la puissance de transmission sous contrainte de taux de secret. Ces problèmes sont non convexes, donc difficiles à résoudre. Dans cette thèse, nous nous concentrons sur le développement des méthodes d'optimisation pour résoudre ces deux classes de problèmes d'optimisation. Nos méthodes sont basées sur la programmation DC (Difference of convex functions) et DCA (DC Algorithm) étant reconnues comme des outils puissants d'optimisation non convexe. Dans la première partie, nous considérons trois classes de problèmes de maximisation du taux de secret (chapitre 2, 3, 4). Le chapitre 2 étudie la transmission sécurisée des informations dans un système de relais MISO. Le relais utilise une combinaison de technique de formation de faisceau et de technique de bruit artificiel sous les modèles déterministes des canaux d'incertitude. Sans utiliser de relais, le chapitre 3 étudie le problème du transfert simultané d'information sans fil et de l’énergie dans un système sécurisé sous parfaite connaissance des canaux et imparfaite connaissance des canaux. Deux stratégies de transmission : formation de faisceaux avec bruit artificiel et sans bruit artificiel sont étudiés. Avec l'hypothèse du cana

关键词： Optimisation non convexe Programmation DC DCA Sécurité de la couche physique non convex optimization DC programming DCA Physical layer security 005.8 004.6

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SmartStreamer: Preference-Aware Multipath Video Streaming Over MPTCP

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第7期68卷 6975-6984页

作者： Elgabli, Anis Aggarwal, Vaneet Purdue Univ Sch Elect Comp Engn W Lafayette IN 47907 USA Univ Oulu Ctr Wireless Commun Oulu 90014 Finland Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

Simultaneous access to multiple interfaces (e.g., WiFi and cellular networks) can significantly improve the users' quality of experience (QoE) in video streaming. However, some interfaces could be more expensive to use and less energy efficient. Therefore, in this paper, we propose a preference-aware multipath video streaming algorithm over HTTP using multipath TCP (MPTCP). First, we formulate the quality decisions of the video chunks and the chunk's download policy subject to the chunk's deadlines, the available bandwidth of the different paths, and the link preferences as a non-convex optimization problem. The objective is to optimize a novel QoE metric that maintains a tradeoff between maximizing the quality of every video's chunk and ensuring quality fairness among all chunks for the minimum re-buffering (stall) duration, and without violating the link preference constraint. Second, we develop a polynomial time complexity algorithm to solve the proposed optimization problem, and provide guarantees for the proposed algorithm. We further propose a sliding window based online algorithm where several challenges including short bandwidth prediction with prediction errors are addressed. Extensive emulated experiments with real bandwidth traces of public datasets reveal the robustness of our scheme and demonstrate its significant performance improvement compared to the state-of-the-art multi-path streaming algorithms.

关键词： Video streaming multi-path multi-path TCP stall duration non convex optimization

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GroupCast: Preference-Aware Cooperative Video Streaming With Scalable Video Coding

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IEEE-ACM TRANSACTIONS ON NETWORKING 2019年第3期27卷 1138-1150页

作者： Elgabli, Anis Felemban, Muhamad Aggarwal, Vaneet Purdue Univ Sch ECE W Lafayette IN 47907 USA Univ Oulu Ctr Wireless Commun Oulu 90014 Finland KFUPM Dhahran 31261 Saudi Arabia Purdue Univ Sch IE W Lafayette IN 47907 USA

In this paper, we propose a preference-aware cooperative video streaming system for videos encoded using scalable video coding (SVC). In the proposed system, the collaborating users are interested in watching a video together on a shared screen. However, the willingness of each user to cooperate is subject to her own constraints such as user data plans. Using SVC, videos are segmented into chunks and each chunk is encoded using layers, where each layer can be fetched through any of the collaborating users. We formulate the problem of finding the optimal quality decisions and fetching policy of the SVC layers of video chunks subject to the available bandwidth, chunk deadlines, and cooperation willingness of the different users as an optimization problem. The objective is to optimize a QoE metric that maintains a trade-off between maximizing the playback rate of every chunk and ensuring fairness among all chunks to achieve the minimum skip (stall) duration without violating any of the imposed constraints. We propose an offline algorithm to solve the non-convex optimization problem when the bandwidth prediction is non-causally known. This algorithm has a run-time complexity that is polynomial in the video length and the number of collaborating users. Furthermore, we propose an online version of the algorithm for practical scenarios, where erroneous bandwidth prediction for a short window is used. Real implementation with android devices using SVC encoded video and a public dataset of bandwidth traces reveals the robustness and performance of the proposed algorithm and shows that the algorithm significantly outperforms round robin-based mechanisms in terms of avoiding skips/stalls and fetching video chunks at their highest quality possible.

关键词： Cooperative video streaming scalable video coding rate adaptation non convex optimization

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Waveform Design for Kalman Filter-Based Target Scattering Coefficient Estimation in Adaptive Radar System

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2018年第12期67卷 11805-11817页

作者： Chen, Peng Qi, Chenhao Wu, Lenan Wang, Xianbin Southeast Univ State Key Lab Millimeter Waves Nanjing 210096 Jiangsu Peoples R China Columbia Univ Dept Elect Engn New York NY 10027 USA Southeast Univ Sch Informat Sci & Engn Nanjing 210096 Jiangsu Peoples R China Western Univ Dept Elect & Comp Engn London ON N6A 3K7 Canada

The temporal correlation of target can be exploited to improve the radar estimation performance. This paper studies the estimation of target scattering coefficients in an adaptive radar system, and a novel estimation method based on Kalman filter (KF) with wavetbrm optimization is proposed for the temporally correlated target in the scenario with both noise and clutter. Different from the existing indirect methods, a direct optimization method is proposed to design the transmitted waveform and minimize the mean square error of the KF estimation. Additionally, the waveform is optimized subject to the practical constraints including the transmitted energy, the peak-to-average power ratio, and the target detection performance. With clutter and noise, the waveform optimization problem is non-convex. Therefore, a novel two-step method is proposed and converts the original non-convex problem into several semidefinite programming problems, which are convex and can solve efficiently. Simulation results demonstrate that the proposed KF-based method with waveform optimization can outperform state-of-art methods and significantly improve the estimation performance.

关键词： Adaptive radar system Kalman filter non convex optimization waveform optimization

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Real time trajectory optimization for nonlinear robotic systems: Relaxation and convexification

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SYSTEMS & CONTROL LETTERS 2017年 108卷 56-63页

作者： Liu, Changliu Tomizuka, Masayoshi Univ Calif Berkeley Dept Mech Engn Berkeley CA 94720 USA

Real time trajectory optimization is critical for robotic systems. Due to nonlinear system dynamics and obstacles in the environment, the trajectory optimization problems are highly nonlinear and non convex, hence hard to be computed online. Liu, Lin and Tomizuka proposed the convex feasible set algorithm (CFS) to handle the non convex optimization in real time by convexification. However, one limitation of CFS is that it will not converge to local optima when there are nonlinear equality constraints. In this paper, the slack convex feasible set algorithm (SCFS) is proposed to handle the nonlinear equality constraints, e.g. nonlinear system dynamics, by introducing slack variables to relax the constraints. The geometric interpretation of the method is discussed. The feasibility and convergence of the SCFS algorithm is proved. It is demonstrated that SCFS performs better than existing non convex optimization methods such as interior-point, active set and sequential quadratic programming, as it requires less computation time and converges faster. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Optimal control nonlinear optimization non convex optimization Motion planning

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On a Conservation Law and the Achievable Region for Waiting Time Tail Probabilities in 2-class M/G/1 Queueing Systems 13

On a Conservation Law and the Achievable Region for Waiting ...

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13th International Symposium on Modeling and optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Gupta, Manu K. Hemachandra, N. Indian Inst Technol Ind Engn & Operat Res Bombay 400076 Maharashtra India

ISBN: (纸本)9783901882746

Conservation laws and the related achievable region for mean waiting times are important concepts in multi-class queues. The nice geometric polytope structure of this region driven by the conservation law is exploited extensively for dynamic control of multi-class queues. Such control problems have wide range of applications in computers, communication networks and manufacturing systems. Tail probability of each class's waiting time is another important performance measure in any multi-class queue. This paper studies an approximate conservation law, the related achievable region and completeness of the tail probability of waiting time of each class in two class M/G/1 queues. We use completeness of the recently introduced relative priority scheme for mean waiting time vector as well as a suitable partition of the stability region of the queue to show that this approximate achievable region for tail probabilities is enclosed in a trapezium. We also study the tightness of bounds based on this decomposition of the stability region.

关键词： Dynamic priority tail probability achievable region conservation law multi class queues optimal control of queues non convex optimization

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Dual attitude and parameter estimation of passively magnetically stabilized nano satellites

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ACTA ASTRONAUTICA 2014年第1期94卷 145-158页

作者： Burton, R. Rock, S. Springmann, J. Cutler, J. Stanford Univ Stanford CA 94305 USA Univ Michigan Ann Arbor MI 48109 USA

The attitude determination capability of a nano satellite is limited by a lack of traditional high performance attitude sensors, a result of having small budgets for mass and power. Attitude determination can still be performed on a nano satellite with low fidelity sensors, but an accurate model of the spacecraft attitude dynamics is required. The passive magnetic stabilization systems commonly employed in nano satellites are known to introduce uncertainties in the parameters of the attitude dynamics model that cannot easily be resolved prior to launch. In this paper, a batch estimation problem is formulated that simultaneously solves for the attitude of the spacecraft and performs parameter estimation on the magnetic properties of the magnetic materials using only a measurement of the solar vector. The estimation technique is applied to data from NASA Ames Research Center's O/OREOS nano satellite and the University of Michigan's RAX-1 nano satellite, where clear differences are detected between the magnetic properties as measured before launch and those that fit the observed data. To date this is the first known on-orbit verification of the attitude dynamics model of a passively magnetically stabilized spacecraft. (C) 2013 IAA. Published by Elsevier Ltd. All rights reserved.

关键词： Attitude determination Nano satellites Passive magnetic stabilization Batch estimation non convex optimization Cubesat

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