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Femtocaching in video content delivery: Assignment of video clips to serve dynamic mobile users

COMPUTER COMMUNICATIONS 2014年 51卷 60-69页

作者： Yue, Jianting Yang, Bo Chen, Cailian Guan, Xinping Zhang, Weidong Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200030 Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200030 Peoples R China McMaster Univ Dept Elect & Comp Engn Hamilton ON Canada Cyber Joint Innovat Ctr Hangzhou Zhejiang Peoples R China

Online video streaming has been experiencing great popularity in recent years, and an increasing number of video contents are now delivered via wireless networks, which brings an overwhelming burden towards mobile operators. Femtocells are introduced to improve the area spectral efficiency of wireless video delivery via short link transmission. The backhaul pressure in the presence of dense deployment of femtocells can be reduced by the technologies of femtocaching. In this paper, video clip selection and video clip assignment problems are considered for femtocaching. On one hand, since mobile users always pursue the video clips that are highly popular and can be played smoothly, it is important to ensure the satisfaction of mobile users. On the other hand, the assignment of multiple video clips among multiple femto-caches is also significant as the capacity of each cache is limited. To model the video selection dynamics of mobile users, an evolutionary game is introduced and two algorithms are proposed to result in an evolutionary stable strategies, which correspond to the balance of video popularity and video quality. For the video assignment problem, the auction-based algorithms are proposed with low complexity to approximate the social optimality with the limited caching capacities. As a consequence, all femtocells and mobile video users are satisfied with their utilities respectively. (c) 2014 Elsevier B.V. All rights reserved.

关键词： Femtocaching Video content Evolutionary game auction algorithm

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Distributed Energy Efficient Channel Allocation

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

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IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING 2019年第4期3卷 1152-1166页

作者： Naparstek, Oshri Zafaruddin, S. M. Leshem, Amir Jorswieck, Eduard A. Bar Ilan Univ Fac Engn IL-52900 Ramat Gan Israel Rafael Adv Def Syst Ltd IL-31021 Haifa Israel BITS Pilani Dept Elect & Elect Engn Pilani 333031 Rajasthan India Tech Univ Dresden Fac Elect & Comp Engn Commun Lab D-01062 Dresden Germany Tech Univ Carolo Wilhelmina Braunschweig Inst Commun Technol Braunschweig Germany

Design of energy efficient protocols for modern wireless systems has become an important area of research. In this paper, we propose a distributed optimization algorithm for the channel assignment problem for multiple interfering transceiver pairs that cannot communicate with each other. We first modify the auction algorithm for maximal energy efficiency and show that the problem can be solved without explicit message passing using the carrier sense multiple access (CSMA) protocol. We then develop a novel scheme by converting the channel assignment problem into perfect matchings on bipartite graphs. The proposed scheme improves the energy efficiency and does not require any explicit message passing or a shared memory between the users. We derive bounds on the convergence rate and show that the proposed algorithm converges faster than the distributed auction algorithm and achieves near-optimal performance under Rayleigh fading channels. We also present an asymptotic performance analysis of the fast matching algorithm for energy efficient resource allocation and prove the optimality for a large enough number of users and number of channels. Finally, we provide numerical assessments that confirm the faster convergence of the proposed algorithm compared to the distributed auction algorithm.

关键词： auction algorithm bipartite graph channel assignment energy efficiency (EE) linear programming distributed protocol multi-access channel Rayleigh fading channel wireless networks

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Optimal Resource Allocation for GAA Users in Spectrum Access System Using Q-Learning algorithm

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IEEE ACCESS 2022年 10卷 60790-60804页

作者： Abbass, Waseem Hussain, Riaz Frnda, Jaroslav Khan, Irfan Latif Javed, Muhammad Awais Malik, Shahzad A. COMSATS Univ Islamabad CUI Dept Elect & Comp Engn Islamabad 45550 Pakistan Univ Zilina Fac Operat & Econ Transport & Commun Dept Quantitat Methods & Econ Informat Zilina 01026 Slovakia VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Dept Telecommun Ostrava 70800 Czech Republic

Spectrum access system (SAS) is a three-tier layered spectrum sharing architecture proposed by the Federal Communications Commission (FCC) for Citizens Broadband Radio Service (CBRS) 3.5 GHz band. The available 150 MHz spectrum is dynamically shared among Incumbent Access (IA), Primary Access Licensees (PAL) and General Authorized Access (GAA) users. IA users are the highest priority federal military users, PAL users are the licensed users and the GAA users are the least priority unlicensed users. In this scenario, PAL operators are willing to give access to their idle spectrum to GAA users to generate extra revenue. SAS will ensure to protect IA users and PAL users from interference caused by lower-tier users. It is the responsibility of SAS to allocate resources to GAA users but the method to do so is left open. In this article, a novel auction algorithm based on Q-learning for dynamic spectrum access (SAS-QLA) is proposed. In SAS-QLA, multiple GAA users dynamically and intelligently bid using Q-learning to access PAL reserved idle channels. SAS will decide to allocate the channels to GAA users with maximum bidding offers. GAA users have their own quality of service (QoS) demands i.e., transmission rate, packet loss, bidding efficiency, and maintain the preference of available PAL reserved idle channels based on Q-learning considering the available QoS. The proposed scenario is also modeled as a knapsack NP-hard problem and solved using dynamic programming and distributed relaxation method. Numerical results demonstrate the effectiveness of the SAS-QLA algorithm in improving the bidding efficiency, maximizing the data rate per unit cost and spectrum utilization.

关键词： Gallium arsenide Heuristic algorithms Synthetic aperture sonar Quality of service Resource management Relaxation methods Q-learning auction algorithm CBRS-SAS GAA bidding Q-learning

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On the use of suboptimal matchings for scaling and ordering sparse symmetric matrices

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NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS 2015年第4期22卷 648-663页

作者： Hogg, Jonathan Scott, Jennifer STFC Rutherford Appleton Lab Dept Comp Sci Didcot OX11 0QX Oxon England

The use of matchings is a powerful technique for scaling and ordering sparse matrices prior to the solution of a linear system Ax = b. Traditional methods such as implemented by the HSL software package MC64 use the Hungarian algorithm to solve the maximum weight maximum cardinality matching problem. However, with advances in the algorithms and hardware used by direct methods for the parallelization of the factorization and solve phases, the serial Hungarian algorithm can represent an unacceptably large proportion of the total solution time for such solvers. Recently, auction algorithms and approximation algorithms have been suggested as alternatives for achieving near-optimal solutions for the maximum weight maximum cardinality matching problem. In this paper, the efficacy of auction and approximation algorithms as replacements for the Hungarian algorithm is assessed in the context of sparse symmetric direct solvers when used in problems arising from a range of practical applications. High-cardinality suboptimal matchings are shown to be as effective as optimal matchings for the purposes of scaling. However, matching-based ordering techniques require that matchings are much closer to optimality before they become effective. The auction algorithm is demonstrated to be capable of finding such matchings significantly faster than the Hungarian algorithm, but our 1/2-approximation matching approach fails to consistently achieve a sufficient cardinality. Copyright (c) 2015 The Authors Numerical Linear Algebra with Applications Published by John Wiley & Sons Ltd.

关键词： approximation algorithm auction algorithm matching sparse symmetric matrix scaling ordering

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Distributed coordination of emergency medical service for angioplasty patients

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ANNALS OF MATHEMATICS AND ARTIFICIAL INTELLIGENCE 2016年第1期78卷 73-100页

作者： Lujak, Marin Billhardt, Holger Ossowski, Sascha Univ Rey Juan Carlos Madrid Spain

In this paper we study the coordination of Emergency Medical Service (EMS) for patients with acute myocardial infarction with ST-segment elevation (STEMI). This is a health problem with high associated mortality. A "golden standard" treatment for STEMI is angioplasty, which requires a catheterization lab and a highly qualified cardiology team. It should be performed as soon as possible since the delay to treatment worsens the patient's prognosis. The decrease of the delay is achieved by coordination of EMS, which is especially important in the case of multiple simultaneous patients. Nowadays, this process is based on the First-Come-First-Served (FCFS) principle and it heavily depends on human control and phone communication with high proneness to human error and delays. The objective is, therefore, to automate the EMS coordination while minimizing the time from symptom onset to reperfusion and thus to lower the mortality and morbidity resulting from this disease. In this paper, we present a multi-agent decision-support system for the distributed coordination of EMS focusing on urgent out-of-hospital STEMI patients awaiting angioplasty. The system is also applicable to emergency patients of any pathology needing pre-hospital acute medical care and urgent hospital treatment. The assignment of patients to ambulances and angioplasty-enabled hospitals with cardiology teams is performed via a three-level optimization model. At each level, we find a globally efficient solution by a modification of the distributed relaxation method for the assignment problem called the auction algorithm. The efficiency of the proposed model is demonstrated by simulation experiments.

关键词： EMS coordination Ambulance coordination Angioplasty PCI Distributed optimization auction algorithm Emergency medical assistance

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An optimization framework with improved auction-based initialization for highly constrained on-orbit servicing mission planning

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APPLIED SOFT COMPUTING 2023年第PartA期149卷

作者： Xu, Hang Song, Bin Guo, Yanning Liu, Lujiang Li, Xinglong Ma, Guangfu Harbin Inst Technol Harbin 150001 Peoples R China Shanghai Inst Aerosp Syst Engn Shanghai 201109 Peoples R China

The on-orbit servicing (OOS) mission planning problem for multiple geosynchronous earth orbit (GSO) satellites is a critical issue due to its huge economic value. However, given the complexity of the space scenario and the subjective nature of the formulation process, the problem is highly constrained in actual use, and the performance of conventional optimization algorithms decreases due to fuel or mission deadline constraints. With the goal of enhancing solution quality and speeding up the solution process, this paper proposes a novel optimization framework. The problem is decomposed into three sub-problems and then solved using the proposed three-level algorithm to lessen its complexity. In addition, a new initialization method is embedded to improve global search capabilities. Notably, considering the high computation efficiency of the auction algorithm (AA), an improved version is designed to generate primary solutions, which introduces the grouping and reallocation mechanism. Then, several variations of the primary solutions are used as the initial variables in the optimization. Numerical simulations demonstrate that the proposed methodology has higher computational efficiency and convergence performance than conventional strategies.

关键词： Optimization Initialization Geosynchronous satellite Mission planning auction algorithm

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Computationally efficient assignment-based algorithms for data association for tracking with angle-only sensors

Computationally efficient assignment-based algorithms for da...

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19th Conference on Signal and Data Processing of Small Targets

作者： Sathyan, T. Sinha, A. Kirubarajan, T. McMaster Univ Dept Elect & Comp Engn 1280 Main St West Hamilton ON L8S 4K1 Canada

ISBN: (纸本)9780819468475

In this paper we describe computationally efficient assignment-based algorithms to solve the data association problem in synchronous passive multisensor tracking systems. A traditional assignment-based solution to this problem is to solve the measurement-to-measurement association using multidimensional (S-dimensional or S-D with S sensors) assignment formulation and the measurement-to-track association using two-dimensional assignment formulation. Even though this solution has been proven to be effective, it is computationally very expensive. One of the reasons is that in calculating the assignment cost of each possible candidate association one requires to find the maximum likelihood (ML) estimate of the unknown target state. The algorithms proposed in this paper use prior information of the targets that are being tracked to reduce the requirement for the costly ML estimation. The first algorithm is similar to the traditional two step technique except that it uses the predicted track information to avoid building the whole assignment tree in the measurement-to-measurement association. In particular, based on the predicted track information first validation gates are constructed for every target. Then, when forming the assignment tree, only the branches connecting measurements that satisfy the validation gate requirement are constructed. The second algorithm is a one-step algorithm in that it directly assigns the measurements to the tracks. We pose the data association problem as an (S + 1)-D assignment with the first dimension being the predicted state information of the tracks, and the rest of the S dimensions are the lists of measurements from the sensors. The costs of each possible (S + 1)-tuple are calculated based on the predicted track information, hence, the requirement for an ML estimate is eliminated. Further, we show that when the target maneuvers are not very high, and when the sensor measurements are uncorrelated the (S + 1)-D assignment approximately

关键词： multitarget/multisensor tracking data association assignment technique auction algorithm passive sensor tracking

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Fair route guidance: bridging system and user optimization 17

Fair route guidance: bridging system and user optimization

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IEEE 17th International Conference on Intelligent Transportation Systems (ITSC)

作者： Lujak, Marin Giordani, Stefano Ossowski, Sascha Univ King Juan Carlos CETINIA Madrid Spain Univ Roma Tor Vergata Dip Ingn Impresa Rome Italy

ISBN: (纸本)9781479960781

In this paper we study the problem of the assignment of road paths to vehicles. If we assume available the real-time road network information, then (self-concerned) vehicles select paths in a way related to user optimization which results in Wardrop equilibrium. The latter, even though fair for the vehicles of the same Origin-Destination (O-D) pair, in general can be arbitrarily more costly than the system optimum. System optimization, on the other hand, can produce unfair assignments both for the vehicles of the same as of different O-D pairs. To surmount the performance issue of the user-in respect to the system-optimization while considering the fairness issues, we propose a MAS-based distributed optimization model for path assignment to vehicles from the same and different OD pairs at two levels. On the upper level, the proposed model optimizes the overall O-D pairs' Nash Welfare with the fairness related constraints while on the lower level, for every O-D pair separately, paths are assigned to individual vehicles through the auction algorithm. We test the solution approach through simulation, compare it with the conventional user-and systemoptimization, and thus demonstrate that it results in fair and globally efficient path-vehicle assignments.

关键词： optimisation transportation MAS-based distributed optimization model O-D pairs Wardrop equilibrium auction algorithm bridging system fair route guidance origin-destination pair path assignment path-vehicle assignments real-time road network information system optimization user optimization Optimization Real-time systems Resource management Roads Routing Vectors Vehicles

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Implementation of an Assignment algorithm for Object Tracking on a FPGA MPSoC 26

Implementation of an Assignment Algorithm for Object Trackin...

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26th Euromicro Conference on Digital System Design (DSD) / 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Shemonaev, Denis Le Gal, Bertrand Jego, Christophe Besseau, Anthony Univ Bordeaux Bordeaux INP IMS Lab CNRSUMR 5218 Talence France EMG2 Villebon Sur Yvette France

ISBN: (纸本)9798350344196

An assignment algorithm is a key step for multi-object tracking. In order to guarantee real-time execution on embedded systems, it is important to choose an efficient algorithm that matches the application context and the implementation constraints. In this paper, we present a comparative study of different implementations of an auction-based assignment algorithm for asymmetric problems on a System On Module (SOM) target based on an ARM processor and an FPGA circuit. This implementation differs with previous works [1], [2] by the context of multi-object tracking on an embedded system, which implies limited assignment problems, as well as by the choice of a more efficient assignment algorithm. Parallelization strategies were applied to achieve high-efficiency levels for both hardware and software implementations. The experimental results obtained show that, first, software implementation is, in most cases, sufficient to achieve the real-time performances and secondly, that proposed implementations perform better than related work ones (similar to 130x for software and similar to 1.7x for hardware).

关键词： Assignment problem auction algorithm MOT ARM FPGA HLS multicore SIMD

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Joint Passive Beamforming and User Association Optimization for IRS-assisted mmWave Systems

Joint Passive Beamforming and User Association Optimization ...

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IEEE Global Communications Conference (GLOBECOM) on Advanced Technology for 5G Plus

作者： Zhao, Dan Lu, Hancheng Wang, Yazheng Sun, Huan Univ Sci & Technol China Key Lab Wireless Opt Commun Hefei Peoples R China Huawei Technol Co Ltd Wireless Technol Lab Shanghai Peoples R China

ISBN: (纸本)9781728182988

In this paper, we investigate an intelligent reflect surface (IRS) assisted multi-user millimeter wave (mmWave) downlink communication system, exploiting IRS to alleviate the blockage effect and enhance the performance of the mmWave system. Considering the impact of IRS on user association, we formulate a sum rate maximization problem by jointly optimizing the passive beamforming at IRS and user association, which is an intractable non-convex problem. Then an alternating optimization algorithm is proposed to solve the problem efficiently. In the proposed algorithm, passive beamforming at IRS is optimized by utilizing the fractional programming method and user association is solved through the network optimization based auction algorithm. We provide numerical comparisons between the proposed algorithm and different reference algorithms. Simulation results demonstrate that the proposed algorithm can achieve significant gains in the sum rate of all users.

关键词： Millimeter wave intelligent reflect surface user association beamforming auction algorithm

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