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An Optimal online algorithm for Scheduling on Two Parallel Machines with GoS Eligibility Constraints

Journal of the Operations Research Society of China 2016年第3期4卷 371-377页

作者： Jia Xu Zhao-Hui Liu Department of Mathematics East China University of Science and TechnologyShanghai 200237China

We consider the online scheduling problem on two parallel machines with the Grade of Service(GoS)eligibility *** jobs arrive over time,and the objective is to minimize the *** develop a(1+α)-competitive optimal algor... 详细信息

关键词： Scheduling Parallel machine Eligibility constraint online algorithm

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online algorithm for Wireless Backhaul HetNets with Advanced Small Cell Buffering

Online Algorithm for Wireless Backhaul HetNets with Advanced...

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International Conference on Computer Communication and Networks

作者： Tri Minh Nguyen Wessam Ajib Chadi Assi École de Technologie Supérieure Université du Québec á Montréal Concordia University

In this work, we study a novel model of two-tier wireless backhaul small cell networks that considers buffering of finite storage size at each small cell access point. By employing a reverse time division duplexing (RTDD) interference management, we develop an online algorithm that jointly optimizes the transmit beamforming and power allocation. Unlike previous works, we propose a more advanced buffering protocol to improve the small cell performance by solving an online constrained optimization problem that maximizes both the total small cell access rate and backhaul rate. To deal with the non-convex property of the formulated problem, we invoke the framework of successive convex approximation to develop the online algorithm to iteratively solve a convex approximated problem and update corresponding parameters until convergence. Numerical results show that our proposed model with advanced buffering strategy outperforms the traditional designs in terms of small cell access rate.

关键词： Beamforming buffering online algorithm power allocation heterogeneous networks wireless backhaul

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AN online algorithm FOR THROUGHPUT MAXIMIZATION OFWIRELESS POWERED COMMUNICATION NETWORKS 41

AN ONLINE ALGORITHM FOR THROUGHPUT MAXIMIZATION OFWIRELESS P...

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41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Li, Wei-Chiang Hsieh, Hsin-Shan Chi, Chong-Yung Natl Tsing Hua Univ Inst Commun Engn Hsinchu 30013 Taiwan Natl Tsing Hua Univ Dept Elect Engn Hsinchu 30013 Taiwan

ISBN: (纸本)9781479999880

Optimizing the system performance of a wireless powered communication network (WPCN) has been extensively studied recently, by incorporating space, frequency and/or time diversity of the channel, etc. However, the time diversity, inherently imposes the causality constraint on the channel state information (CSI) in the system design. Hence development of effective and efficient online algorithms for optimizing the system performance is essential but challenging. In this paper, a WPCN with two single-antenna access points (APs) and a single-antenna user, wherein the "harvest and then transmit" over multiple time blocks is considered for the resource allocation (time and power in each time block) by maximizing the system throughput rate. To this end, a low-complexity online algorithm is proposed. Some simulation results are provided to support its efficacy.

关键词： Wireless energy transfer time diversity online algorithm throughput maximization

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Efficient Framework for Real-Time Color Cast Correction and Dehazing Using online algorithms to Approximate Image Statistics

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IEEE ACCESS 2024年 12卷 72813-72827页

作者： Bilal, Muhammad Masud, Shahid Hanif, Muhammad Shehzad King Abdulaziz Univ Ctr Excellence Intelligent Engn Syst Jeddah 21589 Saudi Arabia King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Jeddah 21589 Saudi Arabia Lahore Univ Management Sci Dept Elect Engn Lahore 54792 Pakistan

Image dehazing is a crucial task in the early stages of real-time image processing pipelines used in applications such as surveillance and advance driver assistance systems. Dehazing algorithms mitigate the spatially selective degradation of image details caused by natural phenomenon such as fog and sandstorms. The problem is exacerbated in the presence of color cast which can affect the color-sensitive processing in the downstream tasks. In order to correct these two aberrations, we have proposed a light-weight algorithm which is not only quantitively more effective than the state-of-the-art works but also uses minimal computational resources. Specifically, it has been proposed to tackle both aforementioned problems by processing luminance and chrominance channels separately through a custom resource-efficient colorspace transform. Moreover, it has been proposed to employ online calculation of the relevant video stream statistics to estimate the degradation model over several temporally adjacent frames. This approach not only reduces the hardware resource utilization when implemented inside the video processing pipeline but also reduces the flicker effect observed when frames are processed individually. It has been demonstrated through quantitative analysis on standard datasets that the proposed approach either works at par or better than the reference works in terms of image quality metrics. Furthermore, the proposed framework has been developed as a real-time video processing system on an FPGA platform. The synthesis results of this implementation suggest that the proposed framework achieves this performance using minimal logic resources.

关键词： Image color analysis Real-time systems Hardware Estimation Streaming media Task analysis Approximate computing Field programmable gate arrays Image processing algorithm design and analysis color cast correction dehazing FPGA high-level synthesis online algorithm real-time image processing

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online algorithms for the maximum k-interval coverage problem

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第5期44卷 3364-3404页

作者： Li, Songhua Li, Minming Duan, Lingjie Lee, Victor C. S. City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Singapore Univ Technol & Design Engn Syst & Design Pillar Singapore Singapore Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

We study the online maximum coverage problem on a target interval, in which, given an online sequence of sub-intervals (which may intersect among each other) to arrive, we aim to select at most k of the sub-intervals such that the total covered length of the target interval is maximized. The decision to accept or reject each sub-interval is made immediately and irrevocably right at the release time of the sub-interval. We comprehensively study various settings of this problem regarding both the length of each released sub-interval and the total number of released sub-intervals. To begin with, we investigate the offline version of the problem where the sequence of all the released sub-intervals is known in advance to the decision-maker and propose two polynomial-time optimal solutions to different settings of our offline problem. For the online problem, lower bounds on the competitive ratio are first proposed on our well-designed release schemes of sub-intervals. Then, we propose a Single-threshOld-based deterministic algorithm (SOA), which adds a sub-interval if the added length without overlap exceeds a certain threshold, achieving competitive ratios close to the lower bounds. Further, we extend SOA to a Double-threshOlds-based deterministic algorithm (DOA) by using the first threshold for exploration and the second threshold (larger than the first one) for exploitation. With the two thresholds generated by our proposed program, we show that DOA outperforms SOA slightly in the worst-case scenario. Moreover, we show that more thresholds cannot induce better worst-case performance of an online deterministic algorithm as long as those thresholds are used in non-increasing order in accepting sub-intervals.

关键词： Maximum k-coverage problem online budgeted maximum coverage problem Interval coverage online algorithm

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online Rectangle Packing algorithm for Swapped Battery Charging Dispatch Model Considering Continuous Charging Power

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第1期21卷 320-331页

作者： Bai, Jiawen Ding, Tao Jia, Wenhao Zhu, Shanying Bai, Linquan Li, Fangxing Xi An Jiao Tong Univ Dept Elect Engn Xian 710049 Shaanxi Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Univ North Carolina Charlotte Dept Syst Engn & Engn Charlotte NC 27606 USA Univ Tennessee Knoxville UTK Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

The vigorous development of electric vehicles (EVs) is an important means of reducing carbon emissions and mitigating environmental problems such as the greenhouse effect. Battery swapping stations (BSSs) can both provide battery swapping services for large-scale EVs and charge batteries centrally. As the supply of fully charged batteries in the BSS shrinks, it becomes necessary to schedule the charging of the depleted batteries rapidly that users have swapped for fully-charged ones. The charging schedule for depleted batteries must be made without knowledge of future battery arrivals. In this context, this paper develops a mathematical model for online charging scheduling of BSSs, formulates the charging strategy as a two-dimensional rectangle packing problem, and quickly calculates the scheduling arrangement of batteries by partitioning the remaining available capacity of a BSS. Since there are limited battery types within the BSS which can provide battery replacement services, this paper supplements the proposed model with known battery types, which improves the utilization of the available capacity of BSSs. Finally, numerical results verify the effectiveness of the proposed model. Note to Practitioners-Electric vehicles (EVs) are becoming an alternative way to reduce carbon emissions in transportation systems. Herein, the optimal battery charging problem is the core problem when it comes to dispatching a huge number of EVs. Up to now, battery-swapping is widely used for EVs due to its simple, convenient way. Furthermore, a business model for the battery swapping stations (BSSs) is brought up, where EV users send their depleted batteries to the BSS and the BSS provides the users with a fully charged replacement battery from its warehouse, which only takes a few minutes. Since the maximum charging power of the BSS is limited by the capacity of the transformer connecting the BSS to the power grid, the BSS will adopt an optimal charging schedule that maximizes the c

关键词： Electric vehicles battery swapping station uninterrupted discrete-rate charging rectangle packing problem online algorithm

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Distribution-Oblivious online algorithms for Age-of-Information Penalty Minimization

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IEEE-ACM TRANSACTIONS ON NETWORKING 2023年第4期31卷 1779-1794页

作者： Tsai, Cho-Hsin Wang, Chih-Chun Purdue ECE W Lafayette IN 47907 USA MathWorks Inc Natick MA 01760 USA

The ever-increasing needs of supporting real-time applications have spurred new studies on minimizing Age-of-Information (AoI), a novel metric characterizing the data freshness of the system. This work studies the single-queue information update system and strengthens the seminal results of Sun et al. on the following fronts: (i) When designing the optimal offline schemes with full knowledge of the delay distributions, a new fixed-point-based method is proposed with quadratic convergence rate, an order-of-magnitude improvement over the state-of-the-art;(ii) When the distributional knowledge is unavailable (which is the norm in practice), two new low-complexity online algorithms are proposed, which provably attain the optimal average AoI penalty;and (iii) the online schemes also admit a modular architecture, which allows the designer to upgrade certain components to handle additional practical challenges. Two such upgrades are proposed for the situations: (iii.1) The AoI penalty function is also unknown and must be estimated on the fly, and (iii.2) the unknown delay distribution is Markovian instead of i.i.d. The performance of our schemes is either provably optimal or within 3% of the omniscient optimal offline solutions in all simulation scenarios.

关键词： Age-of-information online algorithm fixed-point equation stochastic approximation algorithm

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online and hard constrained adaptive dynamic programming algorithm for energy storage control in smart buildings

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OPTIMAL CONTROL APPLICATIONS & METHODS 2023年第3期44卷 1074-1091页

作者： Chen, Zitao Chen, Si-zhe Zhang, Yun Deng, Quanbin Zeng, Xianxian Guangdong Univ Technol Sch Automat Guangzhou 510006 Guangdong Peoples R China

The high computational complexity caused by static optimization is the key factor to hinder the development of energy management systems. Adaptive dynamic programming (ADP) is an effective dynamic optimization method to break through the bottleneck. However, the hard constraints of energy system have not been fully considered due to the non-convexity and nonlinearity of the value function, which makes the theoretical analysis complicated and brings safe security problems in battery systems. In this article, a systematic online ADP control framework is proposed for smart buildings control to ensure hard constraints to be satisfied. The second-order local expansion at the current state is used to replace the nonlinear value function to simplify the theoretical analysis with the error of the reminder term. Based on the local property of value function, a method for the determination of adaptive parameters is first designed. It is proven that the solution of adaptive parameters not only prevents over-charged and over-discharged of the battery but also limits the charging and discharging power of the battery to be less than the rated power. In addition, long-short term memory (LSTM) neural networks, a type dynamic network with memory characteristics, are used for the implementation of the present algorithm instead of the static networks to help realize the algorithm online. Due to the hidden state of LSTM, the performance of the online algorithm is improved after running the energy system. Numerical results verify the effectiveness of the proposed online control algorithm.

关键词： adaptive dynamic programming constrained dynamic optimization energy storage control online algorithm smart buildings

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A BEST POSSIBLE algorithm FOR AN online SCHEDULING PROBLEM WITH DETERIORATING EFFECT IN STEEL BOX GIRDER SECTION PRODUCTION

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JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION 2023年第8期19卷 5969-5983页

作者： Yang, Xiaohua Ma, Ran Zhang, Yuzhong Qingdao Univ Technol Sch Management Engn Qingdao 266520 Peoples R China Qufu Normal Univ Inst Operat Res Sch Management Rizhao 276826 Peoples R China

The paper focuses on an online scheduling problem with the effect of deterioration to minimize the maximum delivery time in steel box girder sections. This deterioration is considered in terms of job processing and delivery. Specifically, the processing time of job Jj is defined by an increasing function of its starting time t, i.e., pj = alpha j(A + Bt), where alpha j > 0 is the processing deterioration rate of job Jj. Moreover, the delivery time of job Jj is determined with an increasing function of its completion time, i.e., qj = bjCj, where bj > 0 is the delivery deterioration rate of job Jj. For this problem, we prove the property of optimal scheduling and show that the performance ratio of any deterministic online algorithm is not less than 2+ B alpha max. Furthermore, we provide a best possible online algorithm LDDR with a competitive ratio of 2 + B alpha max. And then a concise computational simulation study is presented to show that our algorithm performs very well in practice.

关键词： Scheduling online algorithm delivery time deteriorating effect sec-tion of steel box girder

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An optimal randomized online algorithm for the -Canadian Traveller Problem on node-disjoint paths

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2015年第1期30卷 87-96页

作者： Bender, Marco Westphal, Stephan Univ Gottingen Inst Numer & Appl Math D-37073 Gottingen Germany

We consider the -Canadian Traveller Problem, which asks for a shortest path between two nodes and in an undirected graph, where up to edges may be blocked. An online algorithm learns about a blocked edge when reaching one of its endpoints. Recently, it has been shown that no randomized online algorithm can be better than -competitive, even if all --paths are node-disjoint. We show that the bound is tight by constructing a randomized online algorithm for this case that achieves the ratio against an oblivious adversary and is therefore best possible.

关键词： Competitive analysis online algorithm Canadian Traveller Problem

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