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Rate Adaptation Technique for Media Streaming Over QUIC With Limited Backhaul

IEEE ACCESS 2024年 12卷 139028-139041页

作者： Dwijaksara, Made Harta Hilman, Muhammad Hafizhuddin Lee, Chankyun Lee, Wonhyuk Univ Indonesia Fac Comp Sci Comp Syst Lab CSL Kota Depok 16425 West Java Indonesia Korea Inst Sci & Technol Informat Quantum Network Res Ctr Daejeon 34141 South Korea

The rapid proliferation of mobile devices has caused a significant surge in Internet traffic, mainly due to video streaming services, which account for up to 65% of the total volume. As a primary contributor to Internet traffic, video streaming services must use bandwidth efficiently to avoid overwhelming networks with unnecessary traffic. It is not trivial for media streaming services to utilize bandwidth efficiently while achieving scalability and interactivity. Media over QUIC (MoQ) is a promising new standard for realizing both scalable and interactive streaming services. However, due to its infancy, the selection of a proper bit rate for each video segment to be transmitted (also known as rate adaptation) in MoQ has yet to be explored. Inappropriate video bit rate selection can lead to a deterioration of the user's quality of experience (QoE) and inefficient bandwidth utilization. Furthermore, the rate adaptation problem becomes more complex due to the limitation of backhaul bandwidth. The rate adaptation technique should consider the client parameters (i.e., client bandwidth) and backhaul bandwidth usage known only to the server (server parameters). This paper proposes the rate adaptation technique designed for MoQ that considers both the client and server parameters. We have implemented the proposed scheme and evaluated its performance under realistic scenarios. Our experimental results reveal that the proposed technique has a 70% lower packet delay rate and a 10% higher bandwidth utilization compared to the IFA-based, RENO-based, and DASH-Google. These results demonstrate the novelty and the benefits of the proposed scheme.

关键词： Streaming media Bandwidth Servers Bit rate Backhaul networks Real-time systems Quality of experience mixed integer linear programming Bit rate adaptation media streaming QUIC dynamic adaptive streaming over HTTP (DASH) limited backhaul mixed integer linear programming (MILP)

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Dynamic flow control model and algorithm for metro network under FIFO condition

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2024年 190卷

作者： Zhang, Ping Wu, Jianjun Wang, Kai Qu, Yunchao Long, Jiancheng Beijing Jiaotong Univ Sch Syst Sci Beijing 100044 Peoples R China Dalian Univ Technol Sch Econ & Management Dalian 116024 Peoples R China Tsinghua Univ Sch Vehicle & Mobil Beijing 100084 Peoples R China Hefei Univ Technol Sch Automot & Transportat Engn Hefei 230009 Peoples R China

Implementing passenger flow control strategies is an effective approach to reducing commuter travel delays and ensuring crowd safety in a congested metro network. Due to the intricacy of the interweaving of passenger flows between various lines and stations, the development of a scientific passenger flow control strategy is challenging in the networked mode of operation. The first-in-first-out (FIFO) rule can ensure service fairness and optimal operation by accurate modeling passenger queuing dynamics, but it is rarely considered in existing studies. Inspired by the traditional dynamic traffic assignment models, we propose a novel passenger flow control model with the FIFO rule to find a more reasonable control strategy for a metro network. Unlike road traffic systems, the FIFO rule is formulated as a set of linear constraints to explicitly capture the passenger queuing properties at origin stations. The passenger flow control problem with the FIFO rule is then modeled as a mixed integer linear programming model, which can significantly reduce the model complexity. To reach a high-quality solution, we propose an efficient rolling horizon decomposition approach. In the algorithm, the planning horizon is rolled forward from the current time, and the effects of subsequent periods are considered at each iteration. Besides, a dynamic procedure for loading passengers is developed to evaluate the bounds between the proposed approach and other flow control strategies. The proposed model and algorithm are then applied to solve the problems in test and real metro networks. The numerical results demonstrate the validity of the model's properties and the algorithm's performance.

关键词： Metro network oversaturation Passenger flow control mixed integer linear programming Decomposition heuristic

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Integrated maintenance and production scheduling for unrelated parallel machines with setup times

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FLEXIBLE SERVICES AND MANUFACTURING JOURNAL 2024年第3期36卷 1046-1079页

作者： Geurtsen, Michael Adan, Jelle Akcay, Alp Eindhoven Univ Technol Sch Ind Engn De Zaale NL-5600 MB Eindhoven Netherlands Nexperia Jonkerbosplein 52 NL-6534 AB Nijmegen Netherlands

This paper considers jointly scheduling the production and resource-constrained maintenance activities in a manufacturing setting with unrelated parallel machines. In particular, a single maintenance activity needs to be scheduled on each machine in one of its available time windows, and the maintenance activities require a scarce resource, thereby limiting the number of maintenance activities that can be scheduled simultaneously on different machines. In addition, machine- and sequence-dependent setup times, machine eligibility constraints and job-specific release and due dates are considered. A mixed-integer linear program is formulated with objectives including the makespan and, motivated from practice, a weighted sum of total production completion times at machines and total job tardiness. Additionally, a hybrid genetic algorithm with a novel solution representation is proposed for solving industry-scale large instances. A case study is performed with real-world data from a semiconductor manufacturer, where production and maintenance are scheduled separately. The benefit of simultaneously scheduling production and maintenance is investigated. Tests with real-world data show that the proposed model results in schedules that substantially improve the current factory practice.

关键词： Production scheduling Parallel machines Integrated planning Setup times mixed integer linear programming Hybrid genetic algorithm

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Optimal hydrogen infrastructure planning for heat decarbonisation

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2024年 204卷 121-136页

作者： Efthymiadou, Margarita E. Charitopoulos, Vassilis M. Papageorgiou, Lazaros G. Univ Coll London UCL Sargent Ctr Proc Syst Engn Dept Chem Engn Torrington Pl London WC1E 7JE England

Energy decarbonisation is essential to achieve Net -Zero emissions goal by 2050. Consequently, investments in alternative low-carbon pathways and energy carriers for the heat sector are required. In this study, we propose an optimisation framework for the transition of heat sector in Great Britain focusing on hydrogen infrastructure decisions. A spatially-explicit mixed-integer linear programming (MILP) evolution model is developed to minimise the total system's cost considering investment and operational decisions. The optimisation framework incorporates both long-term planning horizon of 5-year steps from 2035 to 2050 and typical days with hourly resolution. Aiming to alleviate the computational effort of such multiscale model, two hierarchical solution approaches are suggested that result in computational time reduction. From the optimisation results, it is shown that the installation of gas reforming hydrogen production technologies with CCS and biomass gasification with CCS can provide a cost-effective strategy achieving decarbonisation goal. What-if analysis is conducted to demonstrate further insights for future hydrogen infrastructure investments. Results indicate that, as cost is highly dependent on natural gas price, Water Electrolysis capacity increases significantly when gas price rises. Moreover, the introduction of carbon tax policy can lead to lower CO2 net emissions.

关键词： Energy systems modelling Hydrogen infrastructure mixed integer linear programming What-if analysis Heat decarbonisation Net-Zero

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Multi-Period Power System Risk Minimization Under Wildfire Disruptions

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IEEE TRANSACTIONS ON POWER SYSTEMS 2024年第5期39卷 6305-6318页

作者： Yang, Hanbin Rhodes, Noah Yang, Haoxiang Roald, Line Ntaimo, Lewis Chinese Univ Hong Kong Shenzhen Sch Data Sci Shenzhen 518172 Peoples R China Univ Wisconsin Madison Elect & Comp Engn Madison WI 53706 USA Texas A&M Univ Ind & Syst Engn College Stn TX 77843 USA

Natural wildfire becomes increasingly frequent as climate change evolves, posing a growing threat to power systems, while grid failures simultaneously fuel the most destructive wildfires. Preemptive de-energization of grid equipment is effective in mitigating grid-induced wildfires but may cause significant power outages during natural wildfires. This paper proposes a novel two-stage stochastic program for planning preemptive de-energization and solves it via an enhanced Lagrangian cut decomposition algorithm. We model wildfire events as stochastic disruptions with random magnitude and timing. The stochastic program maximizes the electricity delivered while proactively de-energizing components over multiple time periods to reduce wildfire risks. We use a cellular automaton process to sample grid failure and wildfire scenarios driven by realistic risk and environmental factors. We test our method on an augmented version of the RTS-GLMC test case in Southern California and compare it with four benchmark cases, including deterministic, wait-and-see, and robust optimization formulations as well as a comparison with prior wildfire risk optimization. Our method reduces wildfire damage costs and load-shedding losses, and our nominal plan is robust against uncertainty perturbation.

关键词： Wildfires Climate change Lagrangian functions mixed integer linear programming Risk management Stochastic processes Power system reliability Decomposition algorithm de-energization Lagrangian cut optimal power flow stochastic mixed-integer programming wildfire risk

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A 0-1 linear relaxation and stochastic approximation method for real-time pricing in a smart grid with non-convex constraints

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ENGINEERING OPTIMIZATION 2024年第12期56卷 2131-2147页

作者： Tao, Li Wang, Zongyao Su, Xia Huaiyin Inst Technol Fac Math & Phys Huaian Peoples R China

In this article, real-time pricing (RTP) for a smart grid with complicated non-convex and/or non-smooth constraints is explored. First, piecewise linear functions are adopted to approximate any kinds of utility function and RTP is formulated into bilevel non-convex programming. Then, a 0-1 relaxation method is used to linearize sparse constraints and piecewise linear utility functions, to obtain mixed integer linear programming. Finally, a distributed simultaneous perturbation stochastic approximation (DSPSA) method is designed to solve the bilevel non-convex programming. The RTP strategy is generalizable because sparse constraints and non-differentiable and/or non-concave utility functions are widespread in practice, and the piecewise linear functions approximation method is applicable to all kinds of utility function, not just to non-smooth and/or non-concave utility functions. In addition, the 0-1 linear relaxation and stochastic approximation method make the bilevel non-convex programming easily solvable by DSPSA, which converges rapidly while maintaining the high accuracy of solutions.

关键词： Smart grid real-time pricing 0-1 relaxation method mixed integer linear programming distributed simultaneous perturbation stochastic approximation

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A novel model for transfer synchronization in transit networks and a Lagrangian-based heuristic solution method

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2024年第1期317卷 76-91页

作者： Ansarilari, Zahra Bodur, Merve Shalaby, Amer Univ Toronto Dept Civil & Mineral Engn Toronto ON Canada Univ Edinburgh Sch Math Edinburgh Scotland

To realize the benefits of network connectivity in transfer -based transit networks, it is critical to minimize transfer disutility for passengers by synchronizing timetables of intersecting routes. We propose a mixedinteger linear programming timetable synchronization model that incorporates new features, such as dwell time determination and vehicle capacity consideration, which have been largely overlooked in the literature at the scheduling stage. We introduce a new concept of pre -planned holding time, called transfer buffer time, to reduce the transfer waiting time, particularly for transfers to low -frequency routes, while taking into account the penalty of extra in -vehicle time for onboard passengers and the possible consequences on headway regularity of a route. We develop a Lagrangian relaxation -based heuristic to obtain high -quality solutions efficiently for large instances. Our experiments on instances with up to 12 transfer nodes in the City of Toronto, with a mixture of low- and high -frequency routes, illustrate the potential benefits of the proposed model over the state of the art. The results indicate that incorporating transfer buffer time, dwell time determination, and vehicle capacity consideration improves model outcomes considerably, also demonstrating the computational efficiency of our Lagrangian-based solution method.

关键词： Transfer synchronization Bus dwell time determination Vehicle capacity mixed integer linear programming Lagrangian relaxation

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Ego-Network Segmentation via (Weighted) Jaccard Median

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2024年第9期36卷 4646-4663页

作者： Zhong, Haodi Loukides, Grigorios Conte, Alessio Pissis, Solon P. Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China Kings Coll London London WC2R2LS England Univ Pisa I-6126 Pisa Italy CWI NL-1098XG Amsterdam Netherlands Vrije Univ NL-1081HV Amsterdam Netherlands

An ego-network is a graph representing the interactions of a node (ego) with its neighbors and the interactions among those neighbors. A sequence of ego-networks having the same ego can thus model the evolution of these interactions over time. We introduce the problem of segmenting a sequence of ego-networks into k segments. Each segment is represented by a summary network, and the goal is to minimize the total loss of representing k segments by k summaries. The main challenge is to construct a summary with minimum loss. To address it, we employ the Jaccard Median (JM) problem, for which, however, no effective and efficient algorithms are known. We develop several algorithms for JM: (I) an exact algorithm, based on mixed integer linear programming;(II) exact and approximation polynomial-time algorithms for minimizing an upper bound of the objective function of JM;and (III) efficient heuristics. We also study a generalization of the segmentation problem, in which there may be multiple edges between a pair of nodes in an ego-network, and develop a series of algorithms (exact algorithms and heuristics) for it, based on a more general problem than JM, called Weighted Jaccard Median (WJM). By building upon the above results, we design algorithms for segmenting a sequence of ego-networks. Extensive experiments show that our algorithms produce (near)-optimal solutions to JM or to WJM and that they substantially outperform state-of-the-art methods which can be employed for ego-network segmentation.

关键词： Approximation algorithms Heuristic algorithms Social networking (online) Upper bound mixed integer linear programming linear programming Synthetic data Ego-network jaccard median segmentation

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Use statistical analysis to approximate integrated order batching problem

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2024年第12期62卷 4349-4371页

作者： Xue, Sen Gao, Chuanhou Zhejiang Univ Sch Math Sci Hangzhou Peoples R China

This paper highlights the tight relationship between the picking and packing processes in warehouse management and the need to consider them as an integrated problem. The study describes and models this integrated problem as a mixed-integer programming model, to optimise overall labour costs by determining the assignment of the subsets of orders, i.e. batches, for picking and packing. To address the issue of model complexity, the paper presents a statistical-based framework for generating approximate models and selecting the optimal one through examination. Based on the examination results, a pair-swapping heuristic is additionally proposed to be combined as a hybrid algorithm. Numerical experiments based on a real-world case demonstrate the effectiveness of the framework-proposed and selected hybrid algorithm by comparison with other framework-proposed approximate models, a solver, and existing heuristics. Our findings indicate that the combined usage of integrated picking and packing processes planning and the hybrid algorithm proposed and selected within the statistical-based framework can effectively reduce the cost of warehouse management.

关键词： Logistics warehouse order batching mixed integer linear programming Monte Carlo method statistical methods

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Digital Twin-Driven Dynamic Scheduling of Flexible Manufacturing System in the Context of Smart Factory Producing Brass Accessories

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JOURNAL OF INDUSTRIAL INTEGRATION AND MANAGEMENT-INNOVATION AND ENTREPRENEURSHIP 2025年第1期10卷 67-107页

作者： Chakroun, Ayoub Hani, Yasmina Elmhamedi, Abderrahmane Masmoudi, Faouzi Univ Paris VIII Vincennes Univ Inst Technol Lab QUARTZ EA 7393 FR-93100 Montreuil France Univ Sfax Natl Sch Engineers Sfax Lab LA2MP Route Soukra Sfax 3038 Tunisia

This study aims to deal with a dynamic scheduling problem of a real Flow Shop follow-up of an assembly process considering the specific constraints and requirements of a brass accessories manufacturing (BAM) company. We basically set up a Digital Twin-driven dynamic scheduling approach for Industry 4.0 by addressing uncertainties of machine availability. In fact, the setup of this Digital Twin (DT) is the outcome of the combination of both optimization and simulation. For the first step, we have elaborated a mixed integer linear programming (MILP) scheduling model by taking into account the dedicated requisites of our case study. Concerning simulation, a 3D simulation platform of a workshop producing brass accessories controlled by a Cyber-Physical Production System (CPPS) has been developed, in our previous work, including constraints and stochastic aspects. The simulation constraints are difficult or impossible to be modeled in the MILP model. These designs are integrated with the real workshop to construct the Digital Twin. The proposed tool enables the rescheduling of production orders based on machine disturbances and unpredictability. Validation scenarios have been designed and conducted to highlight the efficacy of the Digital Twin approach utilizing the brass accessories case study. We are confident that this represents the initial endeavor addressing the optimization of production rescheduling in a flow shop follow-up of a mixed assembly system.

关键词： Dynamic scheduling flow shop assembly process digital twin Industry 4.0 flexibility machines availability mixed integer linear programming

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