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Real-Time Schedule of Microgrid for Maximizing Battery Energy Storage Utilization

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2022年第3期13卷 1356-1369页

作者： Xue, Xizhen Ai, Xiaomeng Fang, Jiakun Cui, Shichang Jiang, Yazhou Yao, Wei Chen, Zhe Wen, Jinyu Huazhong Univ Sci & Technol Sch Elect & Elect Engn State Key Lab Adv Electromagnet Engn & Technol Wuhan 430074 Peoples R China Clarkson Univ Dept Elect & Comp Engn Potsdam NY 13676 USA Aalborg Univ Dept Energy Technol DK-9220 Aalborg Denmark

This paper proposes a real-time schedule model of a microgrid (MG) for maximizing battery energy storage (BES) utilization. To this end, a BES life model is linearized using piece-wise linearization and big-M method to assess the BES life loss (BLL) in a real-time manner. The cost-effective schedule model of the MG with multiple energy resources aims to maximize BES utilization while ensuring its sufficient lifespan. Corresponding to the optimization model, approximate dynamic programming (ADP) for maximizing BES utilization (ADP-MBU) in the real-time schedule is proposed to optimize the system under stochastic environments. In ADP-MBU, a new value function approximation method employing the BES cumulative life loss (BCLL) is developed to improve the optimality and applicability. The proposed ADP-MBU algorithm can achieve satisfactory approximate optimality while reflecting the variation of real-time BLL. Case studies validate the applicability of the proposed MG schedule model and the advantages of the proposed ADP-MBU algorithm.

关键词： Schedules Real-time systems Costs Computational modeling Optimization approximation algorithms Wind forecasting Real-time schedule microgrid maximize BES utilization approximate dynamic programming BES cumulative life loss

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Approximating Minimum Manhattan Networks in Higher Dimensions

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ALGORITHMICA 2015年第1期71卷 36-52页

作者： Das, Aparna Gansner, Emden R. Kaufmann, Michael Kobourov, Stephen Spoerhase, Joachim Wolff, Alexander Univ Arizona Dept Comp Sci Tucson AZ 85721 USA AT&T Labs Res Florham Pk NJ USA Univ Tubingen Wilhelm Schickard Inst Informat Tubingen Germany Univ Wurzburg Inst Informat Lehrstuhl 1 Wurzburg Germany

We study the minimum Manhattan network problem, which is defined as follows. Given a set of points called terminals in , find a minimum-length network such that each pair of terminals is connected by a set of axis-parallel line segments whose total length is equal to the pair's Manhattan (that is, L (1)-) distance. The problem is NP-hard in 2D and there is no PTAS for 3D (unless ). approximation algorithms are known for 2D, but not for 3D. We present, for any fixed dimension d and any epsilon > 0, an O(n (epsilon) )-approximation algorithm. For 3D, we also give a 4(k-1)-approximation algorithm for the case that the terminals are contained in the union of ka parts per thousand yen2 parallel planes.

关键词： approximation algorithms Computational geometry Minimum Manhattan network

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Efficient Ranking on Entity Graphs with Personalized Relationships

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第4期26卷 850-863页

作者： Hristidis, Vagelis Wu, Yao Raschid, Louiqa Univ Calif Riverside Dept Comp Sci & Engn Riverside CA 92521 USA Microsoft Corp Redmond WA 98052 USA Univ Maryland Robert H Smith Sch Business College Pk MD 20742 USA

Authority flow techniques like PageRank and ObjectRank can provide personalized ranking of typed entity-relationship graphs. There are two main ways to personalize authority flow ranking: Node-based personalization, where authority originates from a set of user-specific nodes;edge-based personalization, where the importance of different edge types is user-specific. We propose the first approach to achieve efficient edge-based personalization using a combination of precomputation and runtime algorithms. In particular, we apply our method to ObjectRank, where a personalized weight assignment vector (WAV) assigns different weights to each edge type or relationship type. Our approach includes a repository of rankings for various WAVs. We consider the following two classes of approximation: (a) SchemaApprox is formulated as a distance minimization problem at the schema level;(b) DataApprox is a distance minimization problem at the data graph level. SchemaApprox is not robust since it does not distinguish between important and trivial edge types based on the edge distribution in the data graph. In contrast, DataApprox has a provable error bound. Both SchemaApprox and DataApprox are expensive so we develop efficient heuristic implementations, ScaleRank and PickOne respectively. Extensive experiments on the DBLP data graph show that ScaleRank provides a fast and accurate personalized authority flow ranking.

关键词： Object search personalization PageRank approximation algorithms

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Testing of clustering (Reprinted from SIAM Journal on Discrete Mathematics, vol 16, pg 393, 2003)

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SIAM REVIEW 2004年第2期46卷 285-308页

作者： Alon, N Dar, S Parnas, M Ron, D Tel Aviv Univ Dept Math Ramat Aviv Israel Acad Coll Tel Aviv Yaffo Dept Comp Sci Ramat Aviv Israel Tel Aviv Univ Dept Elect Engn Ramat Aviv Israel

In this work we study the problem of clustering with respect to the diameter and the radius costs: We say that a set X of points in R-d is (k, b)-clusterable with respect to the diameter cost if X can be partitioned into k subsets (clusters) so that the distance between every pair of points in each cluster is at most b. In the case of the radius cost we require that all points that belong to the same cluster be at a distance of at most b for some common central point. Here we approach the problem of clustering from within the framework of property testing. In property testing, the goal is to determine whether a given object has a particular property or whether it should be modified significantly so that it obtains the property. In the context of clustering, testing takes on the following form: The algorithm is given parameters k, b, beta, and epsilon, and it can sample from the set of points X. The goal of the algorithm is to distinguish between the case when X is (k, b)-clusterable and the case when X is c-far from being (k, (1 + beta)b)-clusterable. By epsilon-far from being (k, (1 + beta)b)-clusterable we mean that more than epsilon . \X\ points should be removed from X so that it becomes (k, (1, + beta)b)-clusterable. In this work we describe and analyze algorithms that use a sample of size polynomial in k and 1/epsilon and independent of \X\. (The dependence on beta and on the dimension, d, of the points varies with the different algorithms.) Such algorithms may be especially useful when the set of points X is very large and it may not even be feasible to observe all of it. Our algorithms can also be used to find approximately good clusterings. Namely, these are clusterings of all but an c-fraction of the points in X that have optimal (or close to optimal) cost. The benefit of our algorithms is that they construct an implicit representation of such clusterings in time independent of \X\. That is, without actually having to partition all points in X, the implici

关键词： property testing clustering randomized algorithms approximation algorithms

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Online EV Scheduling algorithms for Adaptive Charging Networks with Global Peak Constraints

IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING

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IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING 2022年第3期7卷 537-548页

作者： Alinia, Bahram Hajiesmaili, Mohammad H. Lee, Zachary J. Crespi, Noel Mallada, Enrique Telecom SudParis Inst Mines Telecom Dept Networks & Mobile Multimedia Serv RS2M F-91000 Evry France Univ Massachusetts Coll Informat & Comp Sci Amherst MA 01003 USA CALTECH Dept Elect Engn Pasadena CA 91125 USA Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA

This paper tackles online scheduling of electric vehicles (EVs) in an adaptive charging network (ACN) with local and global peak constraints. Given the aggregate charging demand of the EVs and the peak constraints of the ACN, it might be infeasible to fully charge all the EVs according to their charging demand. Two alternatives in such resource-limited scenarios are to maximize the social welfare by partially charging the EVs (fractional model) or selecting a subset of EVs and fully charge them (integral model). The technical challenge is the need for online solution design since in practical scenarios the scheduler has no or limited information of future arrivals in a time-coupled underlying problem. For the fractional model, we devise both offline and online algorithms. We prove that the offline algorithm is optimal. Using competitive ratio as the performance measure, we prove the online algorithm achieves a competitive ratio of 2. The integral model, however, is more challenging since the underlying problem is strongly NP-hard due to 0/1 selection criteria of EVs. Hence, efficient solution design is challenging even in offline setting. For offline setting, we devise a low-complexity primal-dual scheduling algorithm that achieves a bounded approximation ratio. Built upon the offline approximate algorithm, we propose an online algorithm and analyze its competitive ratio in special cases. Extensive trace-driven experimental results show that the performance of the proposed online algorithms is close to the offline optimum, and outperform the existing solutions.

关键词： approximation algorithms Scheduling Electric vehicle charging Scheduling algorithms Adaptive systems Electronic mail Charging stations Electric vehicle online scheduling approximation algorithm competitive analysis

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Path Decomposition under a New Cost Measure with Applications to Optical Network Design

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ACM TRANSACTIONS ON algorithms 2008年第1期4卷 1–20页

作者： Anshelevich, Elliot Zhang, Lisa Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA Bell Labs Murray Hill NJ 07974 USA

We introduce a problem directly inspired by its application to DWDM ( dense wavelength division multiplexing) network design. We are given a set of demands to be carried over a network. Our goal is to choose a route for each demand and to decompose the network into a collection of edge-disjoint simple paths. These paths are called optical line systems. The cost of routing one unit of demand is the number of line systems with which the demand route overlaps;our design objective is to minimize the total cost over all demands. This cost metric is motivated by the need to minimize O-E-O (optical-electrical-optical) conversions in optical transmission. For given line systems, it is easy to find the optimal demand routes. On the other hand, for given demand routes designing the optimal line systems can be NP-hard. We first present a 2-approximation for general network topologies. As optical networks often have low node degrees, we offer an algorithm that finds the optimal solution for the special case in which the node degree is at most 3. Our solution is based on a local greedy approach. If neither demand routes nor line systems are fixed, the situation becomes much harder. Even for a restricted scenario on a 3-regular Hamiltonian network, no efficient algorithm can guarantee a constant approximation better than 2. For general topologies, we offer a simple algorithm with an O(logK)- and an O(logn)-approximation, where K is the number of demands and n the number of nodes. This approximation ratio is almost tight. For rings, a common special topology, we offer a more complex 3/2-approximation algorithm.

关键词： Optical network design path decomposition approximation algorithms

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Fair Beam Allocations Through Reconfigurable Intelligent Surfaces

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2024年第11期42卷 3095-3109页

作者： Xiong, Rujing Yin, Ke Mi, Tiebin Lu, Jialong Wan, Kai Qiu, Robert Caiming Huazhong Univ Sci & Technol Sch Elect Informat & Commun Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Ctr Math Sci Wuhan 430074 Peoples R China

A fair beam allocation framework through reconfigurable intelligent surfaces (RISs) is proposed, incorporating the Max-min criterion. This framework focuses on designing explicit beamforming functionalities through optimization. Firstly, realistic models, grounded in geometrical optics, are introduced to characterize the input/output behaviors of RISs, effectively bridging the gap between the requirements on explicit beamforming operations and their practical implementations. Then, a highly efficient algorithm is developed for Max-min optimizations involving quadratic forms. Leveraging the Moreau-Yosida approximation, we successfully reformulate the original problem and propose an iterative algorithm to obtain the optimal solution. A comprehensive analysis of the algorithm's convergence is provided. Importantly, this approach exhibits excellent extensibility, making it readily applicable to address a broader class of Max-min optimization problems. Finally, numerical and prototype experiments are conducted to validate the effectiveness of the framework. With the proposed beam allocation framework and algorithm, we clarify that several crucial redistribution functionalities of RISs, such as explicit beam-splitting, fair beam allocation, and wide-beam generation, can be effectively implemented. These explicit beamforming functionalities have not been thoroughly examined previously.

关键词： Array signal processing Resource management Minimax techniques Optimization approximation algorithms Antenna arrays Reconfigurable intelligent surfaces Reconfigurable intelligent surface (RIS) fair beam allocation beam-splitting wide-beam generation max-min optimization Moreau-Yosida approximation prototype experiment

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Strong minimum energy hierarchical topology in wireless sensor networks

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2016年第1期32卷 174-187页

作者： Panda, B. S. Shetty, D. Pushparaj Indian Inst Technol Delhi Dept Math Comp Sci & Applicat Grp Hauz Khas New Delhi 110016 India

Given a set of sensors, the strong minimum energy topology (SMET) problem in a wireless sensor network is to assign transmit powers to all sensors such that (i) the graph induced only using the bi-directional links is connected, that is, there is a path between every pair of sensors, and (ii) the sum of the transmit powers of all the sensors is minimum. This problem is known to be NP-hard. In this paper, we study a special case of the SMET problem, namely , the -strong minimum energy hierarchical topology (-SMEHT) problem. Given a set of sensors and an integer , the -SMEHT problem is to assign transmission powers to all sensors such that (i) the graph induced using only bi-directional links is connected, (ii) at most nodes of the graph induced using only bi-directional links have two or more neighbors, that is they are non-pendant nodes, and (iii) the sum of the transmit powers of all the sensors in is minimum. We show that -SMEHT problem is NP-hard for arbitrary . However, we propose a -approximation algorithm for -SMEHT problem, when is a fixed constant. Finally, we propose a polynomial time algorithm for the -SMEHT problem for .

关键词： Sensor networks Topology control problem Graph algorithms NP-complete approximation algorithms

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Task Scheduling With UAV-Assisted Vehicular Cloud for Road Detection in Highway Scenario

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IEEE INTERNET OF THINGS JOURNAL 2020年第8期7卷 7702-7713页

作者： Li, Jiangfan Cao, Xiaofeng Guo, Deke Xie, Junjie Chen, Honghui Natl Univ Def Technol Sci & Technol Informat Syst Engn Lab Changsha 410073 Peoples R China Tianjin Univ Coll Intelligence & Comp Tianjin 300350 Peoples R China

Vehicular cloud computing (VCC) has been utilized to enhance traffic management and road safety. By connecting with base stations (BSes), VCC can provide the information of real-time dynamics for smart vehicles (SVs). However, the area outside the coverage of BSes will be the blind areas, where SVs cannot obtain the real-time safety guarantee, especially on the highway. In this article, we utilize unmanned aerial vehicles (UAVs) to assist the communication between SVs and BSes to solve the above problem. In particular, we study the interdependency task scheduling for the highway driving environment detection, where SVs, BSes, and UAVs collect the environmental data, schedule tasks, and feedback results cooperatively. There are two main problems in this scenario: 1) the scheduling within the coverage of BSes and 2) the rescheduling between the coverage of BSes. We model both the processes as constrained numerical optimization problems aiming to minimize the request-response time. To this end, we propose a systematical scheduling scheme named Teso, which consists of two stages: 1) designed approximation algorithm for scheduling and 2) offloading algorithm for rescheduling. Extensive experiments show that Teso can significantly reduce the response time overall and improve the system stability.

关键词： Task analysis Monitoring Roads Scheduling Real-time systems approximation algorithms Edge computing road detection vehicular cloud computing~(VCC)

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Energy-Efficient Communication in Multi-interface Wireless Networks

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THEORY OF COMPUTING SYSTEMS 2013年第2期52卷 285-296页

作者： Athanassopoulos, Stavros Caragiannis, Ioannis Kaklamanis, Christos Papaioannou, Evi Univ Patras Comp Technol Inst Rion 26500 Greece Univ Patras Dept Comp Engn & Informat Rion 26500 Greece

We study communication problems in wireless networks supporting multiple interfaces. In such networks, two nodes can communicate if they are close enough and share a common interface. The activation of each interface has a cost reflecting the energy consumed when a node uses this interface. We distinguish between the homogeneous and heterogeneous case, depending on whether all nodes have the same activation cost for each interface or not. For the homogeneous case, we present a (3/2 + epsilon)-approximation algorithm for the problem of achieving connectivity with minimum activation cost, improving a previous bound of 2. For the heterogeneous case, we show that the connectivity problem is not approximable within a sublogarithmic factor in the number of nodes and present a logarithmic approximation algorithm for a more general problem that models group communication.

关键词： Wireless networks Energy-efficiency approximation algorithms

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