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Automation of Millimeter Wave Network Planning for Outdoor coverage in Dense Urban Areas Using Wall-Mounted Base Stations

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IEEE WIRELESS COMMUNICATIONS LETTERS 2017年第2期6卷 206-209页

作者： Palizban, Nima Szyszkowicz, Sebastian Yanikomeroglu, Halim Carleton Univ Dept Syst & Comp Engn Ottawa ON K1S 5B6 Canada

The millimeter wave (mmWave) spectrum is an important candidate band for next-generation cellular networks. Using higher frequencies, mmWaves are much more sensitive to blockage, and the presence of line-of-sight links is more desired, making the network planning more dependent on the layout of the cities. In this letter, we use computational geometry and optimization tools to fully automate the process of planning an outdoor mmWave network in dense cities, using wall-mounted below-rooftop base stations (BSs). Based on the locations found, one can analyze some properties of mmWave networks. We provide information about the BS density and coverage in two different large urban areas.

关键词： Network planning mmWave base station density 5G maximum coverage problem

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Mining the Most Influential k-Location Set from Massive Trajectories

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IEEE TRANSACTIONS ON BIG DATA 2018年第4期4卷 556-570页

作者： Li, Yuhong Bao, Jie Li, Yanhua Wu, Yingcai Gong, Zhiguo Zheng, Yu Univ Macau Dept Comp & Informat Sci Macau Peoples R China Microsoft Res Beijing 100080 Peoples R China Xidian Univ Sch Comp Sci & Technol Xian Shi 710126 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Beijing 100864 Peoples R China Worcester Polytech Inst Comp Sci Dept Worcester MA 01609 USA Zhejiang Univ State Key Lab CAD&CG Hangzhou 310027 Zhejiang Peoples R China

Mining the most influential location set finds k locations, traversed by the maximum number of unique trajectories, in a given spatial region. These influential locations are valuable for resource allocation applications, such as selecting charging stations for electric automobiles and suggesting locations for placing billboards. This problem is NP-hard and usually calls for an interactive mining processes involving a user's input, e.g., changing the spatial region and k, or removing some locations (from the results in the previous round) that are not eligible for an application according to the domain knowledge. Efficiency is the major concern in conducting this human-in-the-loop mining. To this end, we propose a complete mining framework, which includes an optimal method for the light setting (i.e., small region and k) and an approximate method for the heavy setting (i.e., large region and k). The optimal method leverages vertex grouping and best-first pruning techniques to expedite the mining process. The approximate method can provide the performance guarantee by utilizing the greedy heuristic, and it is comprised of efficient updating strategy, index partition and workload-based optimization techniques. We evaluate the efficiency and effectiveness of our methods based on two taxi datasets from China, and one check-in dataset from New York.

关键词： Location selection most influential k-location set maximum coverage problem trajectory data mining

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Hybrid Data Selection With Context and Content Features for Visual Crowdsensing

IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY

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IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY 2022年 3卷 426-440页

作者： Song, Wei Univ New Brunswick Fac Comp Sci Fredericton NB E3B 5A3 Canada

Visual crowdsensing (VCS) is becoming predominant in mobile crowdsensing, but there still exist various unique challenges, including large sizes of visual data, multidimensional requirements, and intensive processing demands. As a key research problem in VCS, data selection filters out redundant data and only retains most representative samples, which can effectively reduce the complexity and cost for VCS. In this paper, we study a phase-by-phase data selection approach, in which metadata are first used to pre-select collected photos and then only selected ones are sent to a backend server for further processing based on content features. As such, the initial selection can be completed on nearby edge servers in mobile edge computing (MEC), while more intensive content processing can be done in a remote cloud. We evaluate different initial data selection algorithms using traditional performance measures as well as adapted clustering indices as quality metrics. Moreover, we formulate an integer linear program (ILP) problem for the final data selection based on the scale-invariant feature transform (SIFT) feature. This content-based selection can complement the initial data selection based on contextual metadata. The simulation results show the differences of these selection algorithms and provide guidance on how to choose an appropriate one according to application needs.

关键词： Visualization Metadata Feature extraction Crowdsensing Servers Task analysis Costs Mobile crowdsensing visual crowdsensing edge computing data selection hierarchical clustering maximum coverage problem

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A Rank-Predicted Pseudo-Greedy Approach to Efficient Text Selection From Large-Scale Corpus For maximum coverage of Target Units

A Rank-Predicted Pseudo-Greedy Approach to Efficient Text Se...

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9th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2008)

作者： Li, Wei Huo, Qiang Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China Microsoft Res Asia Beijing Peoples R China

ISBN: (纸本)9781615673780

Selecting efficiently a minimum amount of text from a large-scale text corpus to achieve a maximum coverage of certain units is an important problem in spoken language processing area. In this paper, the above text selection problem is first formulated as a maximum coverage problem with a Knapsack constraint (MCK). An efficient rank-predicted pseudo-greedy approach is then proposed to solve this problem. Experiments on a Chinese text selection task are conducted to verify the efficiency of the proposed approach. Experimental results show that our approach can improve significantly the text selection speed yet without sacrificing the coverage score compared with traditional greedy approach.

关键词： text selection greedy approach pseudo-greedy approach maximum coverage problem

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A GIS-based Optimal Facility Location Framework for Fast Electric Vehicle Charging Stations 30

A GIS-based Optimal Facility Location Framework for Fast Ele...

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30th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Zafar, Usman Bayram, I. Safak Bayhan, Sertac Hamad Bin Khalifa Univ Qatar Environm & Energy Res Inst POB 34110 Doha Qatar Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XQ Lanark Scotland

ISBN: (数字)9781728190235

ISBN: (纸本)9781728190235

Deeper decarbonization of the transport sector requires building a wide coverage electric vehicle charging network that can meet driver's mobility patterns and refueling habits in a seamless manner. Currently, major market players mainly deploy chargers at existing public parking spaces at hotels, shopping centers, etc. On the other hand, gas/petroleum retail business is a century-old industry and "optimized" to serve the refueling needs of the drivers and they come to the forefront as "good" locations to site chargers. To that end, this paper addresses the fast charging station location problem in an urban environment. The optimization problem is formulated as a maximum coverage location problem (MCLP) and existing locations of petrol/fuel stations are considered as candidate locations. Using QGIS software, a geographic information system (GIS) based platform is developed and integrated with a linear-programming relaxation based MCLP algorithm developed in Python. The city of Raleigh, North Carolina with actual geo-spatial data is chosen as a case study. Both census population and highway traffic data are considered as demand metrics to mimic drivers without dedicated chargers and vehicles on highways who need a recharge. A number of evaluations are performed to explore the trade-off between the number of locations and the physical coverage space. Furthermore, comparative analysis show that locating fast chargers in existing petrol stations improve demand coverage by more than 50% when compared to existing fast charging station locations.

关键词： electric vehicles petrol stations facility location fast chargers maximum coverage problem

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The k-allocation problem and its variants

The <i>k</i>-allocation problem and its variants

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4th International Workshop on Approximation and Online Algorithms

作者： Hochbaum, Dorit S. Levin, Asaf Univ Calif Berkeley Dept Ind Engn & Operat Res Berkeley CA 94720 USA Univ Calif Berkeley Sch Business Berkeley CA 94720 USA Hebrew Univ Jerusalem Dept Stat Jerusalem Israel

ISBN: (纸本)9783540695134

In the process of reviewing and ranking projects by a group of reviewers, each reviewer is assumed to review a partial list of projects, up to k projects. Each individual reviewer then ranks and compares all pairs of k projects. The k-allocation problem is to determine the allocation of up to k projects to each reviewer within the expertise set of the reviewer so that the resulting union of reviewed projects has certain desirable properties. One property of the k-allocation is to have all pairs of projects compared by at least one reviewer. This we call the k-complete problem. In cases when the property of k-complete cannot be achieved, one might settle for other properties. One such basic requirement is that each pair of projects is comparable via a ranking path which is a sequence of pairwise rankings of projects implying a comparison of all pairs on the path. A k-allocation with a ranking path between each pair is the connectivity-k-aloc. Since the robustness of relative comparisons deteriorates with the length of the ranking path, another property is that between each pair of projects there will be at least one ranking path that has at most two hops or q hops for fixed values of q. Another property that increases robustness of the ranking is to find a k-allocation so there are at least p disjoint ranking paths between each pair. We model all these problems as graph problems and show that the CONNECTIVITY-k-ALOC problem is polynomially solvable using matroid intersection, the k-complete problem is NP-hard unless k = 2, and all other considered variants of the k-allocation properties problem are NP-complete for all values of k >= 2. We provide approximation algorithms for an optimization problem related to the k-complete problem.

关键词： approximation algorithms allocation problem maximum coverage problem

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The maximum Visibility Facility Selection Query in Spatial Databases 19

The Maximum Visibility Facility Selection Query in Spatial D...

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27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS)

作者： Rabban, Ishat E. Ali, Mohammed E. Cheema, Muhammad A. Hashem, Tanzima BUET Dhaka 1000 Bangladesh Monash Univ Clayton Vic Australia

ISBN: (纸本)9781450369091

Given a set of obstacles in 2D or 3D space, a set of n candidate locations where facilities can be established, the maximum Visibility Facility Selection (MVFS) query finds k out of the n locations, that yield the maximum visibility coverage of the data space. Though the MVFS problem has been extensively studied in visual sensor networks, computational geometry, and computer vision in the form of optimal camera placement problem, existing solutions are designed for discretized space and only work for MVFS instances having a few hundred facilities. In this paper, we revisit the MVFS problem to support new spatial database applications like "where to place security cameras to ensure better surveillance of a building complex?" or "where to place billboards in the city to maximize visibility from the surrounding space?". We introduce the concept of equivisibility triangulation to devise the first approach to accurately determine the visibility coverage of continuous data space from a subset of the facility locations, which avoids the limitations of discretizing the data space. Then, we propose an efficient graph-theoretic approach that exploits the idea of vertex separators for efficient exact in-memory solution of the MVFS problem. Finally, we propose the first external-memory based approximation algorithm (with a guaranteed approximation ratio of 1 - 1/e) that is scalable for a large number of obstacles and facility locations. We conduct extensive experimental study to show the effectiveness and efficiency of our proposed algorithms.

关键词： Visibility maximum coverage problem Triangulation Graph Partitioning Greedy Approximation

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Sequential Pattern Mining for ICT Risk Assessment and Prevention 15th

Sequential Pattern Mining for ICT Risk Assessment and Preven...

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15th International Conference on Software Engineering and Formal Methods (SEFM)

作者： D'Andreagiovanni, Michele Baiardi, Fabrizio Lipilini, Jacopo Ruggieri, Salvatore Tonelli, Federico Univ Pisa Dipartimento Informat Largo B Pontecorvo 3 I-56127 Pisa Italy

ISBN: (纸本)9783319747811;9783319747804

Security risk assessment and prevention in ICT systems rely on the analysis of data on the joint behavior of the system and its (malicious) users. The Haruspex tool models intelligent, goal-oriented agents that reach their goals through attack sequences. Data is synthetically generated through a Monte Carlo method that runs multiple simulations of the attacks against the system. In this paper, we present a sequential pattern mining analysis of the database of attack sequences. The intended objective is twofold: (1) to exploit the extracted patterns for the design of attack counter-measures, and (2) for gaining a better understanding of the "degree of freedom" available for the attackers of a system. We formally motivate the need for using maximal sequential patterns, instead of frequent or closed sequential patterns, and report on the results on a specific case study.

关键词： Security risk assessment Attack sequences Sequential pattern mining maximum coverage problem

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Simulation-Based maximum coverage Hazard Detection and Elimination Analysis, Supporting Combinational Logic Loops 30

Simulation-Based Maximum Coverage Hazard Detection and Elimi...

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30th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC)

作者： Chatzivangelis, Nikolaos Valiantzas, Dimitris Sotiriou, Christos Lilitsis, Iordanis Univ Thessaly Dept Elect & Comp Engn Volos Greece

ISBN: (数字)9781665490054

ISBN: (纸本)9781665490054

We demonstrate an iterative simulation-based maximum coverage detection and elimination analysis of logic-hazards for combinational logic loops. Although the focus is on asynchronous circuits with such feedbacks, it is apparent that the proposed approach can be practiced for every digital circuit with combinational loops. In regard to hazard detection, a simulation-based semi-modular analysis is presented, by extending the provided library technology behavioral Verilog files. For hazard elimination, only the standard cells within the paths causing a hazard have been included for analysis. The circuit becomes hazard-free by inserting buffers of the minimum required delay. We develop three path-based buffer insertion approaches;the more advanced ones model each logic gate and their relative timing constraints as a maximum set covering problem. The main characteristic of comparison is the count of inserted buffers and their total delay. The aforementioned hazard analysis is an iterative process, because the overall timing constraints of the circuit alter after each delay insertion. Experimental results indicate that the three hazard elimination approaches have various area penalties and their success rate ranges from 68.7% to 100%. Moreover, not all hazards can be resolved, mainly due to opposing constraints of sensitized hazard paths, and Boolean logic re-synthesis may be required.

关键词： combinational logic circuits asynchronous circuits logic hazards semi-modular maximum coverage problem

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A Distributed Cloud Service For The Resolution of SAT 7

A Distributed Cloud Service For The Resolution of SAT

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IEEE 7th International Symposium on Cloud and Service Computing (IEEE SC2)

作者： Ngoko, Yanik Trystram, Denis Cerin, Christophe Qarnot Comp Paris France Univ Paris 13 Paris France Univ Grenoble Alpes Grenoble France

ISBN: (纸本)9781538658628

In this paper, we introduce a new parallel and distributed algorithm for the resolution of the satisfiability problem. The proposed algorithm is based on algorithm portfolio and is intended to be used for servicing requests in a distributed cloud. The core of our contribution is the modeling of the optimal resource sharing schedule in parallel executions and the proposition of heuristics for its approximation. For this purpose, we reformulate a computational problem introduced in prior work. The main assumption is that it is possible to learn the optimal resource sharing from traces collected on past executions on a representative set of instances. We show that the learning can be formalized as a set coverage problem. Then, we propose to solve it by approximation and dynamic programming algorithms. These algorithms are based on classical greedy algorithms for the maximum coverage problem. Finally, we conduct an experimental evaluation for comparing the performance of the various proposed algorithms. The results show that some algorithms become more competitive if we intend to determine the trade-off between their quality and the runtime required for their computation.

关键词： Large scale cloud applications Resource provisioning and scheduling parallel distributed SAT algorithm portfolio maximum coverage problem

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