• Title/Summary/Keyword: Coverage Optimization

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Optimization of PSG Flowing and Metallization for Step Coverage Improvement (스텝 커버리지를 위한 PSG와 기첩처리 공정 조건의 개선)

  • 김도진;이종덕
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.19 no.6
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    • pp.91-95
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    • 1982
  • One significant problem which arises during the fabrication of LSI and/or VLSI is how to make a good step coverage for aluminum. One way developed in this study is to flow PSG containing 8.0 wt.% - 8.6 wt.% of phosphorus at 95$0^{\circ}C$ for 30 minutes in steam and to depo3it aluminum of 1 urn thickness at $250^{\circ}C$.

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An Optimization Algorithm for the Maximum Lifetime Coverage Problems in Wireless Sensor Network

  • Ahn, Nam-Su;Park, Sung-Soo
    • Management Science and Financial Engineering
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    • v.17 no.2
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    • pp.39-62
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    • 2011
  • In wireless sensor network, since each sensor is equipped with a limited power, efficient use of the energy is important. One possible network management scheme is to cluster the sensors into several sets, so that the sensors in each of the sets can completely perform the monitoring task. Then the sensors in one set become active to perform the monitoring task and the rest of the sensors switch to a sleep state to save energy. Therefore, we rotate the roles of the active set among the sensors to maximize the network lifetime. In this paper, we suggest an optimal algorithm for the maximum lifetime coverage problem which maximizes the network lifetime. For comparison, we implemented both the heuristic proposed earlier and our algorithm, and executed computational experiments. Our algorithm outperformed the heuristic concerning the obtained network lifetimes, and it found the solutions in a reasonable amount of time.

Research on Supervision and its Realization Mechanism in Legal Supervision System (法治监督体系中的监察监督及其实现机制研究)

  • Wang, Jianglian
    • Analyses & Alternatives
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    • v.4 no.1
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    • pp.89-103
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    • 2020
  • The "rule of law" decision of the Fourth Plenary Session of the 18th Central Committee of the Communist Party of China proposes to build a strict supervision system of the rule of law. The reform of the national supervision system launched in 2016 can be described as an important measure to build such a system. The supervision and supervision system has gradually become the core system of the rule of law supervision system. Its full coverage of supervision of public officials is conducive to preventing corruption of public power and achieving the ultimate goal of supervision by the rule of law. The supervision mechanism in the supervision system under the rule of law requires systemic thinking to realize the effective supervision of public officials of the state power organs, as well as the constraints and supervision of other supervision systems, including the supervision of the People's Congress; Supervision is a full-coverage supervision, and other rules of law supervision systems are also full-coverage supervision systems within their scope of competence. Therefore, gradually exploring and constructing an external supervision system for supervision will be conducive to the optimization and eventual completion of the rule of law supervision system.

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Genetic Algorithms for Maximizing the Coverage of Sensor Deployment (최대 커버리지 센서 배치를 위한 유전 알고리즘)

  • Yoon, You-Rim;Kim, Yong-Hyuk
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.3
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    • pp.406-412
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    • 2010
  • In this paper, we formally define the problem of maximizing the coverage of sensor deployment, which is the optimization problem appeared in real-world sensor deployment, and analyze the properties of its solution space. To solve the problem, we proposed novel genetic algorithms, and we could show their superiority through experiments. When applying genetic algorithms to maximum coverage sensor deployment, the most important issue is how we evaluate the given sensor deployment efficiently. We could resolve the difficulty by using Monte Carlo method. By regulating the number of generated samples in the Monte Carlo evaluation of genetic algorithms, we could also reduce the computing time significantly without loss of solution quality.

An efficient multi-objective cuckoo search algorithm for design optimization

  • Kaveh, A.;Bakhshpoori, T.
    • Advances in Computational Design
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    • v.1 no.1
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    • pp.87-103
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    • 2016
  • This paper adopts and investigates the non-dominated sorting approach for extending the single-objective Cuckoo Search (CS) into a multi-objective framework. The proposed approach uses an archive composed of primary and secondary population to select and keep the non-dominated solutions at each generation instead of pairwise analogy used in the original Multi-objective Cuckoo Search (MOCS). Our simulations show that such a low computational complexity approach can enrich CS to incorporate multi-objective needs instead of considering multiple eggs for cuckoos used in the original MOCS. The proposed MOCS is tested on a set of multi-objective optimization problems and two well-studied engineering design optimization problems. Compared to MOCS and some other available multi-objective algorithms such as NSGA-II, our approach is found to be competitive while benefiting simplicity. Moreover, the proposed approach is simpler and is capable of finding a wide spread of solutions with good coverage and convergence to true Pareto optimal fronts.

Discrete bacterial foraging optimization for resource allocation in macrocell-femtocell networks

  • Lalin, Heng;Mustika, I Wayan;Setiawan, Noor Akhmad
    • ETRI Journal
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    • v.40 no.6
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    • pp.726-735
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    • 2018
  • Femtocells are good examples of the ultimate networking technology, offering enhanced indoor coverage and higher data rate. However, the dense deployment of femto base stations (FBSs) and the exploitation of subcarrier reuse between macrocell base stations and FBSs result in significant co-tier and cross-tier interference, thus degrading system performance. Therefore, appropriate resource allocations are required to mitigate the interference. This paper proposes a discrete bacterial foraging optimization (DBFO) algorithm to find the optimal resource allocation in two-tier networks. The simulation results showed that DBFO outperforms the random-resource allocation and discrete particle swarm optimization (DPSO) considering the small number of steps taken by particles and bacteria.

Constrained Relay Node Deployment using an improved multi-objective Artificial Bee Colony in Wireless Sensor Networks

  • Yu, Wenjie;Li, Xunbo;Li, Xiang;Zeng, Zhi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.6
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    • pp.2889-2909
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    • 2017
  • Wireless sensor networks (WSNs) have attracted lots of attention in recent years due to their potential for various applications. In this paper, we seek how to efficiently deploy relay nodes into traditional static WSNs with constrained locations, aiming to satisfy specific requirements of the industry, such as average energy consumption and average network reliability. This constrained relay node deployment problem (CRNDP) is known as NP-hard optimization problem in the literature. We consider addressing this multi-objective (MO) optimization problem with an improved Artificial Bee Colony (ABC) algorithm with a linear local search (MOABCLLS), which is an extension of an improved ABC and applies two strategies of MO optimization. In order to verify the effectiveness of the MOABCLLS, two versions of MO ABC, two additional standard genetic algorithms, NSGA-II and SPEA2, and two different MO trajectory algorithms are included for comparison. We employ these metaheuristics on a test data set obtained from the literature. For an in-depth analysis of the behavior of the MOABCLLS compared to traditional methodologies, a statistical procedure is utilized to analyze the results. After studying the results, it is concluded that constrained relay node deployment using the MOABCLLS outperforms the performance of the other algorithms, based on two MO quality metrics: hypervolume and coverage of two sets.

Constellation Multi-Objective Optimization Design Based on QoS and Network Stability in LEO Satellite Broadband Networks

  • Yan, Dawei;You, Peng;Liu, Cong;Yong, Shaowei;Guan, Dongfang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1260-1283
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    • 2019
  • Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

Fixed Indoor-BS Selection Based Self-Healing in Indoor Wireless Communication System (인도어 무선통신시스템에서 고정적 인도어기지국 선택을 통한 자가치유 알고리즘)

  • Lee, Howon;Lee, Kisong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.7
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    • pp.1540-1546
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    • 2014
  • In order to resolve coverage hole problems caused by indoor-BS (IBS) faults, we propose a new frame structure and practical algorithm based on optimization technique. Our main contributions can be described as follows: 1) a frame structure with healing channels for solving abnormal IBS faults; and 2) an efficient heuristic resource allocation algorithm with fixed IBS selection to reduce the complexity for the optimization problem. Through intensive simulations, we evaluate the performance excellency of our proposed algorithm with respect to average cell capacity and user fairness compared with conventional algorithms.

Low-Complexity Energy Efficient Base Station Cooperation Mechanism in LTE Networks

  • Yu, Peng;Feng, Lei;Li, Zifan;Li, Wenjing;Qiu, Xuesong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.10
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    • pp.3921-3944
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    • 2015
  • Currently Energy-Saving (ES) methods in cellular networks could be improved, as compensation method for irregular Base Station (BS) deployment is not effective, most regional ES algorithm is complex, and performance decline caused by ES action is not evaluated well. To resolve above issues, a low-complexity energy efficient BS cooperation mechanism for Long Time Evolution (LTE) networks is proposed. The mechanism firstly models the ES optimization problem with coverage, resource, power and Quality of Service (QoS) constraints. To resolve the problem with low complexity, it is decomposed into two sub-problems: BS Mode Determination (BMD) problem and User Association Optimization (UAO) problem. To resolve BMD, regional dynamic multi-stage algorithms with BS cooperation pair taking account of load and geographic topology is analyzed. And then a distributed heuristic algorithm guaranteeing user QoS is adopted to resolve UAO. The mechanism is simulated under four LTE scenarios. Comparing to other algorithms, results show that the mechanism can obtain better energy efficiency with acceptable coverage, throughput, and QoS performance.