• Title/Summary/Keyword: resource optimization

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Task Scheduling and Resource Management Strategy for Edge Cloud Computing Using Improved Genetic Algorithm

  • Xiuye Yin;Liyong Chen
    • Journal of Information Processing Systems
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    • 제19권4호
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    • pp.450-464
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    • 2023
  • To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

전산유체해석을 이용한 다양한 요철 형상에 대한 고압터빈 노즐 냉각유로 최적화 및 냉각 성능 비교 (DESIGN OPTIMIZATION AND PERFORMANCE ANALYSIS OF INTERNAL COOLING PASSAGE WITH VARIOUS TYPE OF RIB TURBULATOR FOR HIGH PRESSURE TURBINE NOZZLE)

  • 이상아;이동호;강영석;이관중;김규홍
    • 한국전산유체공학회지
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    • 제19권4호
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    • pp.14-19
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    • 2014
  • This study conducts shape optimization of rib turbulator on the internal cooling passage that has triangular cross-section of high pressure turbine nozzle. During optimization, various types of rib turbulator including angled, V-shaped, A-shaped and angled rib with intersecting rib are considered. Each type of rib turbulator is parameterized with attack angle(s), rib height, spacing ratio and bending/intersecting location. For optimization, Design of Experiment (DOE) and Kriging surrogate model are used to utilize computational resource more efficiently and Genetic Algorithm (GA) is used to search the optimum points. As a result, Pareto front of each type of rib turbulator with friction factor that relates to pressure drop in cooling passage and spatially averaged Nusselt number that relates to heat transfer on the wall is drawn and optimum points on the Pareto front are suggested.

A Holistic Approach to Optimizing the Lifetime of IEEE 802.15.4/ZigBee Networks with a Deterministic Guarantee of Real-Time Flows

  • Kim, Kang-Wook;Park, Myung-Gon;Han, Junghee;Lee, Chang-Gun
    • Journal of Computing Science and Engineering
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    • 제9권2호
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    • pp.83-97
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    • 2015
  • IEEE 802.15.4 is a global standard designed for emerging applications in low-rate wireless personal area networks (LR-WPANs). The standard provides beneficial features, such as a beacon-enabled mode and guaranteed time slots for realtime data delivery. However, how to optimally operate those features is still an open issue. For the optimal operation of the features, this paper proposes a holistic optimization method that jointly optimizes three cross-related problems: cluster-tree construction, nodes' power configuration, and duty-cycle scheduling. Our holistic optimization method provides a solution for those problems so that all the real-time packets can be delivered within their deadlines in the most energy-efficient way. Our simulation study shows that compared to existing methods, our holistic optimization can guarantee the on-time delivery of all real-time packets while significantly saving energy, consequently, significantly increasing the lifetime of the network. Furthermore, we show that our holistic optimization can be extended to take advantage of the spatial reuse of a radio frequency resource among long distance nodes and, hence, significantly increase the entire network capacity.

A Framework for Universal Cross Layer Networks

  • Khalid, Murad;Sankar, Ravi;Joo, Young-Hoon;Ra, In-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제8권4호
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    • pp.239-247
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    • 2008
  • In a resource-limited wireless communication environment, various approaches to meet the ever growing application requirements in an efficient and transparent manner, are being researched and developed. Amongst many approaches, cross layer technique is by far one of the significant contributions that has undoubtedly revolutionized the way conventional layered architecture is perceived. In this paper, we propose a Universal Cross Layer Framework based on vertical layer architecture. The primary contribution of this paper is the functional architecture of the vertical layer which is primarily responsible for cross layer interaction management and optimization. The second contribution is the use of optimization cycle that comprises awareness parameters collection, mapping, classification and the analysis phases. The third contribution of the paper is the decomposition of the parameters into local and global network perspective for opportunistic optimization. Finally, we have shown through simulations how parameters' variations can represent local and global views of the network and how we can set local and global thresholds to perform opportunistic optimization.

A Comprehensive Cash Management Model for Construction Projects Using Ant Colony Optimization

  • Mohamed Abdel-Raheem;Maged E. Georgy;Moheeb Ibrahim
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.243-251
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    • 2013
  • Cash management is a major concern for all contractors in the construction industry. It is arguable that cash is the most critical resource of all. A contractor needs to secure sufficient funds to navigate the project to the end, while keeping an eye on maximizing profits along the way. Past research attempted to address such topic via developing models to tackle the time-cost tradeoff problem, cash flow forecasting, and cash flow management. Yet, little was done to integrate the three aspects of cash management together. This paper, as such, presents a comprehensive model that integrates the time-cost tradeoff problem, cash flow management, and cash flow forecasting. First, the model determines the project optimal completion time by considering the different alternative construction methods available for executing project activities. Second, it investigates different funding alternatives and proposes a project-level cash management plan. Two funding alternatives are considered; they are borrowing and company own financing. The model was built as a combinatorial optimization model that utilizes ant colony search capabilities. The model also utilizes Microsoft Project software and spreadsheets to maintain an environment that incorporates activities, their durations, and other project data, in order to estimate project completion time and cost. Ant Colony Optimization algorithm was coded as a Macro program using VBA. Finally, an example project was used to test the developed model, where it acted reliably in maximizing the contractor's profit in the test project.

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A Novel Technique for Tuning PI-Controllers in Induction Motor Drive Systems for Electric Vehicle Applications

  • Elwer Ayman Saber
    • Journal of Power Electronics
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    • 제6권4호
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    • pp.322-329
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    • 2006
  • In the last decade, the increasing restrictions imposed on the exhaust emissions from internal combustion engines and traffic limitations have increased the development of electrical propulsion systems for automotive applications. The goal of electrical and hybrid vehicles is the reduction of global emissions, which in turn leads to a decrease in fuel resource exploitation. This paper presents a novel approach for control of Induction Motors (IM) using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the Proportional Integral Controller (PI-Controller). The overall system is simulated under various operating conditions. The use of PSO as an optimization algorithm makes the drive robust and insensitive to load variation with faster dynamic response and higher accuracy. The system is tested under variable operating conditions. The simulation results show a positive dynamic response with fast recovery time.

Route Optimization Scheme for Mobile Content Sources in Content Centric Networking

  • Lee, Jihoon;Rhee, Eugene
    • Journal of information and communication convergence engineering
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    • 제18권1호
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    • pp.22-27
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    • 2020
  • Content centric networking (CCN) is regarded as promising internet architecture because it can provide network efficiency in terms of bandwidth consumption by separating contents from a specific network location and decrease network congestion events. However, the application of a CCN does not widely consider the side effects of mobile devices, particularly mobile content sources. For content source mobility, a full routing update is required. Therefore, in this study, a route optimization scheme is proposed for mobile content sources in a CCN environment to provide low communication overhead, short download time, and low resource consumption. The proposed scheme establishes a direct path between content requesters and a mobile content source for the exchange of interest and data packets using interest-piggybacked data packets. Based on the inherent CCN naming characteristics, the content source does not know the name prefix of the content consumer, and thus the proposed optimized CCN scheme utilizes the content router in the home domain of the content source.

LINEAR PROGRAMMING OPTIMIZATION OF NUCLEAR ENERGY STRATEGY WITH SODIUM-COOLED FAST REACTORS

  • Lee, Je-Whan;Jeong, Yong-Hoon;Chang, Yoon-Il;Chang, Soon-Heung
    • Nuclear Engineering and Technology
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    • 제43권4호
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    • pp.383-390
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    • 2011
  • Nuclear power has become an essential part of electricity generation to meet the continuous growth of electricity demand. A Sodium-cooled Fast Reactor (SFR) was developed to extend uranium resource utilization under a growing nuclear energy scenario while concomitantly providing a nuclear waste management solution. Key questions in this scenario are when to introduce SFRs and how many reactors should be introduced. In this study, a methodology using Linear Programming is employed in order to quantify an optimized growth pattern of a nuclear energy system comprising light water reactors and SFRs. The optimization involves tradeoffs between SFR capital cost premiums and the total system U3O8 price premiums. Optimum nuclear growth patterns for several scenarios are presented, as well as sensitivity analyses of important input parameters.