Dissertations / Theses on the topic 'Load prediction and scheduling'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Load prediction and scheduling.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
Andrews, Matthew. "Scheduling techniques for packet routing, load, balancing and disk scheduling." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/42692.
Full textRadi, Kamal Mohammed A. R. "Scheduling algorithm including load curtailment costs." Thesis, Queen's University Belfast, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335465.
Full textDacre, Marcus James. "Stochastic scheduling in networks." Thesis, University of Newcastle Upon Tyne, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285800.
Full textAntoniadis, Antonios. "Scheduling algorithms for saving energy and balancing load." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16566.
Full textThis thesis studies problems of scheduling tasks in computing environments. We consider both the modern objective function of minimizing energy consumption, and the classical objective of balancing load across machines. We first investigate offline deadline-based scheduling in the setting of a single variable-speed processor that is equipped with a sleep state. The objective is that of minimizing the total energy consumption. Apart from settling the complexity of the problem by showing its NP-hardness, we provide a lower bound of 2 for general convex power functions, and a particular natural class of schedules. We also present an algorithmic framework for designing good approximation algorithms. Furthermore, we give tight bounds for the aforementioned particular class of schedules. We then focus on the multiprocessor setting where each processor has the ability to vary its speed. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time. Regarding the online problem and a natural class of power functions, we extend the two well-known single-processor algorithms Optimal Available and Average Rate. We prove that Optimal Available has the same competitive ratio as in the single-processor case. For Average Rate we show a competitive factor that increases by an additive constant of one compared to the single-processor result. With respect to load balancing, we consider offline load balancing on identical machines, with the objective of minimizing the current load, for temporary unit-weight jobs. The problem can be seen as coloring n intervals with k colors, such that for each point on the line, the maximal difference between the number of intervals of any two colors is minimal. We prove that a coloring with maximal difference at most one is always possible, and develop a fast polynomial-time algorithm for generating such a coloring. Lastly, we prove that two generalizations of the problem are NP-hard.
Piccinini, Federico. "Dynamic load balancing based on latency prediction." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-143333.
Full textMurphy, Patrick F. R. "Load-haul-dump vehicle component life prediction using experimentally acquired load histories." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2002. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ65641.pdf.
Full textDogan, Osman Tufan. "A Stochastic Approach For Load Scheduling Of Cogeneration Plants." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/2/12611698/index.pdf.
Full textheat to power ratio&rsquo
. This ratio determines the operating conditions of the plant. However, this ratio may vary in order to adapt to the physical and economical changes in power and to the meteorological conditions. Employing reliable optimization models to enhance short term scheduling capabilities for cogeneration systems is an important research area. The optimal load plan is targeted by achieving maximum revenue for cogeneration plants. Revenue is defined for the purpose of the study as the sales revenues minus total cost associated with the plant operation. The optimization problem, which aims to maximize the revenue, is modeled by thermodynamic analyses. In this context, the study introduces two objective functions: energy based optimization, exergy-costing based optimization. A new method of stochastic programming is developed. This method combines dynamic programming and genetic algorithm techniques in order to improve computational efficiency. Probability density function estimation method is introduced to determine probability density functions of heat demand and electricity price for each time interval in the planning horizon. A neural network model is developed for this purpose to obtain the probabilistic data for effective representation of the random variables. In this study, thermal design optimization for cogeneration plants is also investigated with particular focus on the heat storage volume.
Rosas, Ham Demian. "Dynamic scheduling in multicore processors." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/dynamic-scheduling-in-multicore-processors(c96d6641-ba16-44d2-9da5-34c41fd15956).html.
Full textBahadornejad, Momen. "On-line local load measurement based voltage instability prediction." Thesis, Queensland University of Technology, 2005. https://eprints.qut.edu.au/16187/1/Momen_Bahadornejad_Thesis.pdf.
Full textBahadornejad, Momen. "On-line local load measurement based voltage instability prediction." Queensland University of Technology, 2005. http://eprints.qut.edu.au/16187/.
Full textGraue, Ryan M. (Ryan Matthew). "Prediction and optimization techniques to streamline surgical scheduling." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82482.
Full textThis electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from department-submitted PDF version of thesis
Includes bibliographical references (p. 72-76).
Abstract We have created a set of decision support tools to streamline the surgical case scheduling process by allowing surgical wait list cases (elective cases that cannot be assigned a slot on the operating room schedule at the time of booking) to be confirmed onto the operating room schedule up to three weeks in advance of the day of surgery. Prior to our research, wait list cases could not be confirmed more than a few days prior to the desired day of surgery due to uncertainty about available time prior to the release of dedicated OR capacity. Earlier confirmation of wait list cases serves three purposes: (1) to improve patients' ability to plan logistics to prepare for their visits, (2) to reduce wait list case backlogs for surgeons' offices, and (3) to reduce variability in the total daily caseload through proactive decision making. Our contributions assist scheduling personnel in confirming wait list case dates sooner to help medical institutions achieve these benefits. We have developed two Excel-based pieces of software: a prediction tool and a schedule optimization tool. The prediction tool predicts time that is available each day between one and three weeks in advance to accommodate wait list cases, and the schedule optimization tool automates the consolidation process for all cases that are currently booked on a future date so that rooms and equipment are used as efficiently as possible. Our platform lets users interact with simple GUIs in which they make selections to generate prediction results and optimized daily case schedules. Specifically, our prediction algorithm employs a multiple linear regression model over historical data to forecast unused time, and the optimization tool uses a mixed integer linear program to optimize the daily schedule by consolidating cases into a minimum number of rooms and closing any gaps between cases, subject to constraints that are specific to the facility and the date in question. We have achieved our desired outcome of maximizing operating room resource utilization by giving human schedulers a set of tools to use on a daily basis that simplifies the scheduling process and confirms wait list cases with more advance notice. This system is generalizable to other areas within healthcare delivery environments and any other industry where tasks are scheduled in advance into a fixed set of resources with a record of historical demand over time.
by Ryan M. Graue.
S.M.
M.B.A.
Senniappan, Karthikeyan Yildirim Mehmet Bayram. "Parallel-machine scheduling with load-balancing and sequence-dependent setups." Diss., A link to full text of this thesis in SOAR, 2006. http://soar.wichita.edu/dspace/handle/10057/679.
Full text"December 2006." Title from PDF title page (viewed on Sept. 18, 2007). Thesis adviser: Mehmet Bayram Yildirim. Includes bibliographic references (leaves 53-57).
Saranyan, N. "Prediction based load balancing heuristic for a heterogeneous cluster." Thesis, Indian Institute of Science, 2003. http://hdl.handle.net/2005/95.
Full textMolloy, Susan. "Ship powering prediction using load varying self-propulsion tests." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ62403.pdf.
Full textLeen, Sean B. "Elastic-plastic generalised load-displacement prediction for tubular joints." Thesis, University of Nottingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.287266.
Full textDunn, Michael S. "Asymmetric Non-Uniform Proportional Share Scheduling." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1282313314.
Full textThiam, Cheikhou. "Anti load-balancing for energy-aware distributed scheduling of virtual machines." Toulouse 3, 2014. http://thesesups.ups-tlse.fr/2441/.
Full textThe multiplication of Cloud computing has resulted in the establishment of largescale data centers around the world containing thousands of compute nodes. However, Cloud consume huge amounts of energy. Energy consumption of data centers worldwide is estimated at more than 1. 5% of the global electricity use and is expected to grow further. A problem usually studied in distributed systems is to evenly distribute the load. But when the goal is to reduce energy consumption, this type of algorithms can lead to have machines largely under-loaded and therefore consuming energy unnecessarily. This thesis presents novel techniques, algorithms, and software for distributed dynamic consolidation of Virtual Machines (VMs) in Cloud. The main objective of this thesis is to provide energy-aware scheduling strategies in cloud computing for energy saving. To achieve this goal, we use centralized and decentralized approaches. Contributions in this method are presented these two axes. The objective of our approach is to reduce data center's total energy consumed by controlling cloud applications' overall energy consumption while ensuring cloud applications' service level agreement. Energy consumption is reduced by dynamically deactivating and reactivating physical nodes to meet the current resource demand. The key contributions are: - First, we present an energy aware clouds scheduling using anti-load balancing algorithm : concentrate the load on a minimum number of severs. The goal is to turn off the machines released and therefore minimize the energy consumption of the system. - The second axis proposed an algorithm which works by associating a credit value with each node. The credit of a node depends on its affinity to its jobs, its current workload and its communication behavior. Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual network topologies established between VMs, and thermal state of computing nodes. The experiment results, obtained with a simulator which extends CloudSim (EnerSim), show that the cloud application energy consumption and energy efficiency are being improved. - The third axis is dedicated to the consideration of a decentralized dynamic scheduling approach entitled Cooperative scheduling Anti-load balancing Algorithm for cloud. It is a decentralized approach that allows cooperation between different sites. To validate this algorithm, we have extended the simulator MaGateSim. With an extensive experimental evaluation with a real workload dataset, we got the conclusion that both the approach using centralized and decentralized algorithms can reduce energy consumed by data centers
Joshi, Avinash. "Load Balancing, Queueing and Scheduling Mechanisms in Mobile Ad Hoc Networks." University of Cincinnati / OhioLINK, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1004447615.
Full textYusof, Norzan Mohd. "Environmental load versus concrete quality : prediction of structure's design life." Thesis, University of Birmingham, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323997.
Full textXie, Ningbo. "NDT-based performance prediction for wrinkled composites under compressive load." Thesis, University of Bristol, 2018. http://hdl.handle.net/1983/919cd8f3-463f-4618-b794-ede41a5b92ad.
Full textChan, Sonya. "The use of EMG for load prediction during manual lifting." Thesis, Kingston, Ont. : [s.n.], 2007. http://hdl.handle.net/1974/871.
Full textBai, Mo, and Mahabaleshwar Sagar Parampalli. "Accelerated Engine Suspension Load Prediction and Exhaust System Displacement Simulation." Thesis, KTH, Maskinkonstruktion (Inst.), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218029.
Full textI dagens konkurrensutsatta bilindustri försöker de flesta företag att göra sina nya mönster och funktioner implementerbara i sina produkter för att vara före sina konkurrenter. I det preliminära konstruktionsstadiet av CEVT-fordon förbrukar dynamisk simulering dock en stor tid beroende på komplexiteten hos den dynamiska modellen och simuleringsinställningarna. Det är fördelaktigt och möjligt att förkorta simuleringstiden. Denna avhandling fokuserar på att minska den dynamiska simuleringstiden i ADAMS / Car i motorupphängningens tidiga utvecklingsstadium. Med hjälp av bakgrundsstudier och erfarenheter från CEVT’s personal provades fem olika sätt att minska simuleringstiden, samtidigt som simuleringsresultatens noggrannhet kontrollerades. Varje metod användes separat i simuleringen för att studera effekten på resultatens noggrannhet. I slutet kombineras alla metoder i simuleringen för att få bästa möjliga simuleringstid utan att förlora noggrannhet. Genom att kombinera de fem metoderna reducerades den totala dynamiska simuleringstiden till 61% och variationen i utmattningsskadans resultat av varje motorupphängningskomponent kontrollerades inom 30%. Dynamisk modellering av ett avgassystem ingår också i denna avhandling, vilket ger referensdata för framtida förpackningsdesign av avgassysteme
Jensen, Taylor (Taylor Moroni), and Qi Sun. "Absenteeism prediction and labor force optimization in rail dispatcher scheduling." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/85457.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 61-62).
Unplanned employee absences are estimated to account for a loss of 3% of scheduled labor hours. This can be costly in railroad dispatcher scheduling because every absence must be filled through overtime or a qualified extra dispatcher. One factor that complicates this problem is the uncertainty of unplanned employee absences. The ability to predict unplanned absences would facilitate effective scheduling of extra dispatchers and help reduce overtime costs. This thesis uses data from a railroad company over a four year period to examine company-wide factors thought to impact the number of unplanned absences among dispatchers. Using Poisson regression, we identify several factors that provide statistical evidence of influencing the number of unplanned absences. These factors are month, snowstorms, shift, and certain holidays. Despite these findings, the overall predictive capability of our regression model is very weak. Instead, we model the number of unplanned absences by shift as a Hadrom process with a Negative Binomial distribution and use Monte Carlo simulation to explore the impact on overtime costs of increasing the number of scheduled extra dispatchers and increasing the number of positions on which each employee is qualified to work. Our results show that increasing the number of extra dispatchers has a greater effect on reducing overtime, but the cost savings from reducing overtime expenses are not enough to offset the additional labor costs of having more employees on staff. Our results provide insight regarding the relationship among extra staff, higher levels of qualification among employees, and the willingness to use overtime in handling unplanned absences.
by Taylor Jensen and Qi Sun.
M. Eng. in Logistics
Xu, Yizheng. "Probabilistic estimation and prediction of the dynamic response of the demand at bulk supply points." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/probabilistic-estimation-and-prediction-of-the-dynamic-response-of-the-demand-at-bulk-supply-points(b9e427ec-7e5e-49a5-aec4-0f34032d71a9).html.
Full textBischof, Stefan. "Efficient algorithms for on-line scheduling and load distribution in parallel systems." [S.l. : s.n.], 1999. http://deposit.ddb.de/cgi-bin/dokserv?idn=959771409.
Full textHaukedal, Eirik Daleng. "Load-scheduling and Plug-in Hybrid Electric Vehicles in the Smart Grid." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18624.
Full textALWAN, HAYDER O. "Load Scheduling with Maximum Demand and Time of Use pricing for Microgrids." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5954.
Full textAlkharboush, Raed. "Improved Prediction-based Dynamic Load Balancing Systems for HLA-Based Distributed Simulations." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32162.
Full textBlagojevic, Filip. "Scheduling on Asymmetric Architectures." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/27952.
Full textPh. D.
Dhandayuthapani, Sumithra. "Automatic selection of dynamic loop scheduling algorithms for load balancing using reinforcement learning." Master's thesis, Mississippi State : Mississippi State University, 2004. http://library.msstate.edu/etd/show.asp?etd=etd-06292004-144402.
Full textEhlers, George E. "Hi-fidelity simulation and prediction of helicopter single point external load stabilization." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2001. http://handle.dtic.mil/100.2/ADA397012.
Full textThesis advisor: Woods, E. Robert. "September 2001." Includes bibliographical references (p. 43-45). Also Available online.
Aliamiri, Sara. "Prediction of premature failure load in FRP or steel plated RC beams." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13631.
Full textBozokalfa, Gökhan Akkurt Sedat. ""Ann" artifical neural networks and fuzzy logic models for cooling load prediction/." [s.l.]: [s.n.], 2005. http://library.iyte.edu.tr/tezlerengelli/master/makinamuh/T000372.pdf.
Full textKeywords: Artificial neural networks, fuzzy logic, modeling, cooling load, prediction. Includes bibliographical references (leaves. 44-45).
Bean, Brennan L. "Interval-Valued Kriging Models with Applications in Design Ground Snow Load Prediction." DigitalCommons@USU, 2019. https://digitalcommons.usu.edu/etd/7579.
Full textBo-TingChen and 陳柏廷. "Prediction and Optimal Scheduling of Shedding Air Conditioning Load for Demand Response." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/93pf9z.
Full text國立成功大學
電機工程學系
106
In order to relieve urgent need of new power plants as well as the pressure of power shortage, Taipower has promoted demand response (DR) program and biding options to consolidate demand side load management. This study evaluates the benefit for NCKU EE to partici-pate in the DR program. The proposed methodology uses historical power consumption, temperature, and humidity statistics as training data to develop a general regression neural network (GRNN) model, so that it can predict the power consumption of the NCKU EE building after shedding its indi-vidual air conditioning (A/C) loads. The predicted power consumption after shedding air conditioning load is further used as input for the genetic algorithm to come up with optimal commitment of A/C load shedding. The proposed strategy was applied in June 2018 to check the benefit of joining the DR program.
Badenhorst, Werner. "Optimal control on rock winder hoist scheduling." Diss., 2010. http://hdl.handle.net/2263/28001.
Full textDissertation (MEng)--University of Pretoria, 2010.
Electrical, Electronic and Computer Engineering
Unrestricted
Chen, Niangjun. "Model Predictive Control for Deferrable Loads Scheduling." Thesis, 2014. https://thesis.library.caltech.edu/8468/1/master_thesis.pdf.
Full textReal-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.
In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.
Sou-Jen, Lai, and 賴守仁. "Speculative Load/Store Scheduling for X86." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/10264470881287369734.
Full text國立交通大學
資訊工程系
87
The design of Load/Store Units in existed superscalar microarchitectures is always restricted on the conservative scheduling of load/store operations. True data dependency of a load operation is checked before issuing to the data cache. Only load bypassing or forwarding is provided in the scheduling policy of the load/store units. However, the instruction level parallelism is still limited by true data dependencies seriously. Thus, various speculation methods have been proposed to increase the execution performance of load/store operations. The speculative scheduling proposed in this thesis not only predicts data dependencies of load operations, but also predicts the possibilities of data forwarding and data addresses of load operations. Thus, a load can speculatively bypass stores or be speculatively forwarded data directly from the store that might be depended upon before the address generation and true data dependency checking. Our model speculatively executes load operations much earlier than the proposed methods of data dependency speculation under precise prediction. Finally, the selective design is proposed to reduce mis-speculations.
FU, CHUN-KUEI, and 傅俊貴. "Investigation of direct load control scheduling." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/93253919498978836970.
Full textHwang, Hui-yue, and 黃慧瑜. "An X86 Load/store Unit with Aggressive Scheduling of Load/store Operations." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/53375158433004818687.
Full text國立交通大學
資訊工程學系
86
Superscalar microarchitecture is broadly used in the modern microprocessors to execute multiple instructions in parallel. Because of limited register set and register-memory instruction set architecture, there are significant amounts of memory access instructions in x86 microprocessors. To explore more ILP of memory access operations becomes an important issue for the design of x86 microprocessors. The design of load/store units in the existed superscalar microprocessors is always restricted on the conservative scheduling of load/store operations. True data dependency is checked before issuing to the data cache. Only load bypassing or forwarding is provided in the scheduling policy of the load/store units. As higher degrees of instruction issuing are provided, more aggressive scheduling policies for load/store operations are required. In this thesis, the proposed speculation model, which allows load operations to precede the previous unsolved pending store operations, has the best performance gain in comparison with in-order, load bypassing and forwarding models. And, the additional traffic to the datacache caused by the true data dependency is always below 5.5%. The speculation model enlarges the execution window of load/store operations and gains the profit as the window size grows. In addition, the pipeline stages of the speculation model can be further reduced to gain more performance improvement.
Lin, Chiao-Win, and 林巧雲. "Dynamic Load Route Scheduling Problem in Tandem AGVS." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/15065740760101931382.
Full textSimon, Michał. "Fault tolerant data acquisition through dynamic load scheduling." Rozprawa doktorska, 2013. https://repolis.bg.polsl.pl/dlibra/docmetadata?showContent=true&id=21532.
Full textSimon, Michał. "Fault tolerant data acquisition through dynamic load scheduling." Rozprawa doktorska, 2013. https://delibra.bg.polsl.pl/dlibra/docmetadata?showContent=true&id=21532.
Full textErasmus, Dawid J. "Load scheduling with cogeneration and real time pricing." Diss., 2000. http://hdl.handle.net/2263/30443.
Full textDissertation (M Eng (Electrical Engineering))--University of Pretoria, 2006.
Electrical, Electronic and Computer Engineering
unrestricted
Maharaj, Yajna. "Modelling electricity load scheduling and retailer decision-making." Diss., 2016. http://hdl.handle.net/2263/57491.
Full textDissertation (MEng)--University of Pretoria, 2016.
tm2016
Industrial and Systems Engineering
MEng
Unrestricted
Wang, Ming-jun, and 王銘君. "Parallel Turning Machine Scheduling with Limited Power Load." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/02975429293028069508.
Full text逢甲大學
工業工程與系統管理學系
101
Power has become indispensable part of modern life in 21st century, and overuse of energy often results in severe climate change and environmental pollution. In classical production scheduling problems for parallel machines, jobs are known and unchanged. However, energy issues are seldom considered for such the problems in most of the literatures. In this study, selection of proper machining parameters under an electrical load constrained in a shop floor is addressed for the parallel machine scheduling problem. The objective of the scheduling problem is to minimize makespan. A simple heuristic is proposed to determine the proper machining parameter for each turning operation. After setting the machining parameters for all the jobs, the processing times are then constant, a genetic algorithm (GA)-based approach is developed for solving this parallel machine scheduling problem.
Arif, Hamdani, and Hamdani Arif. "Load balanced Energy Efficient Scheduling in Cloud Computing." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/7tp9t3.
Full text長庚大學
資訊工程學系
104
Acquiring fast processing time for some specific tasks will most likely satisfy the users. In response, cloud providers need to accommodate it by provisioning efficient tasks allocation policy. On the other hand, cloud computing platform allows the providers to manage their physical resources smartly in order to save the power consumption for their own merit. This paper addresses a trade-off mechanism between the cloud providers to achieve their own objectives and the users to obtain the quality of service evenly. Hence, a virtual and physical machine load balancing scheme is proposed to satisfy both user and service provider sides.
Chen, Yueh Ren, and 陳躍仁. "Prediction-Based Load Balancing in Heterogeneous Environment." Thesis, 1995. http://ndltd.ncl.edu.tw/handle/13541281458387784872.
Full text國立中山大學
資訊工程研究所
83
In heterogeneous distributed environment, load balancing is very important for overall system performance improvement. But load balancing is not a easy work. So in this thesis, we will use benchmark to normalize the difference between the systems and establish a prediction system to forecast the future load variation by some techniques like linear regression and pattern composition. This system will help users to decide the best host to execute their programs for the maximum utilization of all system resources. And it is hard to write distributed applications in heterogeneous environment, too. For this reason, we provide a transparency tool --- modified PVM, which scheduler has been improved by our prediction system to automatically balance the system load for more efficient system performance.
Hung, Yu-Hsin, and 洪鈺欣. "Load Prediction and Contract Capacity Optimization Research." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/84796303164980464046.
Full text國立臺灣大學
工程科學及海洋工程學研究所
99
In Taiwan, most industrial and commercial enterprises sign power contracts with Taiwan Power Company. Problems occur when deciding the capacity in contracts: the high power capacity leads to increase of total electronic consuming cost. However, if the power capacity is set low, consumers run the risk of high penalty when the actual consumption exceed. The aim of this thesis is to optimize power demand for Taiwanese industries through the model of forecast and optimization. This thesis presents a new combination method by using particle swarm optimization (PSO) to forecast the load capacity, and control uncertainty of forecasting with stochastic simulation. Then optimize the capacity of contract with the improved particle swarm optimization by query based learning (QBLPSO) [1] algorithm. There are two main purposes in this thesis. First, the proposed method will be compared with the other methods, and we analyze separately the forecast and optimization. Second, we make decision analysis framework for determining the optimal power contract capacity and an empirical study in real cases, which included the industry, the commerce. The load forecast has about 90% of accuracy in government units, 92% of accuracy in commerce, 90% of accuracy in manufacturing industry, and 85% of accuracy in service industry. And optimization model help user to save about $195,374 in government units, $4,031 in commerce, $30,978 in manufacturing industry, and $39,905 in service industry. Therefore, the result of experiment explain that this proposed method can help user efficiently to make appropriate contract capacity.
Black, Jonathan D. "Load Hindcasting: A Retrospective Regional Load Prediction Method Using Reanalysis Weather Data." 2011. https://scholarworks.umass.edu/theses/666.
Full text