Relevant bibliographies by topics / Scheduling policies

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Scheduling policies'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Scheduling policies"

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Guide, V. Daniel R., Mark E. Kraus, and Rajesh Srivastava. "Scheduling policies for remanufacturing." International Journal of Production Economics 48, no. 2 (January 1997): 187–204. http://dx.doi.org/10.1016/s0925-5273(96)00091-6.

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Caspi, Paul, Jean-Louis Colaço, Léonard Gérard, Marc Pouzet, and Pascal Raymond. "Synchronous objects with scheduling policies." ACM SIGPLAN Notices 44, no. 7 (June 28, 2009): 11–20. http://dx.doi.org/10.1145/1543136.1542455.

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Labarta, Jesus, Sergi Girona, and Toni Cortes. "Analyzing scheduling policies using Dimemas." Parallel Computing 23, no. 1-2 (April 1997): 23–34. http://dx.doi.org/10.1016/s0167-8191(96)00094-4.

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Kesselman, Alex, and Adi Rosén. "Scheduling policies for CIOQ switches." Journal of Algorithms 60, no. 1 (July 2006): 60–83. http://dx.doi.org/10.1016/j.jalgor.2004.09.003.

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Thomasian, Alexander, and Chang Liu. "Disk scheduling policies with lookahead." ACM SIGMETRICS Performance Evaluation Review 30, no. 2 (September 2002): 31–40. http://dx.doi.org/10.1145/588160.588165.

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Anton, E., R. Righter, and I. M. Verloop. "Scheduling under redundancy." ACM SIGMETRICS Performance Evaluation Review 50, no. 2 (August 30, 2022): 30–32. http://dx.doi.org/10.1145/3561074.3561085.

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In the present extended abstract we investigate the impact that the scheduling policy has on the performance of redundancy systems when the usual exponentially distributed i.i.d. copies assumption is relaxed. In particular, we investigate the performance, in terms of the total number of jobs in the system, not only for redundancy-oblivious policies, such as FCFS (First-Come-First-Serve) and ROS (Random- Order-of-Service), but also for redundancy-aware policies of the form Π1-?2, where Π1 discriminates among job classes and Π2 discriminates among jobs of the same class. Examples of first-level policies are LRF (Least-Redundant-First) and MRF (Most-Redundant-First), where under LRF, respectively MRF, within a server jobs with fewer copies, respectively more copies, have priority over jobs with more copies, respectively fewer copies. Second-level policies could be FCFS or ROS.
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Guide, V. D. R., R. Srivastava, and M. E. Kraus. "Priority scheduling policies for repair shops." International Journal of Production Research 38, no. 4 (March 2000): 929–50. http://dx.doi.org/10.1080/002075400189220.

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Krueger, P., and N. G. Shivaratri. "Adaptive location policies for global scheduling." IEEE Transactions on Software Engineering 20, no. 6 (June 1994): 432–44. http://dx.doi.org/10.1109/32.295892.

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Brown, Patrick. "Comparing FB and PS scheduling policies." ACM SIGMETRICS Performance Evaluation Review 34, no. 3 (December 2006): 18–20. http://dx.doi.org/10.1145/1215956.1215965.

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Martinez, G., E. Heymann, and M. Senar. "Integrating scheduling policies into workflow engines." Procedia Computer Science 1, no. 1 (May 2010): 2743–52. http://dx.doi.org/10.1016/j.procs.2010.04.308.

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Dissertations / Theses on the topic "Scheduling policies"

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King, Brett. "Optimal mine scheduling policies." Thesis, Imperial College London, 2000. http://hdl.handle.net/10044/1/8458.

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Wan, Ziqi. "Scheduling Policies for Cloud Computing." Master's thesis, Temple University Libraries, 2015. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/328227.

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Computer and Information Science
M.S.
Cloud computing focuses on maximizing the effectiveness of the shared resources. Cloud resources are usually not only shared by multiple users but are also dynamically reallocated per demand. This can work for allocating resources to users. This leads to task scheduling as a core and challenging issue in cloud computing. This thesis gives different scheduling strategies and algorithms in cloud computing. For a common cloud user, there is a great potential to boost the performance of mobile devices by offloading computation-intensive parts of mobile applications to the cloud. However, this potential is hindered by a gap between how individual mobile devices demand computational resources and how cloud providers offer them. In this thesis, we present the design of utility-based uploads sharing strategy in cloud scenarios, which bridges the above gap through providing computation offloading as a service to mobile devices. Our scheme efficiently manages cloud resources for offloading requests to improve offloading performances of mobile devices, as well as to reduce the monetary cost per request of the provider. However, from the viewpoint of data centers, resource limitations in both bandwidth and computing triggers a variety of resource management problems. In this thesis, we discuss the tradeoff between locality and load balancing, along with the multi-layer topology of data centers. After that, we investigate the interrelationship between the time cost and the virtual machine rent cost, and formalize it as the parallel speedup pattern. We then design several algorithms by adopting the idea of minimizing the utility cost. Furthermore, we focus on the detail of MapReduce framework in Cloud. For different MapReduce phases, there are different resource requirements. We propose a new scheduling algorithm based on the idea of combining map shuffle pairs, which has better performance than the popular min-max time first algorithm in minimizing the average makespan of tasks in the job matrix. Directions for future research mainly focus on the large scale implementation of our proposed solution. There are a wide variety of open questions remaining with respect to the design of algorithms to minimize response time. Further, it is interesting and important to understand how to schedule in order to minimize other performance metrics.
Temple University--Theses
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Núñez, del Toro Alma Cristina. "Scheduling policies for multi-period services." Doctoral thesis, Universitat Politècnica de Catalunya, 2016. http://hdl.handle.net/10803/384932.

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In many situations, the resources in organizations are employed to satisfy some demand (or services) requirements, which are repeated with some periodicity. These recurrent services appear in a large variety of processes such as manufacturing, logistics and several other types of services. In this thesis, we focus on a particular family of problems involving the planning of recurrent services. In these problems resources are assigned to offer recurrent services over a planning horizon. Even if these problems can be classified as scheduling problems, this specific characteristic makes them differ from the typical scheduling problems studied in the literature. A very special characteristic of the problems that we study is that services are considered as single-period tasks. That is, the time needed to start and complete a service never exceeds one time period of the planning horizon. Furthermore, we focus on identifying the single periods when each service is repeated within the time horizon, instead of on the sequence according to which the different services are executed along the time horizon. We concentrate on modelling aspects for recurrent service problems with single-period duration,and on solution techniques for efficiently finding solutions. Particular emphasis is placed on the study of the strategy that is followed to offer the services over the planning horizon, that is, the policy for scheduling. Our aim is to analyze different options for such scheduling policies.The purpose is to provide enough support to decision makers to determine the convenience of using (or not) flexible policies as an alternative to regular strategies.For this, we study alternative models for two different scheduling policies. These models are addressed from a mathematical programming point of view and, therefore, we present several Mixed Integer Linear Programming (MILP) formulations. We develop two different types of formulations: the first type can be seen as a natural initial approach to the problem and produces sparse coefficients matrices whereas the second type is focused on determining the very first service period for each customer and gives dense matrices. For each type of formulation, we present two versions: an extensive and a compact one. In the first one decision variables are associated with individual demand customers whereas in the second one decision variables are associated with classes of customers with similar characteristics. For the regular policy we develop the both types of formulations whereas for the flexible policy we only study the extensive formulation. The formulations for each policy are compared trough extensive computational experience. Since the flexible policy results harder to solve than the regular one, we make use of combinatorial optimization techniques that permit alternative solution methods.In particular, we propose two different formulations suitable for column generation (CG).For each formulation we study the pricing subproblem that allows generating new columns, the initialization phase, as well as a procedure to tackle infeasibility issues. Additionally, we apply stabilization procedures in order to avoid the generation of an excessive of columns. Each CG algorithm is embedded within a branch-and-price (BP) framework, which combines different branching strategies. The BP was implemented for each CG formulation producing very interesting results that we present and analyze. Heuristics are alternative combinatorial optimization techniques that provide optimal and near optimal values within small computational times. In this thesis we also propose a heuristic algorithm suitable for both of scheduling policies.The heuristic produces good quality solutions for the studied problems, specially for the flexible policy. Finally, the structure of the solutions obtained with both scheduling policies are analyzed giving important insights on the trade-off between the regular and the flexible policies.
En muchas situaciones los recursos en las organizaciones se usan para satisfacer requerimientos de demanda (o servicios) los cuales se repiten con cierta periodicidad. Estos servicios recurrentes aparecen en una gran variedad de procesos de manufactura, logística y varios otros tipos de servicios. Esta tesis aborda una familia de problemas en donde los recursos deben ser asignados para ofrecer servicios recurrentes sobre un horizonte de planeación. Estos problemas tienen ciertas características que los hacen distintos a los problemas típicos de calendarización encontrados en la literatura. Una de ellas es que los servicios son tareas de periodo unitario. Esto es, el tiempo necesario para comenzar y terminar un servicio nunca excede de un periodo de tiempo del horizonte de planeación. Además, en este tipo de problemas no enfocamos en determinar los periodos en los que cada servicio será repetido, en lugar de la secuenciación en que los diferentes servicios son ejecutados. En particular, nos concentramos en aspectos de modelización para los problemas de servicios recurrentes con duración de periodo simple así como en técnicas de resolución para encontrar soluciones eficientes. Hacemos particular énfasis en el estudio de la estrategia a seguir para ofrecer los servicios, esto es, la política de calendarización. Nuestro propósito es el análisis de distintas opciones para tales políticas. El objetivo es proveer soporte suficiente para los tomadores de decisiones en cuanto a la conveniencia de usar (o no) políticas flexibles como alternativa a estrategias regulares. Para ello estudiamos modelos alternativos para dos diferentes políticas de calendarización. Estos modelos se estudian desde una perspectiva de programación matemática y, por tanto, se presentan varias formulaciones de programación lineal mixta entera. En esta tesis desarrollamos dos tipos de formulaciones: el primer tipo puede verse como un acercamiento natural al problema y produce matrices con coeficientes dispersos mientras que el segundo tipo se enfoca en determinar el primer periodo de servicio para cada cliente y da como resultado matrices densas. Para cada tipo de formulación presentamos dos versiones: una extensa y una compacta. En la primera, las variables de decisión están asociadas a clientes individuales mientras que en la segunda, las variables de decisión se asocian con clases de clientes con características similares. Para la política regular desarrollamos formulaciones de las dos versiones mientras que para la política flexible únicamente estudiamos formulaciones extensas. Las formulaciones para cada política son comparadas por medio de una amplia experiencia computacional. Debido a que la política flexible resulta más difícil de resolver que la regular, usamos técnicas de optimización combinatoria que permiten métodos alternativos de solución. En particular, proponemos dos formulaciones distintas, ambas adecuadas para generación de columnas (GC). Para cada formulación estudiamos el subproblema de pricing para generar nuevas columnas, la fase de inicialización así como un procedimiento para atacar temas de infactibilidad. Además, aplicamos procedimientos de estabilización con el objetivo de evitar la generación de un número excesivo de columnas. Cada algoritmo de GC ha sido incrustado dentro de una estructura de branch-and-price (BP), el cual combina diferentes estrategias de ramificación. El BP ha sido implementado para cada formulación de GC produciendo resultados interesantes los cuales presentamos y analizamos. En este trabajo también proponemos un algoritmo heurístico adaptable para ambas políticas de calendarización. Las heurísticas producen soluciones de buena calidad para los problemas estudiados, especialmente para la política flexible. Finalmente, la estructura de las soluciones obtenidas con ambas políticas se analizan, obteniendo ideas importantes en cuanto a la compensación entre las políticas regulares y las flexibles.
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Mitchell, Helen Margaret. "Index policies for complex scheduling problems." Thesis, University of Newcastle Upon Tyne, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.397534.

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Matondang, Abdul Rahim. "Evaluation of real time scheduling policies using simulation." Thesis, Cranfield University, 1988. http://hdl.handle.net/1826/3704.

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The purpose of this research is to investigate the effects of different scheduling operating policies in real- time scheduling. The scheduling policies include due date assignment method, priority rules, process batch method and operator reassignment policy. A specific case of production scheduling-in a hypothetical assembled product manufacturing system was investigated in this research. The simulated production system encompasses fifteen work centres, each containing one to three identical machines and each machine requires one operator with all operations being perfectly efficient on all machine types. The production -system produces finished products as well as components and sub-assemblies. Orders from outside the system arrive for service generated according to the exponential distribution. The orders coming to the system were classified into "priority" and "standard" orders. Processing times at each work centre are statistically independent and uniformly distributed. A computer simulation technique was chosen as the approach method. A computer simulation written in DBASE III PLUS was used to generate the data for analysis. In order to analyse the behaviour of the simulated production system with respect to the different performance criteria, a number of performance measures were selected. These are, mean tardiness, percent tardy, mean work in progress, mean machine utilisation, and mean operator utilisation. The 2x6x2x2 complete factorial is analysed by the analysis of variance (ANOVA) procedure to statistically determine whether due date assignment method, priority rules, process batch method, and operator reassignment policy or their interaction significantly affect the performance criteria considered. Further analysis to identify where significant differences in performance occur is conducted via Duncan multiple comparison test. Based upon the statistical analysis it was found that the relative impact of due date assignment method, priority rule, process batch method, and operator reassignment policy or their interaction for scheduling policies in real time scheduling to be dependent upon the measure of performance considered. In respect of root mean square of tardiness, the scheduling policies involving the slack time remaining (STR) priority rule are the most important of scheduling policies in minimising the tardiness of customer orders produced by the company. In respect to minimising the work in progress, there is no dominant level of due date assignment method, or priority rule or process batch method or operator reassignment policy. However, the scheduling policies involving the variable process batch (VPB) method produce the best result. The scheduling policies involving the variable process batch (VPB) method are the best performers in maximising the utilisation of machine and operator.
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PERES, IGOR TONA. "SIMULATION OF APPOINTMENT-SCHEDULING POLICIES IN OUTPATIENT SERVICES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=31401@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
FUNDAÇÃO DE APOIO À PESQUISA DO ESTADO DO RIO DE JANEIRO
BOLSA NOTA 10
Os sistemas de agendamento de consultas tradicionalmente realizam as marcações dos pacientes em intervalos fixos de tempo, sem levar em consideração diversos fatores de complexidade do sistema de saúde. Isso pode causar mão de obra ociosa em alguns períodos do dia e longas filas de espera de pacientes em outros momentos. Nesse contexto, esta dissertação tem como intuito propor uma nova política de agendamento para uma clínica especializada em cirurgia bariátrica do Rio de Janeiro, considerando os fatores desse sistema: tempos de serviços estocásticos, impontualidade do paciente, atrasos e interrupções do serviço, e presenças de no-shows. Esta dissertação analisou diversos cenários com overbooking (marcação de pacientes adicionais), e testou as principais políticas por meio de simulação, propondo a mais adequada para a clínica. As 18 políticas de agendamento aplicadas foram encontradas através de uma extensa revisão sistemática da literatura. Com a utilização da política de agendamento OFFSET, foi possível aumentar o número de atendimentos em 30 por cento para o agendamento do principal provedor da clínica, mantendo o nível de serviço prestado. Além disto, foi proposta uma nova política de agendamento, denominada DOME CYCLE, que teve resultados superiores às demais políticas da literatura na média dos cenários realizados.
Appointment-scheduling systems traditionally schedule patient appointments at fixed intervals, without taking into account several complexity factors of health-care system. This schedule can make the server idle at certain times of the day and can produce long queues of patients at other times. In this context, the objective of this study is to propose a new scheduling policy for a clinic specialized in bariatric surgery in Rio de Janeiro, considering the following factors of this system: stochastic service times, patient unpunctuality, delays and interruptions of the provider and presences of no-shows. This study analyzed several scenarios with overbooking, and tested the main policies with a simulation model, proposing the most appropriate for the clinic. The 18 scheduling policies applied were found through an extensive systematic review of the literature. With the use of the OFFSET scheduling policy, it was possible to increase the number of appointments by 30 percent to the scheduling of the main clinic provider, maintaining the level of service provided. In addition, a new scheduling policy, called DOME CYCLE, was proposed, which has outperformed the other policies in the average of the tests performed.
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Martínez, Gustavo Enrique. "Frame work for Integrating Scheduling Policies into Workflow Engines." Doctoral thesis, Universitat Autònoma de Barcelona, 2011. http://hdl.handle.net/10803/79127.

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En este trabajo se ha desarrollado una nueva solución para la integración de políticas de planificación de workflows en sistemas gestores de workflows (workflow engines). SchedFlow es la solución propuesta e implementada, la cual Permite que un usuario final pueda utilizar la política de planificación que desee, ya sea esta estática o dinámica, sin necesidad de modificar el sistema gestor de workflow. Además SchedFlow toma en cuenta cuando una tarea del workflow no se puede ejecutar por eventos externos, como que una máquina está siendo utilizada por el usuario principal de la misma. En este tipo de escenarios SchedFlow realiza la replanificación de tareas, siempre bajo la política de planificación definida o elegida por el usuario. Como resultado se ha obtenido una aportación novedosa ya que normalmente si el usuario desea utilizar una política de planificación específica, deberá modificar el gestor de workflow para que soporte dicha política de planificación. Un punto importante a destacar, es que esta tesis además de contener un estudio exhaustivo de la bibliografía existente en el área, y de realizar un análisis de problema y diseño de solución propuesta, implementa la solución en un entorno oportunístico real. Los resultados de esta tesis para la planificación de workflows en entornos Grid, abre una nueva vía para el estudio de políticas de planificación para este tipo de aplicaciones, que será aprovechado por futuras investigaciones en la UAB.
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Malhotra, Manoj K. "Staff scheduling models and policies in postal distribution systems /." Connect to resource, 1990. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1266494783.

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Young, Laurie Robert. "Scheduling in a grid environment using high level policies." Thesis, Imperial College London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426063.

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Malhotra, Manoj Kumar. "Staff scheduling models and policies in postal distribution systems." The Ohio State University, 1990. http://rave.ohiolink.edu/etdc/view?acc_num=osu1266494783.

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Books on the topic "Scheduling policies"

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Educational Research Service (Arlington, Va.), ed. Alternative time and scheduling policies. Alexandria, VA: Educational Research Service, 2008.

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Lin, Kyle Y. Scheduling policies for an antiterrorist surveillance system. Monterey, Calif: Naval Postgraduate School, 2006.

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Psychas, Konstantinos. Scalable Scheduling Policies with Performance Guarantees for Cloud Applications. [New York, N.Y.?]: [publisher not identified], 2020.

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Raine, J. W. Of corporate concern: Scheduling policies in the Northamptonshire magistrates courts. Birmingham: University of Birmingham, 1985.

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Pop, Traian. Analysis and optimisation of distributed embedded systems with heterogeneous scheduling policies. Linköping: Department of Computer and Information Science, Linköpings universitet, 2007.

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Latta, Peter James. A comparison of six repair scheduling policies for the P-3 aircraft. Monterey, California: Naval Postgraduate School, 1988.

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NASA schedule management handbook. Washington, D.C: National Aeronautics and Space Administration, 2011.

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Markowitz, David Maxwell. The stochastic economic lot scheduling problem: Heavy traffic analysis of dynamic cyclic policies. [Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology], 1995.

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Markowitz, David Maxwell. Heavy traffic analysis of dynamic cyclic policies: A unified treatment of the single machine scheduling problem. [Cambridge, MA: Sloan School of Management, Massachusetts Institute of Technology], 1996.

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Moulder, Evelina R. Police personnel practices: Education, participation, and scheduling. Washington, D. C: International City/County Management Association, 1991.

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Book chapters on the topic "Scheduling policies"

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Hou, I.-Hong, and P. R. Kumar. "Scheduling Policies." In Packets with Deadlines, 31–40. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-031-79257-1_4.

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Nakagawa, Toshio. "Random Scheduling." In Random Maintenance Policies, 175–96. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6575-0_7.

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Melchiors, Philipp. "Scheduling Using Priority Policies." In Lecture Notes in Economics and Mathematical Systems, 51–71. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04540-5_6.

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Dandamudi, Sivarama. "Performance of Scheduling Policies." In Hierarchical Scheduling in Parallel and Cluster Systems, 121–39. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0133-6_5.

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Chen, Quan, and Minyi Guo. "Conventional Task Scheduling Policies." In Task Scheduling for Multi-core and Parallel Architectures, 13–26. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6238-4_2.

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Minguet, Agustín Espinosa, Ana García-Fornes, Vicente Lorente Garcés, and Andrés Terrasa Barrena. "Mixing Scheduling Policies in Ada." In Lecture Notes in Computer Science, 273–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24841-5_22.

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Melchiors, Philipp. "Optimal and Near Optimal Scheduling Policies." In Lecture Notes in Economics and Mathematical Systems, 73–156. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04540-5_7.

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Cai, Xiaoqiang, Xianyi Wu, and Xian Zhou. "Optimal Policies in Time-Varying Scheduling." In International Series in Operations Research & Management Science, 321–46. Boston, MA: Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-7405-1_9.

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Weishaupt, Jürgen. "Optimal Myopic Policies and Index Policies for Stochastic Scheduling Problems." In Operations Research ’92, 90–93. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12629-5_24.

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Rosti, E., E. Smirni, G. Serazzi, and L. W. Dowdy. "Analysis of non-work-conserving processor partitioning policies." In Job Scheduling Strategies for Parallel Processing, 165–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60153-8_28.

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Conference papers on the topic "Scheduling policies"

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Kadloor, Sachin, Xun Gong, Negar Kiyavash, and Parv Venkitasubramaniam. "Designing router scheduling policies." In the 17th ACM conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1866307.1866403.

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Caspi, Paul, Jean-Louis Colaço, Léonard Gérard, Marc Pouzet, and Pascal Raymond. "Synchronous objects with scheduling policies." In the 2009 ACM SIGPLAN/SIGBED conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1542452.1542455.

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Kesselman, Alex, and Adi Rosén. "Scheduling policies for CIOQ switches." In the fifteenth annual ACM symposium. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/777412.777473.

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Anderson, David P. "Emulating Volunteer Computing Scheduling Policies." In Distributed Processing, Workshops and Phd Forum (IPDPSW). IEEE, 2011. http://dx.doi.org/10.1109/ipdps.2011.343.

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Wang, Xingxuan. "Switching scheduling policies and their balanceabililty." In 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC). IEEE, 2009. http://dx.doi.org/10.1109/cdc.2009.5400495.

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Ogur, Emin, and Mehmet E. Aydin. "Refining scheduling policies with genetic algorithms." In Proceeding of the fifteenth annual conference companion. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2464576.2482730.

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Geetha, V., R. Aruna Devi, T. Ilavenil, S. Marjana Begum, and S. Revathi. "Performance comparison of cloudlet scheduling policies." In 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). IEEE, 2016. http://dx.doi.org/10.1109/icetets.2016.7602986.

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Kretsis, A., P. Kokkinos, and E. Varvarigos. "Developing Scheduling Policies in gLite Middleware." In 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid. IEEE, 2009. http://dx.doi.org/10.1109/ccgrid.2009.54.

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Johnson, Mary A., Udatta S. Palekar, and Yi Zhang. "Scheduling policies for a computing system." In the 25th conference. New York, New York, USA: ACM Press, 1993. http://dx.doi.org/10.1145/256563.257051.

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Kadloor, Sachin, Xun Gong, Negar Kiyavash, and Parv Venkitasubramaniam. "Designing privacy preserving router scheduling policies." In 2011 45th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2011. http://dx.doi.org/10.1109/ciss.2011.5766104.

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Reports on the topic "Scheduling policies"

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Lin, Kyle Y., Moshe Kress, and Roberto Szechtman. Scheduling Policies for an Antiterrorist Surveillance System. Fort Belvoir, VA: Defense Technical Information Center, June 2008. http://dx.doi.org/10.21236/ada486551.

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Leung, Vitus Joseph, Gerald Sabin, and Ponnuswamy Sadayappan. Parallel job scheduling policies to improve fairness : a case study. Office of Scientific and Technical Information (OSTI), February 2008. http://dx.doi.org/10.2172/929521.

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