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1

Mullender, Sape J. "Distributed operating systems." ACM Computing Surveys 28, no. 1 (March 1996): 225–27. http://dx.doi.org/10.1145/234313.234407.

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2

Tanenbaum, Andrew S., and Robbert Van Renesse. "Distributed operating systems." ACM Computing Surveys 17, no. 4 (December 10, 1985): 419–70. http://dx.doi.org/10.1145/6041.6074.

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3

Mullender, Sape J. "Distributed operating systems." Computer Standards & Interfaces 6, no. 1 (January 1987): 37–44. http://dx.doi.org/10.1016/0920-5489(87)90043-2.

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4

Chandras, Rajan G. "Distributed message passing operating systems." ACM SIGOPS Operating Systems Review 24, no. 1 (January 3, 1990): 7–17. http://dx.doi.org/10.1145/90994.90999.

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5

Stojcev, M. "Distributed Operating Systems: Concepts and Practice." Microelectronics Journal 31, no. 5 (May 2000): 374–75. http://dx.doi.org/10.1016/s0026-2692(99)00156-1.

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6

Moller, R. "Distributed Operating Systems: Concepts And Design." IEEE Concurrency 6, no. 2 (April 1998): 93–94. http://dx.doi.org/10.1109/mcc.1998.678836.

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7

Wiseman, Yair. "Advanced non-distributed operating systems course." ACM SIGCSE Bulletin 37, no. 2 (June 2005): 65–69. http://dx.doi.org/10.1145/1083431.1083466.

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8

Frieder, O., A. Litman, and M. E. Segal. "DUNIX: Distributed operating systems education via experimentation." Microprocessing and Microprogramming 27, no. 1-5 (August 1989): 811–18. http://dx.doi.org/10.1016/0165-6074(89)90155-5.

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9

Hackel, R., and M. Nagy. "Supervisory Tasks on Operating Distributed Computing Systems." IFAC Proceedings Volumes 23, no. 8 (August 1990): 117–21. http://dx.doi.org/10.1016/s1474-6670(17)51809-1.

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10

Ceballos, Henry Zárate, and Jorge Eduardo Ortiz Triviño. "S.O.V.O.R.A.: A Distributed Wireless Operating System." Information 11, no. 12 (December 14, 2020): 581. http://dx.doi.org/10.3390/info11120581.

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Due to the growth of users and linked devices in networks, there is an emerging need for dynamic solutions to control and manage computing and network resources. This document proposes a Distributed Wireless Operative System on a Mobile Ad-hoc Network (MANET) to manage and control computing resources in relation to several virtual resources linked in a wireless network. This prototype has two elements: a local agent that works on each physical node to manage the computing resources (e.g., virtual resources and distributed applications) and an orchestrator agent that monitors, manages, and deploys policies on each physical node. These elements arrange the local and global computing resources to provide a quality service to the users of the Ad-hoc cluster. The proposed S.O.V.O.R.A. model (Operating Virtualized System oriented to Ad-hoc networks) defines primitives, commands, virtual structures, and modules to operate as a distributed wireless operating system.
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11

Andrianoff, Steven K. "A module on distributed systems for the operating systems course." ACM SIGCSE Bulletin 22, no. 1 (February 1990): 176–80. http://dx.doi.org/10.1145/319059.323443.

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12

Leslie, Ian M., Derek McAuley, and Sape J. Mullender. "Pegasus—operating system support for distributed multimedia systems." ACM SIGOPS Operating Systems Review 27, no. 1 (January 1993): 69–78. http://dx.doi.org/10.1145/160551.160557.

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13

Lebee, Pierre, Kun Mean Hou, Marc Guillemont, and Guy Fontenier. "A new machine architecture for distributed operating systems." Microprocessing and Microprogramming 22, no. 3 (May 1988): 187–203. http://dx.doi.org/10.1016/0165-6074(88)90421-8.

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14

Pontremoli, M. M. B., and C. E. Pereira. "Hardware support for distributed real-time operating systems." Control Engineering Practice 5, no. 10 (October 1997): 1435–42. http://dx.doi.org/10.1016/s0967-0661(97)00141-x.

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15

Daszczuk, W. B. "A Structured Semantic Design of Distributed Operating Systems." Computer Journal 34, no. 6 (December 1, 1991): 482–92. http://dx.doi.org/10.1093/comjnl/34.6.482.

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16

Pontremoli, Moisés M. B., and Carlos Eduardo Pereira. "Hardware Support for Distributed Real-Time Operating Systems." IFAC Proceedings Volumes 30, no. 3 (April 1997): 161–65. http://dx.doi.org/10.1016/s1474-6670(17)44484-3.

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17

Wybranietz, Dieter, and Peter Buhler. "The LADY programming environment for distributed operating systems." Future Generation Computer Systems 6, no. 3 (December 1990): 209–23. http://dx.doi.org/10.1016/0167-739x(90)90020-e.

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18

Tripathi, Anand R., and Neeran M. Karnik. "Trends in multiprocessor and distributed operating systems designs." Journal of Supercomputing 9, no. 1-2 (March 1995): 23–49. http://dx.doi.org/10.1007/bf01245396.

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19

Kosarev, B. A., O. A. Lysenko, V. K. Fedorov, and R. N. Khamitov. "CHAOTIC OPERATING MODES OF POWER SYSTEMS WITH DISTRIBUTED GENERATION." Actual Issues Of Energy 2, no. 1 (2020): 027–31. http://dx.doi.org/10.25206/2686-6935-2020-2-1-27-31.

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20

Thekkath, Chandramohan A., Henry M. Levy, and Edward D. Lazowska. "Separating data and control transfer in distributed operating systems." ACM SIGPLAN Notices 29, no. 11 (November 1994): 2–11. http://dx.doi.org/10.1145/195470.195481.

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21

Longo, Francesco, Dario Bruneo, Salvatore Distefano, and Marco Scarpa. "Variable operating conditions in distributed systems: modeling and evaluation." Concurrency and Computation: Practice and Experience 27, no. 10 (October 13, 2014): 2506–30. http://dx.doi.org/10.1002/cpe.3419.

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22

Thekkath, Chandramohan A., Henry M. Levy, and Edward D. Lazowska. "Separating data and control transfer in distributed operating systems." ACM SIGOPS Operating Systems Review 28, no. 5 (December 1994): 2–11. http://dx.doi.org/10.1145/381792.195481.

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23

Shriram, Alok, Anuraag Sarangi, and Avinash S. "ICHU model for processor allocation in distributed operating systems." ACM SIGOPS Operating Systems Review 35, no. 3 (July 2001): 16–21. http://dx.doi.org/10.1145/383237.383239.

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24

Rabbie, Harold M. "DISTRIBUTED PROCESSING USING LOCAL OPERATING NETWORKS." Assembly Automation 12, no. 1 (January 1992): 14–19. http://dx.doi.org/10.1108/eb004354.

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25

DiLuoffo, Vincenzo, William R. Michalson, and Berk Sunar. "Robot Operating System 2." International Journal of Advanced Robotic Systems 15, no. 3 (May 1, 2018): 172988141877001. http://dx.doi.org/10.1177/1729881418770011.

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It is no secret that robotic systems are expanding into many human roles or are augmenting human roles. The Robot Operating System is an open-source standard for the robotic industry that enables locomotion, manipulation, navigation, and recognition tasks by integrating sensors, motors, and controllers into reusable modules over a distributed messaging architecture. As reliance on robotic systems increases, these systems become high value targets, for example, in autonomous vehicles where human life is at risk. As Robot Operating System has become a de facto standard for many robotic systems, the security of Robot Operating System becomes an important consideration for deployed systems. The original Robot Operating System implementations were not designed to mitigate the security risks associated with hostile actors. Robot Operating System 2, the next generation of the Robot Operating System, addresses this shortcoming, leveraging Data Distributed Services for its messaging architecture and Data Distributed Services security extension for its data protection in motion. This article provides a systematic review of Robot Operating System 2 and identifies potential risks for this new robotic system paradigm. A Robot Operating System 2 robotic system is viewed as a series of layers from the hardware that include sensors, motors, and controllers to the software layers, which include the operating system, security services, protocols, messaging, and the cognitive layer for observation, learning, and action. Since Robot Operating System 2 and security are new considerations for robotics systems as they move into mainstream, many questions emerge. For example, can some portions be secure and other portions be non-secure? Does everything need to be secure? What are the trade-offs between, security, performance, latency and throughput? What about real-time robotic systems? This article provides an overview of the Robot Operating System 2 paradigm and represents a first step toward answering these questions.
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26

Thararak, Panida, and Peerapol Jirapong. "Implementation of Optimal Protection Coordination for Microgrids with Distributed Generations Using Quaternary Protection Scheme." Journal of Electrical and Computer Engineering 2020 (February 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/2568652.

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The flexible operation of microgrids, along with the availability of distributed generation (DG) units, causes a variety of changes in short-circuit current levels, magnitudes, and directions, which has undesirable effects on the operation of protection systems. Conventional protection schemes use typical directional overcurrent relays (DOCRs) with limited operating capability, unable to respond to microgrid operations in the manner of short-circuit current changes. In this paper, a quaternary protection scheme implemented with dual-directional overcurrent relays (dual-DOCR) and a protection control strategy is developed for protecting against faults in microgrids, taking into account the existence of DGs and connection and disconnection of DG units. The optimal dual-DOCRs setting and coordination are formulated as an optimization problem solved by evolutionary programming to minimize the relay operating times. The proposed protection scheme is implemented with a centralized protection control system based on the smart grid concept to increase the adaptability of the dual-DOCRs, which have multiple relay setting groups in accordance with system state changes. The simulation case studies are performed using the IEEE 14-bus test system, which is modified as a meshed microgrid operation. Test scenarios, including possible operations of microgrids, DGs availabilities, and different fault events, are analyzed and discussed. The comparative studies and simulation results show that the proposed scheme provides efficient coordination between the primary and backup relays and increases the responsibility of the protection system, which can be observed from the significant reduction in the relay operating times, resulting in the enhancement of selectivity, sensitivity, and speed of microgrid protection systems.
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27

Lee, Hyeon-Seok, and Jae-Jung Yun. "Advanced MPPT Algorithm for Distributed Photovoltaic Systems." Energies 12, no. 18 (September 19, 2019): 3576. http://dx.doi.org/10.3390/en12183576.

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The basic and adaptive maximum power point tracking algorithms have been studied for distributed photovoltaic systems to maximize the energy production of a photovoltaic (PV) module. However, the basic maximum power point tracking algorithms using a fixed step size, such as perturb and observe and incremental conductance, suffer from a trade-off between tracking accuracy and tracking speed. Although the adaptive maximum power point tracking algorithms using a variable step size improve the maximum power point tracking efficiency and dynamic response of the basic algorithms, these algorithms still have the oscillations at the maximum power point, because the variable step size is sensitive to external factors. Therefore, this paper proposes an enhanced maximum power point tracking algorithm that can have fast dynamic response, low oscillations, and high maximum power point tracking efficiency. To achieve these advantages, the proposed maximum power point tracking algorithm uses two methods that can apply the optimal step size to each operating range. In the operating range near the maximum power point, a small fixed step size is used to minimize the oscillations at the maximum power point. In contrast, in the operating range far from the maximum power point, a variable step size proportional to the slope of the power-voltage curve of PV module is used to achieve fast tracking speed under dynamic weather conditions. As a result, the proposed algorithm can achieve higher maximum power point tracking efficiency, faster dynamic response, and lower oscillations than the basic and adaptive algorithms. The theoretical analysis and performance of the proposed algorithm were verified by experimental results. In addition, the comparative experimental results of the proposed algorithm with the other maximum power point tracking algorithms show the superiority of the proposed algorithm.
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28

Holmbacka, Simon, Mohammad Fattah, Wictor Lund, Amir-Mohammad Rahmani, Sébastien Lafond, and Johan Lilius. "A task migration mechanism for distributed many-core operating systems." Journal of Supercomputing 68, no. 3 (March 8, 2014): 1141–62. http://dx.doi.org/10.1007/s11227-014-1144-7.

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29

Pessolani, Pablo Andrés. "An Architecture Model for a Distributed Virtualization System." Journal of Computer Science and Technology 19, no. 2 (October 10, 2019): e17. http://dx.doi.org/10.24215/16666038.19.e17.

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The Thesis is about an architecture model for a Distributed Virtualization System, which could expand a virtual execution environment from a single physical machine to several nodes of a cluster. With current virtualization technologies, computing power and resource usage of Virtual Machines (or Containers) are limited to the physical machine where they run. To deliver high levels of performance and scalability, cloud applications are usually partitioned in several Virtual Machines (or Containers) located on different nodes of a virtualization cluster. Developers often use that processing model because the same instance of the operating system is not available on each node where their components run. The proposed architecture model is suitable for new trends in software development because it is inherently distributed. It combines and integrates Virtualization and Distributed Operating Systems technologies with the benefits of both worlds, providing the same isolated instance of a Virtual Operating System on each cluster node. Although it requires the introduction of changes in existing operating systems, thousands of legacy applications would not require modifications to obtain their benefits. A Distributed Virtualization System is suitable to deliver high-performance cloud services with provider-class features, such as high-availability, replication, migration, and load balancing. Furthermore, it is able to concurrently run several isolated instances of different guest Virtual Operating Systems, allocating a subset of nodes for each instance and sharing nodes between them. Currently, a prototype is running on a cluster of commodity hardware provided with two kinds of Virtual Operating Systems tailored for internet services (web server) as a proof of concept.
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30

RUSSELL, DAVID W. "DISTRIBUTED INTELLIGENCE IN MANUFACTURING INFORMATION SYSTEMS." New Mathematics and Natural Computation 07, no. 01 (March 2011): 71–87. http://dx.doi.org/10.1142/s1793005711001810.

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This paper describes an information system that was architected to enable front end distributed intelligence in a real manufacturing environment. By distributing intelligence to the most robust components of the system, data can be preserved at the cost of very real-time information. In order for the system as a whole to function this way, each software component was fitted with watchdog agent and granted system level access to the operating system so that it could detect and repair itself and other tasks in the event of a failure. During the repair process, the appropriate data collection processes were granted a level of autonomy that preserved data integrity. The paper is quite practical and designed as a case study rather than a theoretical research paper, although the techniques and principles applied are the result of much study.
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31

Lee, Young Choon, and Albert Y. Zomaya. "Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions." IEEE Transactions on Parallel and Distributed Systems 22, no. 8 (August 2011): 1374–81. http://dx.doi.org/10.1109/tpds.2010.208.

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32

Kulkarni, Dinesh C., Arindam Banerji, and David L. Cohn. "π: a new approach to the design of distributed operating systems." ACM SIGPLAN OOPS Messenger 4, no. 2 (April 1993): 141–43. http://dx.doi.org/10.1145/157710.157736.

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33

Tanenbaum, A. S. "Distributed operating systems anno 1992. What have we learned so far?" Distributed Systems Engineering 1, no. 1 (September 1993): 3–10. http://dx.doi.org/10.1088/0967-1846/1/1/001.

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34

Cvijović, Miomirka, and Mojca Kunc. "An approach to the design of distributed real-time operating systems." Microprocessors and Microsystems 16, no. 2 (January 1992): 81–89. http://dx.doi.org/10.1016/0141-9331(92)90075-5.

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35

Shi, Zhong Jin, Bing Xu, Bao Guo Zheng, and Xue Han Zhu. "The Energy-Saving Control of Combined Multi-Unit for Building Automatic System in the Subway." Applied Mechanics and Materials 513-517 (February 2014): 3597–600. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3597.

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Multi-unit operation in building automatic system (BAS) is an important part for the equipment operation; it is essentially a distributed multi agent system (MAS). In this paper, Petri net is adopted to establish the control model about the equipment operation in BAS, know the operating characteristics and start-stop conditions of energy consumption equipment in the rail which are in under different circumstances. Based on the analysis of BAS and the theory of distributed intelligent systems, according to the actual environment and energy requirements, the start-stop arrays are selected dynamically as the basis for the units operating, and ultimately achieve energy-saving operation of multi-unit control purposes.
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36

Raju, Leo, R. S. Milton, and Senthilkumaran Mahadevan. "Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX." Scientific World Journal 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9858101.

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The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.
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37

Gaitán, Luis Felipe, Juan David Gómez, and Edwin Rivas-Trujillo. "Quasi-Dynamic Analysis of a Local Distribution System with Distributed Generation. Study Case: The IEEE 13 Node System." TecnoLógicas 22, no. 46 (September 20, 2019): 195–212. http://dx.doi.org/10.22430/22565337.1489.

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Distributed generation is one of the most accepted strategies to attend the increase in electrical demand around the world. Since 2014, Colombian government agencies have enacted laws and resolutions to promote and regulate the introduction of different generation technologies into the country’s electrical system. The incorporation of distributed generation systems into conventional distribution networks can cause problems if technical studies are not previously carried out to determine the consequences of the start of the operations of these new generation technologies. This scenario represents a new challenge for distribution networks operators because they must ensure that their systems can integrate these new generation sources without affecting the correct operation of the grid. In this article, the IEEE 13 nodes system is modified by incorporating the load curves of the three types of consumers in the Colombian electricity market into the model. Additionally, distributed generation systems from non-conventional sources of energy are integrated into two system nodes in order to perform a quasi-dynamic analysis of the different electrical variables, which can be used to determine the impact of these new technologies on a local distribution system. The voltage profiles and active and reactive power do not show considerable changes in the behavior of the electrical network; however, in the simulation scenarios where distributed generators are operating, the system exhibits a considerable increase in lines losses. There are two alternatives to manage these unusual levels in the operation of the nodes with distributed generation: (1) operating these new DG nodes in islanded mode or (2) strengthening the local distribution system through the implementation of new distribution lines in the network.
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38

Etkin, J. "The transition from network operating systems to distributed global operating systems: Do we stretch too much the real-time requirements?" Microprocessing and Microprogramming 25, no. 1-5 (January 1989): 295–300. http://dx.doi.org/10.1016/0165-6074(89)90211-1.

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39

Chaudhary, Gaurav, Jacob J. Lamb, Odne S. Burheim, and Bjørn Austbø. "Review of Energy Storage and Energy Management System Control Strategies in Microgrids." Energies 14, no. 16 (August 11, 2021): 4929. http://dx.doi.org/10.3390/en14164929.

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A microgrid (MG) is a discrete energy system consisting of an interconnection of distributed energy sources and loads capable of operating in parallel with or independently from the main power grid. The microgrid concept integrated with renewable energy generation and energy storage systems has gained significant interest recently, triggered by increasing demand for clean, efficient, secure, reliable and sustainable heat and electricity. However, the concept of efficient integration of energy storage systems faces many challenges (e.g., charging, discharging, safety, size, cost, reliability and overall management). Additionally, proper implementation and justification of these technologies in MGs cannot be done without energy management systems, which control various aspects of power management and operation of energy storage systems in microgrids. This review discusses different energy storage technologies that can have high penetration and integration in microgrids. Moreover, their working operations and characteristics are discussed. An overview of the controls of energy management systems for microgrids with distributed energy storage systems is also included in the scope of this review.
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40

Wang, Lei, Shi Wei Zhu, and Jun Feng Yu. "Transplant and Tailor of gSOAP Based on Embedded Linux." Applied Mechanics and Materials 303-306 (February 2013): 2445–48. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.2445.

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In this paper, an open source web service software—gSOAP which is transplanted to the embedded Linux is proposed. Web service is not only an application entity for building applications, but also a distributed applications platform which runs operations interoperably. It can also execute all kinds of operating systems (OS) which support HTTP protocol. With the rapid development of the embedded system, lots of open-source software is transplanted to the embedded platform by embedded operating systems.
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41

Shafaat, Ahmed, and Shuxiang Xu. "A Comparative Study of Technologies Developed in Perspective of Distributed Operating Systems." Advances in Modelling and Analysis B 60, no. 3 (September 30, 2017): 613–29. http://dx.doi.org/10.18280/ama_b.600307.

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42

Coulson, Geoff, and Gordon Blair. "Architectural principles and techniques for distributed multimedia application support in operating systems." ACM SIGOPS Operating Systems Review 29, no. 4 (October 1995): 17–24. http://dx.doi.org/10.1145/219282.219286.

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43

Silva, Eudinei O., Wagner E. Vanco, and Geraldo C. Guimaraes. "Capacitor Bank Sizing for Squirrel Cage Induction Generators Operating in Distributed Systems." IEEE Access 8 (2020): 27507–15. http://dx.doi.org/10.1109/access.2020.2971704.

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44

Ravindran, K., and K. K. Ramakrishnan. "A naming system for feature-based service specification in distributed operating systems." ACM SIGSMALL/PC Notes 17, no. 3-4 (September 10, 1991): 12–21. http://dx.doi.org/10.1145/140738.140748.

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45

Wedde, H. F., G. S. Alijani, W. G. Brown, S. Chen, and G. Kang. "Operating system support for adaptive distributed real-time systems in DRAGON SLAYER." ACM SIGOPS Operating Systems Review 23, no. 3 (July 1989): 126–40. http://dx.doi.org/10.1145/71021.71028.

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46

Klöckl, B., G. Papaefthymiou, and P. Pinson. "Probabilistic tools for planning and operating power systems with distributed energy storage." e & i Elektrotechnik und Informationstechnik 125, no. 12 (December 2008): 460–65. http://dx.doi.org/10.1007/s00502-008-0600-6.

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47

Bhargava, Bharat, Enrique Mafla, and John Riedl. "Push: An experimental facility for implementing distributed database services in operating systems." Journal of Systems Integration 3, no. 1 (March 1993): 5–21. http://dx.doi.org/10.1007/bf01974169.

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48

Bifaretti, Stefano, Vincenzo Bonaiuto, Sabino Pipolo, Cristina Terlizzi, Pericle Zanchetta, Francesco Gallinelli, and Silvio Alessandroni. "Power Flow Management by Active Nodes: A Case Study in Real Operating Conditions." Energies 14, no. 15 (July 27, 2021): 4519. http://dx.doi.org/10.3390/en14154519.

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The role of distributor system operators is experiencing a gradual but relevant change to include enhanced ancillary and energy dispatch services needed to manage the increased power provided by intermittent distributed generations in medium voltage networks. In this context, the paper proposes the insertion, in strategic points of the network, of specific power electronic systems, denoted as active nodes, which permit the remote controllability of the active and reactive power flow. Such capabilities, as a further benefit, enable the distributor system operators to provide ancillary network services without requiring any procurement with distributed generation systems owners. In particular, the paper highlights the benefits of active nodes, demonstrating their capabilities in reducing the inverse power flow issues from medium to high voltage lines focusing on a network cluster including renewable energy resources. As a further novelty, this study has accounted for a real cluster operated by the Italian distributor system operator Areti. A specific simulation model of the electrical lines has been implemented in DigSilent PowerFactory (DIgSILENT GmbH–Germany) software using real operating data obtained during a 1-year measurement campaign. A detailed cost-benefit analysis has been provided, accounting for different load flow scenarios. The results have demonstrated that the inclusion of active nodes can significantly reduce the drawbacks related to the reverse power flow.
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49

Bolea, Yolanda, Nicolas Chefdor, and Antoni Grau. "MIMO LPV State-Space Identification of Open-Flow Irrigation Canal Systems." Mathematical Problems in Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/948936.

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Canal systems are complex nonlinear, distributed parameter systems with changing parameters according to the operating point. In this paper, a linear parameter-varying (LPV) state-space canal control model is obtained by identification in a local way using a multimodel approach. This LPV identification procedure is based on subspace methods for different operating points of an irrigation canal covering the full operation range. Different subspace algorithms have been used and compared. The model that best represents the canal behavior in a precise manner has been chosen, and it has been validated by error functions and analysis correlation of residuals in a laboratory multireach pilot canal providing satisfactory results.
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Gałecki, Tomasz, and Wiktor Bohdan Daszczuk. "Tree-Like Distributed Computation Environment with Shapp Library." Information 11, no. 3 (March 3, 2020): 143. http://dx.doi.org/10.3390/info11030143.

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Abstract:
Despite the rapidly growing computing power of computers, it is often insufficient to perform mass calculations in a short time, for example, simulation of systems for various sets of parameters, the searching of huge state spaces, optimization using ant or genetic algorithms, machine learning, etc. One can solve the problem of a lack of computing power through workload management systems used in local networks in order to use the free computing power of servers and workstations. This article proposes raising such a system to a higher level of abstraction: The use in the .NET environment of a new Shapp library that allows remote task execution using fork-like operations from Portable Operating System Interface for UNIX (POSIX) systems. The library distributes the task code, sending static data on which task force is working, and individualizing tasks. In addition, a convenient way of communicating distributed tasks running hierarchically in the Shapp library was proposed to better manage the execution of these tasks. Many different task group architectures are possible; we focus on tree-like calculations that are suitable for many problems where the range of possible parallelism increases as the calculations progress.
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