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Journal articles on the topic 'Scheduling, data management, grid computing'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Cao, Junwei, Stephen A. Jarvis, Subhash Saini, Darren J. Kerbyson, and Graham R. Nudd. "ARMS: An Agent-Based Resource Management System for Grid Computing." Scientific Programming 10, no. 2 (2002): 135–48. http://dx.doi.org/10.1155/2002/910792.

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Resource management is an important component of a grid computing infrastructure. The scalability and adaptability of such systems are two key challenges that must be addressed. In this work an agent-based resource management system, ARMS, is implemented for grid computing. ARMS utilises the performance prediction techniques of the PACE toolkit to provide quantitative data regarding the performance of complex applications running on a local grid resource. At the meta-level, a hierarchy of homogeneous agents are used to provide a scalable and adaptable abstraction of the system architecture. Ea

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Pei, Yun Xia, and Yue Zhang. "The Map-Reduce Parallelism Framework for Task Scheduling in Grid Computing." Advanced Materials Research 216 (March 2011): 111–15. http://dx.doi.org/10.4028/www.scientific.net/amr.216.111.

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As a rapid developing infrastructure, the grid can share widely distributed computing, storage, data and human resources. In order to improve the usability and QoS of the grid, the job management in the grid is very important, and becomes one of the key research issues in grid computing. Map-Reduce provide an efficient and easy-to-use framework for parallelizing the global optimization procedure. The simulation results show the usefulness and effectiveness of our task scheduling algorithm.

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Adamski, Marcin, Krzysztof Kurowski, Marek Mika, Wojciech Piątek, and Jan Węglarz. "Security Aspects in Resource Management Systems in Distributed Computing Environments." Foundations of Computing and Decision Sciences 42, no. 4 (2017): 299–313. http://dx.doi.org/10.1515/fcds-2017-0015.

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Abstract In many distributed computing systems, aspects related to security are getting more and more relevant. Security is ubiquitous and could not be treated as a separated problem or a challenge. In our opinion it should be considered in the context of resource management in distributed computing environments like Grids and Clouds, e.g. scheduled computations can be much delayed because of cyber-attacks, inefficient infrastructure or users valuable and sensitive data can be stolen even in the process of correct computation. To prevent such cases there is a need to introduce new evaluation m

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Pujiyanta, Ardi, Lukito Edi Nugroho, and Widyawan Widyawan. "Resource allocation model for grid computing environment." International Journal of Advances in Intelligent Informatics 6, no. 2 (2020): 185. http://dx.doi.org/10.26555/ijain.v6i2.496.

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Grid computing is a collection of heterogeneous resources that is highly dynamic and unpredictable. It is typically used for solving scientific or technical problems that require a large number of computer processing cycles or access to substantial amounts of data. Various resource allocation strategies have been used to make resource use more productive, with subsequent distributed environmental performance increases. The user sends a job by providing a predetermined time limit for running that job. Then, the scheduler gives priority to work according to the request and scheduling policy and

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Khorsheed, Murad B., Qasim M. Zainel, Oday A. Hassen, and Saad M. Darwish. "The Application of Fractal Transform and Entropy for Improving Fault Tolerance and Load Balancing in Grid Computing Environments." Entropy 22, no. 12 (2020): 1410. http://dx.doi.org/10.3390/e22121410.

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This paper applies the entropy-based fractal indexing scheme that enables the grid environment for fast indexing and querying. It addresses the issue of fault tolerance and load balancing-based fractal management to make computational grids more effective and reliable. A fractal dimension of a cloud of points gives an estimate of the intrinsic dimensionality of the data in that space. The main drawback of this technique is the long computing time. The main contribution of the suggested work is to investigate the effect of fractal transform by adding R-tree index structure-based entropy to exis

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Liu, Lin, Jian Guo, Jianyu Luo, Xiongfeng Xu, Kaiming Luo, and Shengming Wang. "Advance Evaluation of System Protection Control Strategy Based on Multi-scheme Concurrency." E3S Web of Conferences 252 (2021): 01038. http://dx.doi.org/10.1051/e3sconf/202125201038.

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According to rapid assessment requirement of system protection control strategy adaptability in future operation mode, combining with application status of distributed computing for power system security and stability analysis, based on design idea of asynchronism and concurrency, this paper proposes a multi-scheme concurrent computing framework suitable for coarse-grained case parallelism. By the way of multi-data section parallel, the asynchronous and concurrent scheduling management of computing task of multiple application functions under different sections is realized, which effectively i

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Ji, Xin, Da Hua Zhang, and De Yue Men. "Research on Heterogeneous Cloud Service Model for Smart Grid Business Application." Advanced Materials Research 860-863 (December 2013): 2427–33. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2427.

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With the construction of smart grid and centralized data center, traditional information technology management mode already cannot meet the requirements on the timeliness and flexibility. Cloud computing technology can solve the complicated calculation, mass data processing, and network dynamic migration issues for electric power business, but when in the face of different business applications demand, due to the heterogeneous resources variety of applications bottleneck will be produced, difficult to achieve real "smart". In view of the smart grid application scenarios, heterogeneous resource

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Shahryari, Om-Kolsoom, Amjad Anvari-Moghaddam, and Shadi Shahryari. "Demand side management using the internet of energy based on LoRaWAN technology." Kurdistan Journal of Applied Research 2, no. 3 (2017): 112–19. http://dx.doi.org/10.24017/science.2017.3.35.

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The smart grid, as a communication network, allows numerous connected devices such as sensors, relays and actuators to interact and cooperate with each other. An Internet-based solution for electricity that provides bidirectional flow of information and power is internet of energy (IoE) which is an extension of smart grid concept. A large number of connected devices and the huge amount of data generated by IoE and issues related to data transmission, process and storage, force IoE to be integrated by cloud computing. Furthermore, in order to enhance the performance and reduce the volume of tra

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Gupta, Punit, and Deepika Agrawal. "Trusted Cloud Platform for Cloud Infrastructure." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 10, no. 8 (2013): 1884–91. http://dx.doi.org/10.24297/ijct.v10i8.1473.

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Reliability and trust Models are used to enhance secure , reliable scheduling , load balancing and QoS in cloud and Distributed environment. Trust models that are being used in Distributed and Grid environment, does not qualify cloud computing environment requirements. Since the parameters that have being taken into consideration in these trust models, does not fit in the cloud Infrastructure As A Service, a suitable trust model is proposed based on the existing model that is suitable for trust value management for the cloud IaaS parameters. Based on the above achieved trust values,Â trust bas

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SANDHOLM, THOMAS, PETER GARDFJÄLL, ERIK ELMROTH, OLLE MULMO, and LENNART JOHNSSON. "A SERVICE-ORIENTED APPROACH TO ENFORCE GRID RESOURCE ALLOCATIONS." International Journal of Cooperative Information Systems 15, no. 03 (2006): 439–59. http://dx.doi.org/10.1142/s0218843006001426.

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We present the SweGrid Accounting System (SGAS) — a decentralized and standards-based system for Grid resource allocation enforcement that has been developed with an emphasis on a uniform data model and easy integration into existing scheduling and workload management software. The system has been tested at the six high-performance computing centers comprising the SweGrid computational resource, and addresses the need for soft, real-time quota enforcement across the SweGrid clusters. The SGAS framework is based on state-of-the-art Web and Grid services technologies. The openness and ubiquity o

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Ostermann, Simon, Kassian Plankensteiner, and Radu Prodan. "Using a New Event-Based Simulation Framework for Investigating Resource Provisioning in Clouds." Scientific Programming 19, no. 2-3 (2011): 161–78. http://dx.doi.org/10.1155/2011/267153.

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Today, Cloud computing proposes an attractive alternative to building large-scale distributed computing environments by which resources are no longer hosted by the scientists' computational facilities, but leased from specialised data centres only when and for how long they are needed. This new class of Cloud resources raises new interesting research questions in the fields of resource management, scheduling, fault tolerance, or quality of service, requiring hundreds to thousands of experiments for finding valid solutions. To enable such research, a scalable simulation framework is typically r

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VADHIYAR, SATHISH S., and JACK J. DONGARRA. "SRS: A FRAMEWORK FOR DEVELOPING MALLEABLE AND MIGRATABLE PARALLEL APPLICATIONS FOR DISTRIBUTED SYSTEMS." Parallel Processing Letters 13, no. 02 (2003): 291–312. http://dx.doi.org/10.1142/s0129626403001288.

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The ability to produce malleable parallel applications that can be stopped and reconfigured during the execution can offer attractive benefits for both the system and the applications. The reconfiguration can be in terms of varying the parallelism for the applications, changing the data distributions during the executions or dynamically changing the software components involved in the application execution. In distributed and Grid computing systems, migration and reconfiguration of such malleable applications across distributed heterogeneous sites which do not share common file systems provide

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Kosar, Tevfik, and Mehmet Balman. "A new paradigm: Data-aware scheduling in grid computing." Future Generation Computer Systems 25, no. 4 (2009): 406–13. http://dx.doi.org/10.1016/j.future.2008.09.006.

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14

Buyya, Rajkumar, David Abramson, Jonathan Giddy, and Heinz Stockinger. "Economic models for resource management and scheduling in Grid computing." Concurrency and Computation: Practice and Experience 14, no. 13-15 (2002): 1507–42. http://dx.doi.org/10.1002/cpe.690.

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15

Gao, Xiao Bo. "An Efficient Resources Management Model and Task Scheduling Algorithm in Grid Computing." Applied Mechanics and Materials 50-51 (February 2011): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.526.

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From the perspective of resource sharing, grid computing is a system ranging from small kind of network system for home using to large-scale network computing systems even to the Internet. The management of resources in the grid environment becomes very complex as these resources are distributed geographically, heterogeneous in nature, and each having their own resource management policies and different access as well as cost models. In this paper, we bring forward an efficient resources management model and task scheduling algorithm in grid computing. The simulation results show that the prop

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16

Yousaf, Muhammad Murtaza, and Michael Welzl. "Network-Aware HEFT Scheduling for Grid." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/317284.

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We present a network-aware HEFT. The original HEFT does not take care of parallel network flows while designing its schedule for a computational environment where computing nodes are physically at distant locations. In the proposed mechanism, such data transfers are stretched to their realistic completion time. A HEFT schedule with stretched data transfers exhibits the realisticmakespanof the schedule. It is shown how misleading a schedule can be if the impact of parallel data transfers that share a bottleneck is ignored. A network-aware HEFT can be used to yield a benefit for Grid application

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Aloisio, Giovanni, Massimo Cafaro, Euro Blasi, and Italo Epicoco. "The Grid Resource Broker, A Ubiquitous Grid Computing Framework." Scientific Programming 10, no. 2 (2002): 113–19. http://dx.doi.org/10.1155/2002/969307.

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Portals to computational/data grids provide the scientific community with a friendly environment in order to solve large-scale computational problems. The Grid Resource Broker (GRB) is a grid portal that allows trusted users to create and handle computational/data grids on the fly exploiting a simple and friendly web-based GUI. GRB provides location-transparent secure access to Globus services, automatic discovery of resources matching the user's criteria, selection and scheduling on behalf of the user. Moreover, users are not required to learn Globus and they do not need to write specialized

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18

Yuan, Shao Guang, Yong Li Zhu, Guo Liang Zhou, and Ming Kun Wang. "Research on Dynamic Scheduling of Grid Monitoring Data Processing Tasks Based Storm." Applied Mechanics and Materials 651-653 (September 2014): 1051–55. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1051.

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Development of smart grid spawned the big data in electric power industry, the cloud computing platform provided the solution for the big data in electric power industry, it has a significant effect for batch jobs, but its real-time is not guaranteed. For the real-time problem of cloud computing platform, the Storm platform will be introduced to monitor the grid power. This paper studies the fair share scheduling algorithm under the Storm platform. It introduced the concept of Storm framework briefly, then, proposed the fair share scheduling algorithm according to the lack of current Storm sch

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19

Nayyar, Anand, Rudra Rameshwar, and Piyush Kanti Dutta. "Special Issue on Recent Trends and Future of Fog and Edge Computing, Services and Enabling Technologies." Scalable Computing: Practice and Experience 20, no. 2 (2019): iii—vi. http://dx.doi.org/10.12694/scpe.v20i2.1558.

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Recent Trends and Future of Fog and Edge Computing, Services, and Enabling Technologies Cloud computing has been established as the most popular as well as suitable computing infrastructure providing on-demand, scalable and pay-as-you-go computing resources and services for the state-of-the-art ICT applications which generate a massive amount of data. Though Cloud is certainly the most fitting solution for most of the applications with respect to processing capability and storage, it may not be so for the real-time applications. The main problem with Cloud is the latency as the Cloud dat

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20

R, Ms Prema. "TBHR: A Dynamic Data Management in Grid Computing." International Journal for Research in Applied Science and Engineering Technology 7, no. 3 (2019): 2018–23. http://dx.doi.org/10.22214/ijraset.2019.3372.

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21

., B. Mallikarjuna. "INTELLIGENT GRID DATA MANAGEMENT IN CLOUD COMPUTING ENVIRONMENT." International Journal of Research in Engineering and Technology 05, no. 17 (2016): 38–44. http://dx.doi.org/10.15623/ijret.2016.0517008.

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22

Zhang, Yue, and Yun Xia Pei. "An Effective Grid Resource Management Model Based on Cloud Computing Platform." Applied Mechanics and Materials 50-51 (February 2011): 358–62. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.358.

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Resource management model was presented based on cloud computing using virtualization technologies. According to this strategy, a resource scheduling model was designed. This strategy can really effectively improve resource utilization rate. This algorithm met the needs of cloud computing more than others for grid environment with shorter response time and better performance, which were proved by the simulation results in the Gridsim environment.

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23

Patel, Surendra Kumar, and Anil Kumar Sharma. "Improved PSO based job scheduling algorithm for resource management in grid computing." International Journal of Advanced Technology and Engineering Exploration 6, no. 54 (2019): 152–61. http://dx.doi.org/10.19101/ijatee.2019.650021.

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24

Saravanan, G., and V. Gopalakrishnan. "Hybrid Genetic Algorithm based Proficient Resource Management and Scheduling in Grid Computing." Asian Journal of Research in Social Sciences and Humanities 6, no. 9 (2016): 1430. http://dx.doi.org/10.5958/2249-7315.2016.00881.9.

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25

Chen, Lei. "QoS-Constrained Resource Scheduling Base on Market Economy Models in Grid Computing." Applied Mechanics and Materials 443 (October 2013): 599–602. http://dx.doi.org/10.4028/www.scientific.net/amm.443.599.

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The Grid task scheduling algorithm is proposed that takes the service quality of resource scheduling, time and cost together into consideration, so that it can better meet user tasks Quality of Service (QoS) requirements and make the complex grid environment open. On the basis of the price model drove by supply and demand in economy, we design the Grid task scheduling algorithm in the market economy model. The experiment results indicate the effectiveness of proposed algorithm in terms of usersQoS guarantee. It reduce data access latency and decrease bandwidth consumption.

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Ou, Chao Chun, Jia Qing Zhang, and Xiao Hua Wang. "Grid Electricity Market Bidding Model Based on Agent." Advanced Materials Research 986-987 (July 2014): 322–25. http://dx.doi.org/10.4028/www.scientific.net/amr.986-987.322.

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Grid technology can provide electricity market bidding to achieve the ability to provide large-scale computing. Agent technology has the autonomy, interoperability, and self-learning, can effectively solve the grid resource discovery and management, computing task allocation and scheduling problems, shared grid environment of heterogeneous computing resources. Introduction grid technology related content, Agent technology and proposes a use of Agent technology in the electricity market bidding model grid environment. Bidding able to provide the technology platform the parties a fair trade.

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Li, Chunlin, and Layuan Li. "Energy Efficient Resource Management in Mobile Grid." Mobile Information Systems 6, no. 2 (2010): 193–211. http://dx.doi.org/10.1155/2010/850748.

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Energy efficient computing has recently become hot research area. Many works have been carried out on conserving energy, but considering energy efficiency in grid computing is few. This paper proposes energy efficient resource management in mobile grid. The objective of energy efficient resource management in mobile grid is to maximize the utility of the mobile grid which is denoted as the sum of grid application utility. The utility function models benefits of application and system. By using nonlinear optimization theory, energy efficient resource management in mobile grid can be formulated

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BEAUMONT, O., A. LEGRAND, L. MARCHAL, and Y. ROBERT. "SCHEDULING STRATEGIES FOR MIXED DATA AND TASK PARALLELISM ON HETEROGENEOUS CLUSTERS." Parallel Processing Letters 13, no. 02 (2003): 225–44. http://dx.doi.org/10.1142/s0129626403001252.

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We consider the execution of a complex application on a heterogeneous "grid" computing platform. The complex application consists of a suite of identical, independent problems to be solved. In turn, each problem consists of a set of tasks. There are dependences (precedence constraints) between these tasks and these dependences are organized as a tree. A typical example is the repeated execution of the same algorithm on several distinct data samples. We use a non-oriented graph to model the grid platform, where resources have different speeds of computation and communication. We show how to det

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R, Ms Prema. "Efficient Data Management in Grid Computing using DMDR Algorithm." International Journal for Research in Applied Science and Engineering Technology 7, no. 3 (2019): 1300–1304. http://dx.doi.org/10.22214/ijraset.2019.3236.

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30

Kumar, Ajay. "Distributed and Big Data Storage Management in Grid Computing." International Journal of Grid Computing & Applications 3, no. 2 (2012): 19–28. http://dx.doi.org/10.5121/ijgca.2012.3203.

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31

Kurowski, K., B. Ludwiczak, J. Nabrzyski, A. Oleksiak, and J. Pukacki. "Dynamic Grid Scheduling with Job Migration and Rescheduling in the GridLab Resource Management System." Scientific Programming 12, no. 4 (2004): 263–73. http://dx.doi.org/10.1155/2004/892169.

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Grid computing has become one of the most important research topics that appeared in the field of computing in the last years. Simultaneously, we have noticed the growing popularity of new Web-based technologies which allow us to create application-oriented Grid middleware services providing capabilities required for dynamic resource and job management, monitoring, security, etc. Consequently, end users are able to get easier access to geographically distributed resources. In this paper we present the results of our experiments with the Grid(Lab) Resource Management System (GRMS), which acts o

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Zheng, Gui De, and Ming Chen. "Probabilistic State Estimation Based Scheduling Approach for Cloud Computing." Applied Mechanics and Materials 55-57 (May 2011): 1053–57. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.1053.

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The next generation of scientific experiments and studies are being carried out by large collaborations of researchers distributed around the world engaged in analysis of huge collections of data generated by scientific instruments. Grid computing has emerged as an enabler for such collaborations as it aids communities in sharing resource to achieve common objective. This paper defines the problem of scheduling distributed data-intensive application on to Gird resource and presents a formal resource and application model for the problem.

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Vashisht, Priyanka, Rajesh Kumar, and Anju Sharma. "Efficient Dynamic Replication Algorithm Using Agent for Data Grid." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/767016.

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In data grids scientific and business applications produce huge volume of data which needs to be transferred among the distributed and heterogeneous nodes of data grids. Data replication provides a solution for managing data files efficiently in large grids. The data replication helps in enhancing the data availability which reduces the overall access time of the file. In this paper an algorithm, namely, EDRA using agents for data grid, has been proposed and implemented. EDRA consists of dynamic replication of hierarchical structure taken into account for the selection of best replica. Decisio

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Mansouri, Najme. "A Hybrid Approach for Scheduling based on Multi-criteria Decision Method in Data Grid." Computer Engineering and Applications Journal 3, no. 1 (2014): 1–12. http://dx.doi.org/10.18495/comengapp.v3i1.44.

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Grid computing environments have emerged following the demand of scientists to have a very high computing power and storage capacity. One among the challenges imposed in the use of these environments is the performance problem. To improve performance, scheduling technique is used. Most existing scheduling strategies in Grids only focus on one kind of Grid jobs which can be data-intensive or computation-intensive. However, only considering one kind of jobs in scheduling does not result in suitable scheduling in the viewpoint of all system, and sometimes causes wasting of resources on the other

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Goswami, Sukalyan, and Ajanta De Sarkar. "Service Oriented Load Balancing Framework in Computational Grid Environment." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 9, no. 3 (2013): 1091–98. http://dx.doi.org/10.24297/ijct.v9i3.3334.

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Grid computing or computational grid has become a vast research field in academics. It is a promising platform that provides resource sharing through multi-institutional virtual organizations for dynamic problem solving. Such platforms are much more cost-effective than traditional high performance computing systems. Due to the provision of scalability of resources, these days grid computing has become popular in industry as well. However, computational grid has different constraints and requirements to those of traditional high performance computing systems. In order to fully exploit such grid

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Yu, Jia, and Rajkumar Buyya. "Scheduling Scientific Workflow Applications with Deadline and Budget Constraints Using Genetic Algorithms." Scientific Programming 14, no. 3-4 (2006): 217–30. http://dx.doi.org/10.1155/2006/271608.

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Grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models, which are capable of supporting diverse computing services. It facilitates scientific applications to take advantage of computing resources distributed world wide to enhance the capability and performance. Many scientific applications in areas such as bioinformatics and astronomy require workflow processing in which tasks are executed based on their control or data dependencies. Scheduling such interdependent tasks on utility Grid environments

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Yahaya, Bakri, Rohaya Latip, Azizol Abdullah, and Mohamed Othman. "RESOURCE BROKER MANAGEMENT BY ADOPTING SELF-ADAPTIVE MULTI-INSTANCE BROKER SCHEDULING IN GRID COMPUTING." Journal of Computer Science 10, no. 12 (2014): 2553–63. http://dx.doi.org/10.3844/jcssp.2014.2553.2563.

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Meddeber, Meriem, and Belabbas Yagoubi. "Dependent tasks assignment and data consistency management for grid computing." Multiagent and Grid Systems 15, no. 2 (2019): 179–96. http://dx.doi.org/10.3233/mgs-190308.

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Liu, Qian, Wen Ying Liu, and Guo Hua Gao. "PSO and OCCI-Based Grid Maintenance Scheduling Management and Optimization System." Applied Mechanics and Materials 380-384 (August 2013): 4716–19. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4716.

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Smart grid is an inevitable choice for the future development of the grid. Smart scheduling is one of the cores to build the strong and smart grid in China. Optimization and Management System for Grid Maintenance Scheduling is an in-depth exploration to achieve dispatching digitalization, intellectualization and visualization. This paper gives a rather detailed description about the functionality and implementation of Optimization and Management System for Grid Maintenance Scheduling. With received maintenance schedules as the basic data, OCCI-based data processing techniques and PSO-based opt

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Zhang, Lin. "Web-Based Data Translation for a Resource Management Grid." Advanced Materials Research 989-994 (July 2014): 4379–82. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4379.

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Grid environment as the cross field of semantic web and grid computing, has received significant attention recently. Our workgroup develops a resource management semantic grid named RM-Grid to enhance information process accuracy and efficiency in heterogeneity environment. This paper describes the architecture of RM-grid, mainly introduces the data translation service of RM-Grid. It puts forward an ontology based common semantic model and an XML based data model, presents the data translation algorithm between different data sources and an adapter framework for accessing distributed heterogen

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Tusa, Francesco, Massimo Villari, and Antonio Puliafito. "Credential Management Enforcement and Secure Data Storage in gLite." International Journal of Distributed Systems and Technologies 1, no. 1 (2010): 76–97. http://dx.doi.org/10.4018/jdst.2010090805.

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This article describes new security solutions for Grid middleware, and specifically faces the issues related to the management of users’ and servers’ credentials, together with storing and secure data transmission in the Grid. Our work, built on Grid Security Infrastructure (GSI), provides new capabilities (i.e. smart card Grid access, and strong security file storage XML-based) to be used on top of different Grid middlewares, with a low level of changes. This work is currently implemented on gLite and accomplishes the access to Grid resources in a uniform and transparent way. These improvemen

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Iqbal, Sana, Mohammad Sarfraz, Mohammad Ayyub, et al. "A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment." Sustainability 13, no. 13 (2021): 7170. http://dx.doi.org/10.3390/su13137170.

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The ever increasing demand for electricity and the rapid increase in the number of automatic electrical appliances have posed a critical energy management challenge for both utilities and consumers. Substantial work has been reported on the Home Energy Management System (HEMS) but to the best of our knowledge, there is no single review highlighting all recent and past developments on Demand Side Management (DSM) and HEMS altogether. The purpose of each study is to raise user comfort, load scheduling, energy minimization, or economic dispatch problem. Researchers have proposed different soft co

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Škrinárová, Jarmila, and Michal Povinský. "Parallel Simulation of Tasks Scheduling and Scheduling Criteria in High-performance Computing Systems." Journal of information and organizational sciences 43, no. 2 (2019): 221–28. http://dx.doi.org/10.31341/jios.43.2.5.

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This work is focused on the issue of job scheduling in a high performance computing systems. The goal is based on the analysis of scheduling models of tasks in grid and cloud, design and implementation of the simulator on the base of GPGPU. The simulator is verified by our own proposed model of job scheduling. The simulator consists of a centralized scheduler that is using GPGPU to process large amounts of data by parallel way. In order to ensure the optimization of the scheduling process we have implemented a simulated annealing algorithm. GPGPU model was compared to the CPU when the number o

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Suresh, P., and P. Balasubramanie. "User Demand Aware Grid Scheduling Model with Hierarchical Load Balancing." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/439362.

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Grid computing is a collection of computational and data resources, providing the means to support both computational intensive applications and data intensive applications. In order to improve the overall performance and efficient utilization of the resources, an efficient load balanced scheduling algorithm has to be implemented. The scheduling approach also needs to consider user demand to improve user satisfaction. This paper proposes a dynamic hierarchical load balancing approach which considers load of each resource and performs load balancing. It minimizes the response time of the jobs a

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Zhou, Guo Hong. "Study of Cloud Computing and Advanced Manufacturing Technology under Information Technology Development." Applied Mechanics and Materials 484-485 (January 2014): 227–30. http://dx.doi.org/10.4028/www.scientific.net/amm.484-485.227.

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Cloud computing can be regarded as the integration of grid computing and virtualization technology: namely the use of grid distributed computing processing power of IT resources and build into a resource pool, plus on a mature server virtualization, storage virtualization technology make users can real-time monitoring and deployment of resources. Cloud computing and advanced manufacturing technology is facing many challenges during the process of development in the future, including security and privacy will become a primary issue. This study focused on relations with the important areas of em

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Preve, Nikolaos. "SEGEDMA: Sensor grid enhancement data management system for Health Care computing." Expert Systems with Applications 38, no. 3 (2011): 2371–80. http://dx.doi.org/10.1016/j.eswa.2010.08.025.

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Vlădoiu, Monica, and Zoran Constantinescu. "Development Journey of QADPZ - A Desktop Grid Computing Platform." International Journal of Computers Communications & Control 4, no. 1 (2009): 82. http://dx.doi.org/10.15837/ijccc.2009.1.2416.

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In this paper we present QADPZ, an open source system for desktop grid computing, which enables users of a local network or Internet to share resources. QADPZ allows a centralized management and use of the computational resources of idle computers from a network of desktop computers. QADPZ users can submit compute-intensive applications to the system, which are then automatically scheduled for execution. The scheduling is performed according to the hardware and software requirements of the application. Users can later monitor and control the execution of the applications. Each application cons

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Rahman, Ashiqur Md, and Rashedur M. Rahman. "CAPM Indexed Hybrid E-Negotiation for Resource Allocation in Grid Computing." International Journal of Grid and High Performance Computing 5, no. 2 (2013): 72–91. http://dx.doi.org/10.4018/jghpc.2013040105.

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Computational Grids are a promising platform for executing large-scale resource intensive applications. This paper identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economy-based Grid systems, and proposes an economy based negotiation system protocol for cooperative and competitive trading of resources. Dynamic pricing for services and good level of Pareto optimality make auction

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Yacouba, Yazid Hambally, Amadou Diabagaté, Abdou Maiga, and Adama Coulibaly. "Multi-agent System for Management of Data from Electrical Smart Meters." International Journal of Information Technology and Computer Science 13, no. 1 (2021): 18–43. http://dx.doi.org/10.5815/ijitcs.2021.01.02.

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The smart meter can process sensor data in a residential grid. These sensors transmit different parameters or measurement data (index, power, temperature, fluctuation of voltage and electricity, etc.) to the smart meter. All of these measurement data can come in different ways at the smart meter. The sensors transmit each measurement data to the smart meter. In addition, the collection of this data to a central system is a significant concern to ensure data integrity and protect the privacy of residents. The complexity of these data management also lies in their volume, frequency, and scheduli

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Siddesh, G. M., and K. G. Srinisas. "An Adaptive Scheduler Framework for Complex Workflow Jobs on Grid Systems." International Journal of Distributed Systems and Technologies 3, no. 4 (2012): 63–79. http://dx.doi.org/10.4018/jdst.2012100106.

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Grid Computing provides sharing of geographically distributed resources among large scale complex applications. Due to dynamic nature of resources in grid, there is a need of highly efficient job scheduling and resource management policies in grid. A novel Grid Resource Scheduler (GRS) is proposed to effectively utilize the available resources in Grid. Proposed GRS contributes, an optimal job scheduling algorithm on Job Rank-Backfilling policy and a resource matching algorithm based on ranking of resources with best fit allocation model. Performance of GRS is measured by considering a web base

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