Relevant bibliographies by topics / Scheduling, data management, grid computing

Contents

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

Academic literature on the topic 'Scheduling, data management, grid computing'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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

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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. Each agent is able to cooperate with other agents and thereby provide service advertisement and discovery for the scheduling of applications that need to utilise grid resources. A case study with corresponding experimental results is included to demonstrate the efficiency of the resource management and scheduling system.
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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 metrics for resource management that will represent the level of security of computing resources and more broadly distributed computing infrastructures. In our approach, we have introduced a new metric called reputation, which simply determines the level of reliability of computing resources from the security perspective and could be taken into account during scheduling procedures. The new reputation metric is based on various relevant parameters regarding cyber-attacks (also energy attacks), administrative activities such as security updates, bug fixes and security patches. Moreover, we have conducted various computational experiments within the Grid Scheduling Simulator environment (GSSIM) inspired by real application scenarios. Finally, our experimental studies of new resource management approaches taking into account critical security aspects are also discussed in this paper.
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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 places it in the waiting queue. When the resource is released, the scheduler selects the job from the waiting queue with a specific algorithm. Requests will be rejected if the required resources are not available. The user can re-submit a new request by modifying the parameter until available resources can be found. Eventually, there is a decrease in idle resources between work and resource utilization, and the waiting time will increase. An effective scheduling policy is required to improve resource use and reduce waiting times. In this paper, the FCFS-LRH method is proposed, where jobs received will be sorted by arrival time, execution time, and the number of resources needed. After the sorting process, the work will be placed in a logical view, and the job will be sent to the actual resource when it executes. The experimental results show that the proposed model can increase resource utilization by 1.34% and reduce waiting time by 20.47% when compared to existing approaches. This finding could be beneficially implemented in cloud systems resource allocation management.
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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 existing grid computing models to obtain a balanced infrastructure with minimal fault. In this regard, the presented work is going to extend the commonly scheduling algorithms that are built based on the physical grid structure to a reduced logical network. The objective of this logical network is to reduce the searching in the grid paths according to arrival time rate and path’s bandwidth with respect to load balance and fault tolerance, respectively. Furthermore, an optimization searching technique is utilized to enhance the grid performance by investigating the optimum number of nodes extracted from the logical grid. The experimental results indicated that the proposed model has better execution time, throughput, makespan, latency, load balancing, and success rate.
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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 improves the utilization rate of computing resources and significantly reduces the computing period of advance evaluation of system protection control strategy adaptability. The technology has been applied in provincial power grid and its effectiveness has been verified.
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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 resources adaptation method is given respectively for computing, storage and network resources. Makes the heterogeneous resources can be shared centrally, allocate resources on demand, unified managing, dynamic scheduling, and loaded balancing, form heterogeneous resource pool. Based on heterogeneous resource pool, build the heterogeneous cloud service model, and carried out preliminary design implementation, the availability of the model was verified.
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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 transmitted data and process information in an acceptable time, fog computing is suggested as a layer between IoE layer and cloud layer. This layer is used as a local processing level that leads to reduction in data transmissions to the cloud. So, it can save energy consumption used by IoE devices to transmit data into cloud because of a long range, low power, wide area and low bit rate wireless telecommunication system which is called LoRaWAN. All devices in fog domain are connected by long range wide area network (LoRa) into a smart gateway. The gateway which bridges fog domain and cloud, is introduced for scheduling devices/appliances by creating a priority queue which can perform demand side management dynamically. The queue is affected by not only the consumer importance but also the consumer policies and the status of energy resources.
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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, trust based scheduling and load balancing is done for better allocation of resources and enhancing the QOS of services been provided to the users. In this paper, an trust based cloud computing framework is proposed using trust model ,trust based scheduling and load balancing algorithms. Here we describe the design and development of trusted Cloud service model for cloud Infrastructure as a service (IaaS) known as VimCloud .VimCloud an open source cloud computing framework that implements the tusted Cloud Service Model and trust based scheduling and load balancing algorithm . However one of the major issues in cloud IaaS is to ensure reliability and security or used data and computation. Trusted cloud service model ensures that user virual machine executes only on trusted cloud node, whose integrity and reliability is known in term of trust value . VimCloud shown practical in term of performace which is better then existing models.
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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 of Web services combined with the fine-grained resource control and cross-organizational security models of Grid services proved to be a perfect match for the SweGrid needs. Extensibility and customizability of policy implementations for the three different parties that the system serves (the user, the resource manager, and the allocation authority) are key design goals. Another goal is end-to-end security and single sign-on, to allow resources to reserve allocations and charge for resource usage on behalf of the user. We conclude this paper by illustrating the policy customization capabilities of SGAS in a simulated setting, where job streams are shaped using different modes of allocation policy enforcement. Finally, we discuss some of the early experiences from the production system.
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Dissertations / Theses on the topic "Scheduling, data management, grid computing"

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Agarwalla, Bikash Kumar. "Resource management for data streaming applications." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34836.

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This dissertation investigates novel middleware mechanisms for building streaming applications. Developing streaming applications is a challenging task because (i) they are continuous in nature; (ii) they require fusion of data coming from multiple sources to derive higher level information; (iii) they require efficient transport of data from/to distributed sources and sinks; (iv) they need access to heterogeneous resources spanning sensor networks and high performance computing; and (v) they are time critical in nature. My thesis is that an intuitive programming abstraction will make it easier to build dynamic, distributed, and ubiquitous data streaming applications. Moreover, such an abstraction will enable an efficient allocation of shared and heterogeneous computational resources thereby making it easier for domain experts to build these applications. In support of the thesis, I present a novel programming abstraction, called DFuse, that makes it easier to develop these applications. A domain expert only needs to specify the input and output connections to fusion channels, and the fusion functions. The subsystems developed in this dissertation take care of instantiating the application, allocating resources for the application (via the scheduling heuristic developed in this dissertation) and dynamically managing the resources (via the dynamic scheduling algorithm presented in this dissertation). Through extensive performance evaluation, I demonstrate that the resources are allocated efficiently to optimize the throughput and latency constraints of an application.
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Vernois, Antoine. "Ordonnancement et réplication de données bioinformatiques dans un contexte de grille de calcul." Lyon, École normale supérieure (sciences), 2006. http://www.theses.fr/2006ENSL0368.

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Au cours de cette thèse, nous nous sommes placés dans le contexte bien &gt; particulier d'une catégorie d'applications bioinformatiques dont les &gt; caractéristiques sont d'utiliser des banques de données de références en &gt; lecture seule et d'avoir un coût en temps de calcul affine en la taille des &gt; données. Une autre caractéristique concernant l'utilisation de ces &gt; applications est que leur schéma d'utilisation reste constant dans le &gt; temps. Dans ce cadre, nous avons défini un algorithme basé sur un programme &gt; linéaire permettant de calculer un ordonnancement et un placement statique &gt; des données optimisant le rendement d'une plate-forme de type grille de &gt; calcul. Grâce au simulateur Optorsim que nous avons largement modifié, nous &gt; avons montré les bons résultats de notre algorithme lorsque l'espace de &gt; stockage sur les noeuds de calcul ou le débit du réseau connectant les &gt; différents sites sont des points critiques. &gt; Nous avons ensuite établi un ensemble d'heuristiques dont le but est de &gt; palier à d'éventuels changements dans les schémas d'utilisation des banques &gt; de données. Là encore, nous avons utilisé Optorsim pour montrer et &gt; comprendre l'impact de ces différentes heuristiques. Il en découle que dans &gt; la plupart des cas, nous sommes en mesure de conserver une utilisation &gt; presque optimale de la plate-forme, même lorsque les requêtes qui arrivent &gt; sont très différentes du schéma d'utilisation utilisé pour le placement &gt; initial. Enfin, nous avons réalisé un prototype du système basé sur &gt; l'ordonnancement et le placement statique au sein de l'intergiciel de &gt; grille DIET. Ce prototype, déployé sur un ensemble de noeuds de la &gt; plate-forme Grid 5000, nous a permis de montrer l'efficacité de notre &gt; méthode dans un environnement réel<br>In this thesis, we focus on the specific context of a set of bioinformatic applications. Those applications have the particularity to use wellknown read-only databanks and a computation cost linear with the size of data. The other point is that the use of application and data is always the same. Within this context, we have developped an algorithm (Scheduling and Replication Algorithm, SRA) that combines data management and scheduling using steady-state approach. Using a model of the platform, the number of requests as well as their distribution, the number and size of databanks, we define a linear program to satisfy ball the constraints at every level of the platform in steady-state. The solution of this linear program will give us a placement for the databanks on the servers as well as providing, for each kind of job, the server on which they should be executed. With the OptorSim grid simulator, that we have merely improved, we have show good result when storage space or network bandwidth between grid nodes are critical resources. Then, we have design a set of heuristics that aims to adapt the scheduling and data placement when data use changes. These heuristics have also been tested with our version of OptorSim. The conclusion of these simulations is that, in most cases, our algorithm is able to keep an almost optimal use of computation resources even if usage scheme used for initial data placement are very different of the request that are really submitted. Finally, we have implemented a prototype of our static solution inside the DIET grid middleware. This prototype has been deployed on the Grid'5000 platform. The run of experiments in these real conditions has validated results of our simulations
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Tordsson, Johan. "Portable Tools for Interoperable Grids : Modular Architectures and Software for Job and Workflow Management." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-19630.

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The emergence of Grid computing infrastructures enables researchers to shareresources and collaborate in more efficient ways than before, despite belongingto different organizations and being geographically distributed. While the Gridcomputing paradigm offers new opportunities, it also gives rise to newdifficulties. This thesis investigates methods, architectures, and algorithmsfor a range of topics in the area of Grid resource management. One studiedtopic is how to automate and improve resource selection, despite heterogeneityin Grid hardware, software, availability, ownership, and usage policies.Algorithmical difficulties for this are, e.g., characterization of jobs andresources, prediction of resource performance, and data placementconsiderations. Investigated Quality of Service aspects of resource selectioninclude how to guarantee job start and/or completion times as well as how tosynchronize multiple resources for coordinated use through coallocation.Another explored research topic is architectural considerations for frameworksthat simplify and automate submission, monitoring, and fault handling for largeamounts of jobs. This thesis also investigates suitable Grid interactionpatterns for scientific workflows, studies programming models that enable dataparallelism for such workflows, as well as analyzes how workflow compositiontools should be designed to increase flexibility and expressiveness. We today have the somewhat paradoxical situation where Grids, originally aimed tofederate resources and overcome interoperability problems between differentcomputing platforms, themselves struggle with interoperability problems causedby the wide range of interfaces, protocols, and data formats that are used indifferent environments. This thesis demonstrates how proof-of-concept softwaretools for Grid resource management can, by using (proposed) standard formatsand protocols as well as leveraging state-of-the-art principles fromservice-oriented architectures, be made independent of current Gridinfrastructures. Further interoperability contributions include an in-depthstudy that surveys issues related to the use of Grid resources in scientificworkflows. This study improves our understanding of interoperability amongscientific workflow systems by viewing this topic from three differentperspectives: model of computation, workflow language, and executionenvironment. A final contribution in this thesis is the investigation of how the design ofGrid middleware tools can adopt principles and concepts from softwareengineering in order to improve, e.g., adaptability and interoperability.
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Smith, Andrew Cameron. "LHCb data management on the computing grid." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3018.

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The LHCb detector is one of the four experiments being built to harness the proton-proton collisions provided by the Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN). The data rate expected, when the LHC experiments are fully operational, eclipses that of any previous scientific experiments and has motivated the adoption of a grid computing paradigm to store and process the data. Managing PetaBytes of data in a distributed environment provides a rich set of challenges related to scalability, reliability and performance. This thesis will present the data management requirements for executing the workload of the LHCb collab- oration. We present the systems designed that support all aspects of the grid data management for LHCb, from data transfer, to data integrity, and efficient data access. The distributed computing environment is inherently unstable and much focus has been made on providing systems that are ro- bust and resilient to observed failures.
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Buyya, Rajkumar 1970. "Economic-based distributed resource management and scheduling for grid computing." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/8760.

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Bsoul, Mohammad. "Economic scheduling in Grid computing using Tender models." Thesis, Loughborough University, 2007. https://dspace.lboro.ac.uk/2134/3094.

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Economic scheduling needs to be considered for Grid computing environment, because it gives an incentive for resource providers to supply their resources. Moreover, it enforces efficient use of resources, because the users have to pay for their use. Tendering is a suitable model for Grid scheduling because users start the negotiations for finding suitable resources for executing their jobs. Furthermore, the users specify their job requirements with their requests and therefore the resources reply with bids that are based on the cost of taking on the job and the availability of their processors. In this thesis, a framework for economic Grid scheduling using tendering is proposed. The framework entities such as users, brokers and resources employ tender/contract-net model to negotiate the prices and deadlines. The brokers' role is acting on behalf of users. During the negotiations, the entities aim to maximise their performance which is measured by a number of metrics. In order to evaluate the entities' performance under different scenarios, a Java- based simulator, called MICOSim, supporting event-driven simulation of economic Grid scheduling is presented. MICOSim can perform a simulation of more than one hundred entities faster than real time. It is concluded from the evaluation that users who are interested in increasing the job success rate and paying less for executing their jobs have to consider received prices to select the most appropriate bids, while users who are interested in improving the job average satisfaction rate have to consider either received completion time or both price and completion time to select the most suitable bids when the submission of jobs is static. The best broker strategy is the one that doesn't take into account meeting the job deadlines in the bids it sends to job owners. Finally, the resource strategy that considers the price to determine if to reply to a request or not is superior to other resource strategies. The only exception is employing this strategy with price that is too low. However, there is a tiny difference between the performances of different user strategies in dynamic submission. It is also concluded from the evaluation that broker strategies have the best performance when the revenue they target from the users is reasonable. Thus, the broker's aim has to be receiving reasonable revenue (neither too low nor too high) from acting on behalf of users. It is observed from the results that the strategy performance is influenced by the behaviour of other entities such as the submission time of user jobs. Finally, it is observed that the characteristics of entities have an effect on the performance of strategies. For example, the two user strategies that consider the received completion time and both price and completion time to determine if to accept a broker bid have similar performance, because of the existence of resources with various prices from cheap to expensive and existence of resources which don't care about the price paid for the execution. So, the price threshold doesn't have a large effect on the performance.
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Delgado, Javier. "A grid computing network platform for enhanced data management and visualization." FIU Digital Commons, 2007. http://digitalcommons.fiu.edu/etd/2766.

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This thesis presents a novel approach towards providing a collaboration environment by using Grid Computing. The implementation includes the deployment of a cluster attached to a mural display for high performance computing and visualization and a Grid-infrastructure for sharing storage space across a wide area network and easing the remote use of the computing resources. A medical data processing application is implemented on the platform. The outcome is enhanced use of remote storage facilities and quick return time for computationally-intensive problems. The central issue of this thesis work is thus one that focuses on the development of a secure distributed system for data management and visualization to respond to the need for more efficient interaction and collaboration between technical researchers and medical professionals. The proposed networked solution is envisioned such as to provide synergy for more collaboration on theoretical and experimental issues involving analysis, visualization, and data sharing across sites.
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Brodard, Zacharie. "Workflow management and scheduling in a cloud computing context." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249714.

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Public cloud providers have had a tremendous impact on the software engineering world recently by offering on-demand computing infrastructures and scalable managed solutions. The goal of this master degree project is to determine whether these services offered by public cloud providers can improve the design of workflow management and scheduling systems for data-driven workflows. A cloud based architecture for a distributed workflow management system was designed, implemented and experimented on. It allowed to confirm the value of cloud computing solutions to solve workflow scheduling problems, by allowing to efficiently launch workloads on elastic computing resources.<br>På senaste tiden har public cloud-leverantörer haft stor effekt på mjukvaruingenjörsvetenskapen genom att föreslå databehandlingsinfrastrukturer på begäran samt skalbara lösningar. Målet med detta examensarbete är att fastställa om dessa tjänster, som föreslås av public cloud-leverantörer, kan förbättra designen av arbetsflödeshantering och schemaläggningssystem för datastyrda arbetsflöden. En molnbaserad arkitektur för ett distribuerat system av arbetsflödeshantering utformades, implementerades och testades. Genom effektivt utnyttjande av elastiska datorresurser kunde värdet av molnlösningar för att lösa schemaläggningsproblem i arbetsflöden bekräftas.
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Espling, Daniel. "Enabling Technologies for Management of Distributed Computing Infrastructures." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-80129.

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Computing infrastructures offer remote access to computing power that can be employed, e.g., to solve complex mathematical problems or to host computational services that need to be online and accessible at all times. From the perspective of the infrastructure provider, large amounts of distributed and often heterogeneous computer resources need to be united into a coherent platform that is then made accessible to and usable by potential users. Grid computing and cloud computing are two paradigms that can be used to form such unified computational infrastructures. Resources from several independent infrastructure providers can be joined to form large-scale decentralized infrastructures. The primary advantage of doing this is that it increases the scale of the available resources, making it possible to address more complex problems or to run a greater number of services on the infrastructures. In addition, there are advantages in terms of factors such as fault-tolerance and geographical dispersion. Such multi-domain infrastructures require sophisticated management processes to mitigate the complications of executing computations and services across resources from different administrative domains. This thesis contributes to the development of management processes for distributed infrastructures that are designed to support multi-domain environments. It describes investigations into how fundamental management processes such as scheduling and accounting are affected by the barriers imposed by multi-domain deployments, which include technical heterogeneity, decentralized and (domain-wise) self-centric decision making, and a lack of information on the state and availability of remote resources. Four enabling technologies or approaches are explored and developed within this work: (I) The use of explicit definitions of cloud service structure as inputs for placement and management processes to ensure that the resulting placements respect the internal relationships between different service components and any relevant constraints. (II) Technology for the runtime adaptation of Virtual Machines to enable the automatic adaptation of cloud service contexts in response to changes in their environment caused by, e.g., service migration across domains. (III) Systems for managing meta-data relating to resource usage in multi-domain grid computing and cloud computing infrastructures. (IV) A global fairshare prioritization mechanism that enables computational jobs to be consistently prioritized across a federation of several decentralized grid installations. Each of these technologies will facilitate the emergence of decentralized computational infrastructures capable of utilizing resources from diverse infrastructure providers in an automatic and seamless manner.<br><p>Note that the author changed surname from Henriksson to Espling in 2011</p>
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Radwan, Ahmed M. "Information Integration in a Grid Environment Applications in the Bioinformatics Domain." Scholarly Repository, 2010. http://scholarlyrepository.miami.edu/oa_dissertations/509.

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Grid computing emerged as a framework for supporting complex operations over large datasets; it enables the harnessing of large numbers of processors working in parallel to solve computing problems that typically spread across various domains. We focus on the problems of data management in a grid/cloud environment. The broader context of designing a services oriented architecture (SOA) for information integration is studied, identifying the main components for realizing this architecture. The BioFederator is a web services-based data federation architecture for bioinformatics applications. Based on collaborations with bioinformatics researchers, several domain-specific data federation challenges and needs are identified. The BioFederator addresses such challenges and provides an architecture that incorporates a series of utility services; these address issues like automatic workflow composition, domain semantics, and the distributed nature of the data. The design also incorporates a series of data-oriented services that facilitate the actual integration of data. Schema integration is a core problem in the BioFederator context. Previous methods for schema integration rely on the exploration, implicit or explicit, of the multiple design choices that are possible for the integrated schema. Such exploration relies heavily on user interaction; thus, it is time consuming and labor intensive. Furthermore, previous methods have ignored the additional information that typically results from the schema matching process, that is, the weights and in some cases the directions that are associated with the correspondences. We propose a more automatic approach to schema integration that is based on the use of directed and weighted correspondences between the concepts that appear in the source schemas. A key component of our approach is a ranking mechanism for the automatic generation of the best candidate schemas. The algorithm gives more weight to schemas that combine the concepts with higher similarity or coverage. Thus, the algorithm makes certain decisions that otherwise would likely be taken by a human expert. We show that the algorithm runs in polynomial time and moreover has good performance in practice. The proposed methods and algorithms are compared to the state of the art approaches. The BioFederator design, services, and usage scenarios are discussed. We demonstrate how our architecture can be leveraged on real world bioinformatics applications. We preformed a whole human genome annotation for nucleosome exclusion regions. The resulting annotations were studied and correlated with tissue specificity, gene density and other important gene regulation features. We also study data processing models on grid environments. MapReduce is one popular parallel programming model that is proven to scale. However, using the low-level MapReduce for general data processing tasks poses the problem of developing, maintaining and reusing custom low-level user code. Several frameworks have emerged to address this problem; these frameworks share a top-down approach, where a high-level language is used to describe the problem semantics, and the framework takes care of translating this problem description into the MapReduce constructs. We highlight several issues in the existing approaches and alternatively propose a novel refined MapReduce model that addresses the maintainability and reusability issues, without sacrificing the low-level controllability offered by directly writing MapReduce code. We present MapReduce-LEGOS (MR-LEGOS), an explicit model for composing MapReduce constructs from simpler components, namely, "Maplets", "Reducelets" and optionally "Combinelets". Maplets and Reducelets are standard MapReduce constructs that can be composed to define aggregated constructs describing the problem semantics. This composition can be viewed as defining a micro-workflow inside the MapReduce job. Using the proposed model, complex problem semantics can be defined in the encompassing micro-workflow provided by MR-LEGOS while keeping the building blocks simple. We discuss the design details, its main features and usage scenarios. Through experimental evaluation, we show that the proposed design is highly scalable and has good performance in practice.
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Books on the topic "Scheduling, data management, grid computing"

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Distributed data management for grid computing. John Wiley, 2005.

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Stefano, Michael Di. Distributed Data Management for Grid Computing. John Wiley & Sons, Ltd., 2005.

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Di Stefano, Michael. Distributed Data Management for Grid Computing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471738220.

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Di Stefano, Michael. Distributed Data Management for Grid Computing. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471738220.

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Eric, Yen, and SpringerLink (Online service), eds. Grid Computing: International Symposium on Grid Computing (ISGC 2007). Springer US, 2009.

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Neelanarayanan, ed. Secure Data Management And Transaction of Heterogeneous Large Data Sets In Grid Computing Environment. Association of Scientists, Developers and Faculties, 2014.

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Grid and cloud database management. Springer, 2011.

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C, Leung Clement H., and Rahayu Johanna Wenny, eds. High performance parallel database processing and grid databases. J. Wiley, 2008.

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Min, Tjoa A., and SpringerLink (Online service), eds. Data Management in Grid and Peer-to-Peer Systems: Second International Conference, Globe 2009 Linz, Austria, September 1-2, 2009 Proceedings. Springer Berlin Heidelberg, 2009.

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Khadeer, Hussain Farookh, Morvan Franck, Tjoa A. Min, and SpringerLink (Online service), eds. Data Management in Cloud, Grid and P2P Systems: 5th International Conference, Globe 2012, Vienna, Austria, September 5-6, 2012. Proceedings. Springer Berlin Heidelberg, 2012.

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Book chapters on the topic "Scheduling, data management, grid computing"

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Hoschek, Wolfgang, Javier Jaen-Martinez, Asad Samar, Heinz Stockinger, and Kurt Stockinger. "Data Management in an International Data Grid Project." In Grid Computing — GRID 2000. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44444-0_8.

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Ranganathan, Kavitha, and Ian Foster. "Computation Scheduling and Data Replication Algorithms for Data Grids." In Grid Resource Management. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0509-9_22.

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Nitzberg, Bill, Jennifer M. Schopf, and James Patton Jones. "PBS Pro: Grid Computing and Scheduling Attributes." In Grid Resource Management. Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0509-9_13.

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Moreno, Rafael, and Ana B. Alonso-Conde. "Job Scheduling and Resource Management Techniques in Economic Grid Environments." In Grid Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24689-3_4.

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Liu, Lilan, Tao Yu, Zhanbei Shi, and Minglun Fang. "Resource Management and Scheduling in Manufacturing Grid." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_18.

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Zheng, Ran, and Hai Jin. "An Integrated Management and Scheduling Scheme for Computational Grid." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_7.

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Giacomin, Pierpaolo, Alessandro Bassi, Frank J. Seinstra, and Thilo Kielmann. "Towards Coordinated Data Management For High-Performance Distributed Multimedia Content Analysis." In Grid Computing. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-09457-1_12.

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He, Xiaoshan, and Xian-He Sun. "Incorporating Data Movement into Grid Task Scheduling." In Grid and Cooperative Computing - GCC 2005. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11590354_49.

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Stockinger, Heinz, Omer F. Rana, Reagan Moore, and Andre Merzky. "Data Management for Grid Environments." In High-Performance Computing and Networking. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-48228-8_16.

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Yang, Shaofeng, Zeyad Ali, Houssain Kettani, Vinti Verma, and Qutaibah Malluhi. "Network Storage Management in Data Grid Environment." In Grid and Cooperative Computing. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24680-0_138.

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Conference papers on the topic "Scheduling, data management, grid computing"

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Wen Zhang, Junwei Cao, Yisheng Zhong, Lianchen Liu, and Cheng Wu. "An integrated resource management and scheduling system for grid data streaming applications." In 2008 9th IEEE/ACM International Conference on Grid Computing (GRID). IEEE, 2008. http://dx.doi.org/10.1109/grid.2008.4662807.

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Manfu Ma, Jian Wu, Shuyu Li, Dingjian Chen, and Zhengguo Hu. "A grid-distance based scheduling for grid resource management." In Eighth International Conference on High-Performance Computing in Asia-Pacific Region (HPCASIA'05). IEEE, 2005. http://dx.doi.org/10.1109/hpcasia.2005.4.

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Sha Fan. "Session Scheduling Algorithm of Grid Computing." In 2010 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010). IEEE, 2010. http://dx.doi.org/10.1109/wkdd.2010.87.

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Liu, Feng, Weiwei Guo, and Xiaomin Zhao. "Network Resource Management and Scheduling in Grid Computing." In 2018 International Conference on Robots & Intelligent System (ICRIS). IEEE, 2018. http://dx.doi.org/10.1109/icris.2018.00061.

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"Issues Related to Scheduling in Grid computing." In International conference on Intelligent Systems, Data Mining and Information Technology. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e0414074.

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Berral, Josep Ll, Ricard Gavalda, and Jordi Torres. "Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning." In 2011 12th IEEE/ACM International Conference on Grid Computing (GRID). IEEE, 2011. http://dx.doi.org/10.1109/grid.2011.18.

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Ma, Ruyue, Xiangxu Meng, and Shijun Liu. "Data Management System in Manufacturing Grid." In 2006 IEEE International Conference on Services Computing (SCC'06). IEEE, 2006. http://dx.doi.org/10.1109/scc.2006.40.

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Xu, Meng, Lizhen Cui, Haiyang Wang, Yanbing Bi, and Ji Bian. "A Data-Intensive Workflow Scheduling Algorithm for Grid Computing." In 2009 Fourth ChinaGrid Annual Conference (ChinaGrid). IEEE, 2009. http://dx.doi.org/10.1109/chinagrid.2009.30.

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Lin, Chih-Kuang, Vladimir Zadorozhny, and Prashant Krishnamurthy. "Grid-Based Access Scheduling for Mobile Data Intensive Sensor Networks." In 2008 9th International Conference on Mobile Data Management (MDM). IEEE, 2008. http://dx.doi.org/10.1109/mdm.2008.36.

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Sato, Hitoshi, and Satoshi Matsuoka. "Data Management on Grid Filesystem for Data-Intensive Computing." In 2007 International Symposium on Applications and the Internet Workshops. IEEE, 2007. http://dx.doi.org/10.1109/saint-w.2007.38.

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