New e-Learning system architecture based on knowledge engineering technology

The paper focuses on the field of research on next generational e-Learning facility, in which knowledge-enhanced systems are the most important candidates. In the paper, a reference architecture based on the technologies of knowledge engineering is proposed, which has following three intrinsic characteristics, first, education ontologies are used to facilitate the integration of static learning resource and dynamic learning resource, second, based on semantic-enriched relationships between Learning Objects (LOs), it provides more advanced features for sharing, reusing and repurposing of LOs, third, with the concept of knowledge object, which is extended from LO, an implementing mechanism for knowledge extraction and knowledge evolution in e-Learning facilities is provided. With this reference architecture, a prototype system called FekLoma (Flexible Extensive Knowledge Learning Object Management Architecture) has been realized, and testing on it is carrying out

Survey of grid resource monitoring and prediction strategies.

This literature focuses on grid resource monitoring and prediction, representative monitoring and prediction systems are analyzed and evaluated, then monitoring and prediction strategies for grid resources are summarized and discussed, recommendations are also given for building monitoring sensors and prediction models. During problem definition, one-step-ahead prediction is extended to multi-step-ahead prediction, which is then modeled with computational intelligence algorithms such as neural network and support vector regression. Numerical simulations are performed on benchmark data sets, while comparative results on accuracy and efficiency indicate that support vector regression models achieve superior performance. Our efforts can be utilized as direction for building online monitoring and prediction system for grid resources

A Performance-oriented Adaptive Scheduler For Dependent Tasks On Grids

A scheduler must consider the heterogeneity and communication delays when scheduling dependent tasks on a grid. The task-scheduling problem is NP-Complete in general, which led us to the development of a heuristic for the associated optimization problem. In this work we present a dynamic adaptive approach to schedule dependent tasks onto a grid based on the Xavantes grid middleware. The developed dynamic approach is applied to the Path Clustering Heuristic, and introduces the concept of rounds, which take turns sending tasks to execution and evaluating the performance of the resources. The adaptive extension changes the size of rounds during the process execution, taking task attributes and resources performance as parameters, and it can be adopted in other task schedulers. The experiments show that the dynamic round-based and adaptive schedule can minimize the effects of performance losses while executing processes on the grid. Copyright © 2007 John Wiley & Sons, Ltd.20910291049Bittencourt, L.F., Madeira, E.R.M., Cicerre, F.R.L., Buzato, L.E., A path clustering heuristic for scheduling task graphs onto a grid (short paper) (2005) Proceedings of the 3rd ACM International Workshop on Middleware for Grid Computing, , Grenoble, FranceCicerre, F.R.L., Madeira, E.R.M., Buzato, L.E., A hierarchical process execution support for grid computing (2006) Concurrency and Computation: Practice and Experience, 18 (6), pp. 581-594Kwok, Y.-K., Ahmad, I., Dynamic critical-path scheduling: An effective technique for allocating task graphs to multiprocessors (1996) IEEE Transactions on Parallel and Distributed Systems, 7 (5), pp. 506-521Yang T, Gerasoulis A. DSC: Scheduling parallel tasks on an unbounded number of processors. IEEE Transactions on Parallel and Distributed Systems 19945(9):951-967Bajaj, R., Agrawal, D.R., Improving scheduling of tasks in a heterogeneous environment (2004) IEEE Transactions on Parallel and Distributed Systems, 15 (2), pp. 107-118Sakellariou, R., Zhao, H., A hybrid heuristic for DAG scheduling on heterogeneous systems (2004) Proceedings of the 13th Heterogeneous Computing Workshop, pp. 111-124. , IEEE Computer Society Press: Los Alamitos, CATopcuoglu, H., Hariri, S., Wu, M.-Y., Performance-effective and low-complexity task scheduling for heterogeneous computing (2002) IEEE Transactions on Parallel and Distributed Systems, 13 (3), pp. 260-274Hagras, T., Janeček, J., An approach to compile-time task scheduling in heterogeneous computing systems (2004) Proceedings of the 33rd International Conference on Parallel Processing Workshops, pp. 182-189. , IEEE Computer Society Press: Los Alamitos, CAFrey, J., Condor DAGMan: Handling inter-job dependencies, , http://www.cs.wisc.edu/condor/dagman, 25 July 2006Prodan, R., Fahringer, T., Dynamic scheduling of scientific workflow applications on the grid: A case study (2005) Proceedings of the 2005 ACM Symposium on Applied computing (SAC'05), pp. 687-694. , ACM Press: New YorkChen, H., Maheswaran, M., Distributed dynamic scheduling of composite tasks on grid computing systems (2002) Proceedings of the 11th IEEE Heterogeneous Computing Workshop, , Fort Lauderdale, U.S.ACooper, K., Dasgupta, A., Kennedy, K., Koelbel, C., Mandal, A., Marin, G., Mazina, M., Dongarra, J., New grid scheduling and rescheduling methods in the GrADS project (2004) Proceedings of the IPDPS Next Generation Software Program - NSFNGS - PI Workshop, pp. 199-206. , IEEE Computer Society Press: Los Alamitos, CAFujimoto, N., Hagihra, K., Near-optimal dynamic task scheduling of precedence constrained coarse-grained tasks onto a computational grid (2003) Second International Symposium on Parallel and Distributed Computing, pp. 80-87. , Ljubljana, SloveniaWolski, R., Spring, N.T., Hayes, J., The network weather service: A distributed resource performance forecasting service for metacomputing (1999) Future Generation Computer Systems, 15 (5-6), pp. 757-76

An Environment For Evaluation And Testing Of Service Workflow Schedulers In Clouds

Workflows built through service composition bring new challenges, making the scheduling task even more complex. Besides that, scheduling researchers need a wide range of workflows and their respective services to validate new achievements. In this paper we present a service oriented testbed where experiments can be conducted to develop and evaluate algorithms, heuristics, and scheduling policies for workflows. Our testbed offers an emulator service which allows the workflow characterization through the description of its services. With this, researchers can build workflows which have similar behavior to the real workflow applications, emulating them without the need of implementing all applications and services involved in a real application execution. To demonstrate the utilization of both the testbed and emulator, we conducted workflow executions emulating service workflow applications, such as Montage and LIGO. © 2011 IEEE.301307Bahcesehir University,Grid Telekom,HUAWEI Technologies Co., Ltd.,IBM Turkey,IEEE Turkey Section(2011) Montage: An Astronomical Image Engine, , http://montage.ipac.caltech.edu, [Online]Ramakrishnan, A., Singh, G., Zhao, H., Deelman, E., Sakellariou, R., Vahi, K., Blackburn, K., Samidi, M., Scheduling data-intensive workflows onto storage-constrained distributed resources (2007) CCGRID '07, pp. 401-409. , Washington, DC, USA: IEEE Computer SocietyAlliance, G., (2011) Globus Toolkit, , http://http://www.globus.org/toolkit/, [Online]Senna, C.R., Bittencourt, L.F., Madeira, E.R.M., Execution of service workflows in grid environments (2010) International Journal of Communication Networks and Distributed Systems (IJCNDS), 5 (1-2), pp. 88-108Bharathi, S., Chervenak, A., Deelman, E., Mehta, G., Su, M., Vahi, K., Characterization of scientific workflows (2008) WORKS 2008: 3Rd Workshop on Workflows in Support of Large-scale ScienceDeelman, E., (2008) Clouds: An Opportunity for Scientific Applications? (keynote in the 2008 Cracow Grid Workshops)Bittencourt, L.F., Madeira, E.R.M., A performance-oriented adaptive scheduler for dependent tasks on grids (2008) Concurrency and Computation: Practice and Experience, 20 (9), pp. 1029-1049Blythe, J., Gil, Y., Deelman, E., Coordinating workflows in shared grid environments (2004) ICAPS '04, , Whistler, British Columbia, Canada(2011) Cloudsim, , http://www.buyya.com/gridbus/cloudsim/, [Online

Impact Of Communication Uncertainties On Workflow Scheduling In Hybrid Clouds

The so-called hybrid cloud is the composition of an infrastructure that comprises private resources as well as public resources leased from public clouds. Hybrid clouds can be utilized for the execution of applications composed of dependent jobs, usually modeled as workflows. In this scenario, a scheduler must distribute the components of the workflow onto available resources considering the communication demands and the available bandwidth in network links. However, such information can be imprecise, and consequently decisions on resource allocation can be ineffective. In this paper, we evaluate scheduling algorithms in the face of imprecise information on the availability of communication channels. Results showed that schedules are negatively affected by the unforeseen variations in bandwidth during the execution of the application. © 2012 IEEE.16231628Zhang, Q., Cheng, L., Boutaba, R., Cloud computing: State-of-the-art and research challenges (2010) Journal of Internet Services and Applications, 1 (1), pp. 7-18Casanova, H., Legrand, A., Zagorodnov, D., Berman, F., Heuristics for scheduling parameter sweep applications in grid environments (2000) Heterogeneous Computing Workshop, 2000. (HCW 2000) Proceedings. 9th, pp. 349-363Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Zaharia, M., A view of cloud computing (2010) Communications of the ACM, 53, pp. 50-58. , AprDong, F., Akl, S.G., Scheduling algorithms for grid computing: State of the art and open problems (2006) Queen's University School of Computing, Kingston, Canada, Tech. Rep., , janYu, J., Buyya, R., Ramamohanarao, K., Work flow scheduling algorithms for grid computing (2008) Studies in Computational Intelligence, 146, pp. 173-214Pandey, S., Wu, L., Guru, S., Buyya, R., A particle swarm optimization-based heuristic for scheduling workflow applications in cloud computing environments (2010) 24th IEEE International Conference on Advanced Information Networking and Applications (AINA), pp. 400-407. , aprilYu, J., Buyya, R., Tham, C.K., Cost-based scheduling of scientific workflow applications on utility grids (2005) E-Science and Grid Computing, p. 8. , july, pp. -147Bittencourt, L.F., Madeira, E.R.M., HCOC: A cost optimization algorithm for workflow scheduling in hybrid clouds (2011) Journal of Internet Services and Applications, 2 (3), pp. 207-227. , AugBittencourt, L.F., Madeira, E.R.M., A performance-oriented adaptive scheduler for dependent tasks on grids (2008) Concurrency and Computation: Practice and Experience, 20 (9), pp. 1029-1049Abrishami, S., Naghibzadeh, M., Epema, D., Cost-driven scheduling of grid workflows using partial critical paths (2010) 11th IEEE/ACM International Conference on Grid Computing (GRID 2010), pp. 81-88. , octKalantari, M., Akbari, M.K., Grid performance prediction using state-space model (2009) Concurrency and Computation : Practice and Experience, 21 (9), pp. 1109-1130. , JunGautama, H., Van Gemund, A., Low-cost static performance prediction of parallel stochastic task compositions (2006) Parallel and Distributed Systems, IEEE Transactions on, 17 (1), pp. 78-91. , janKhan, A., Yan, X., Tao, S., Anerousis, N., Workload characterization and prediction in the cloud: A multiple time series approach (2012) Workshop on Cloud Management (CloudMan 2012), NOMS Workshop Proceedings, , USA, AprilAllen, G., Angulo, D., Foster, I., Lanfermann, G., Liu, C., Radke, T., Seidel, E., Shalf, J., The cactus worm: Experiments with dynamic resource discovery and allocation in a grid environment (2001) International Journal of High Performance Computing Applications, 15, p. 2001Sakellariou, R., Zhao, H., A low-cost rescheduling policy for efficient mapping of workflows on grid systems (2004) Scientific Programming, 12 (4), pp. 253-262. , http://dl.acm.org/citation.cfm?id=1240160.1240165, DecBatista, D.M., Da Fonseca, N.L.S., Miyazawa, F.K., Granelli, F., Self-adjustment of resource allocation for grid applications (2008) Computer Networks, 52 (9), pp. 1762-1781. , JunBatista, D.M., Da Fonseca, N.L.S., Robust scheduler for grid networks under uncertainties of both application demands and resource availability (2011) Computer Networks, 55 (1), pp. 3-19Zhao, Y., Dobson, J., Foster, I., Moreau, L., Wilde, M., A notation and system for expressing and executing cleanly typed workflows on messy scientific data (2005) SIGMOD Records, 34 (3), pp. 37-43Deelman, E., (2008) Clouds: An opportunity for scientific applications? (keynote in the 2008 Cracow Grid Workshops)Gil, Y., Deelman, E., Ellisman, M., Fahringer, T., Fox, G., Gannon, D., Goble, C., Myers, J., Examining the challenges of scientific workflows (2007) IEEE Computer, 40 (12), pp. 24-32. , de