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2008
2008 IEEE International Symposium on Parallel and Distributed Processing
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Processor Vivien, Frédéric Offline and Online Master-Worker Scheduling of Concurrent Bags-of-Tasks on Heterogeneous Platforms Vodacek, Anthony Towards a Real-Time Data Driven Wildland Fire Model Voronenko ...
Automated Generation of Explicit Connectors for Component Based Hardware/Software Interaction in Embedded Real-Time Systems Goumas, Georgios Evaluation of Dynamic Scheduling Methods in Simulations of Storm-time ...
doi:10.1109/ipdps.2008.4536576
fatcat:7unikf5ywjhjtdd6xtrmcom3gq
Reliability Aware Task Scheduling In Wireless Hetrogeneous Systems
2016
International Journal of Computer Applications
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A distributed operating system should: General Terms Distributed Computing, reliable task scheduling. ...
A distributed operating system is one that looks to its user like an ordinary centralized operating system, but runs on multiple, independent nodes. ...
Hence, a variety of scheduling strategies with reference to non-real-time applications have not been discussed
PROPOSED SYSTEM AND R-MODEL Here a generalized system model for parallel applications running ...
doi:10.5120/ijca2016909415
fatcat:d2abaetakjgpzmyrnylhx73hxq
A Case Study: Task Scheduling Methodologies for High Speed Computing Systems
2014
International Journal of Embedded Systems and Applications
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In this paper, we brought a review of various application scheduling models which provide parallelism for homogeneous and heterogeneous computing systems. ...
computing platform for real time applications. ...
Communication aware online task scheduling for partially reconfigurable systems [17] distributes the tasks to 2D area based on data communication time of tasks. ...
doi:10.5121/ijesa.2014.4401
fatcat:dtjqbhh7zbdbjoqddi5cd5o6v4
A Novel Methodology for Task Distribution in Heterogeneous Reconfigurable Computing System
2015
International Journal of Embedded Systems and Applications
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In general, task distribution i.e. scheduling models are two types called static and dynamic. ...
In this paper, we have developed a list based task distribution model which is based on the attributes of the tasks of an application and computing platform. ...
CONCLUSION In this paper, we have proposed a novel dynamic task distribution methodology named as MLF algorithm for on chip heterogeneous computing platform. ...
doi:10.5121/ijesa.2015.5102
fatcat:bhqbfz76qzhjpa3lhcl2rjslju
Characterizing Resource Allocation Heuristics for Heterogeneous Computing Systems
[chapter]
2005
Advances in Computers
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In many distributed computing environments, collections of applications need to be processed using a set of heterogeneous computing (HC) resources to maximize some performance goal. ...
to match a given real-world environment. ...
We presented a preliminary version of portions of this material at the Workshop on Advances in Parallel and Distributed Systems. ...
doi:10.1016/s0065-2458(04)63003-8
fatcat:i2sy57dac5eoxnfd7xg3hv6iga
A Hyper Heuristics Technique for Data Partitioning and Scheduling to Heterogeneous Systems using Genetic Algorithm and Improved Particle Swarm Optimization
2019
International journal of recent technology and engineering
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Development of the load partitioning for multiple round load distribution and effective scheduling of partitioned load to heterogeneous processor is primary goal of distributed and parallel system. ...
In order to optimize this issue, we utilizeImproved Particle swarm optimization (IPSO) determine the load fraction for generating activation order in terms of dynamically predicting fitness value of the ...
for Data Partitioning and Scheduling A hybrid real-coded GA is used to determine the population for the load distribution. ...
doi:10.35940/ijrte.b1136.0882s819
fatcat:udy3bbj5bfgtfgu2kvchm2zsim
Enhancing Hadoop Performance in Homogenous and Heterogeneous Big Data Environments by Dynamic Slot Configuration
2020
Advances in Systems Science and Applications
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the degree of influence of heterogeneity for each of these factors on the performance of Hadoop based on different schedulers. ...
A Hadoop system can be characterized based on three main factors: cluster, workload and user. ...
efficient scheduling algorithms for optimized classification in a heterogeneous data environment. ...
doi:10.25728/assa.2020.20.1.761
fatcat:k36ij4tapjdfvco2fxnrcdhmw4
A Survey on ANN Based Task Scheduling Strategies in Heterogeneous Distributed Computing Systems
2016
Nepal Journal of Science and Technology
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<p>Heterogeneous Distributed Computing Systems (HeDCS) efficiently utilize the heterogeneity of diverse computational resources which are interlinked through high speed networks for executing a group of ...
The flexible and powerful nature of ANN for identifying the data patterns, underlying time and other constraints and learning capabilities have shown to be a promising candidate among other heuristics. ...
dynamics can highlight the importance of ANN based strategies in the heterogeneous distributed task scheduling domain. ...
doi:10.3126/njst.v16i1.14359
fatcat:k2xhnkdszzf6teb545czxvdtuq
Evaluation of Selected Resource Allocation and Scheduling Methods in Heterogeneous Many-Core Processors and Graphics Processing Units
2014
Foundations of Computing and Decision Sciences
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Additionally, we present a new architecture for resource allocation and task scheduling library which provides a generic application programming interface at the operating system level for improving scheduling ...
Therefore, as tasks can be scheduled and managed in many alternative ways on both many-core CPUs or GPUs and consequently have a huge impact on the overall computing resources performance, there are needs ...
Acknowledgments This work has been supported by the National Science Centre (NCN) in Poland under the MAESTRO grant No DEC-2013/08/A/ST6/00296. ...
doi:10.2478/fcds-2014-0013
fatcat:wikj66mbx5gkrdpspoqnfogyrm
Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments
[article]
2017
arXiv
pre-print
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The paper at hand suggest a basic set of strategies to handle the arising challenges regarding the volatility, heterogeneity, and desired low latency execution by reducing the overall system timing (scheduling ...
Via these services, a distribution of tasks for the best balance of computational resources is achieved, while monitoring and management can be performed asynchronously in the background. ...
range for real-time scenarios. ...
arXiv:1708.04796v1
fatcat:ieeqnouvifg5fgecl2ac7yuooa
Strategies for Big Data Analytics through Lambda Architectures in Volatile Environments
2016
IFAC-PapersOnLine
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The paper at hand suggest a basic set of strategies to handle the arising challenges regarding the volatility, heterogeneity, and desired low latency execution by reducing the overall system timing (scheduling ...
Via these services, a distribution of tasks for the best balance of computational resources is achieved, while monitoring and management can be performed asynchronously in the background. ...
range for real-time scenarios. ...
doi:10.1016/j.ifacol.2016.11.138
fatcat:zy45z7ztc5f6zbmx4pskr7w5a4
Dynamic Scheduling with Process Migration
2007
Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)
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We then introduce a dynamic scheduling mechanism that considers migration cost as well as other conventional influential factors for performance optimization in a shared, heterogeneous environment. ...
Unlike conventional task scheduling, dynamic rescheduling has to consider process migration costs in its formulation. ...
The design of a migration-based dynamic scheduling is fourfold: reschedule triggering, migration cost modeling, task scheduling, and parameter measurement. ...
doi:10.1109/ccgrid.2007.46
dblp:conf/ccgrid/DuSW07
fatcat:7y7wz4pa3zglrhlptglrcvinsy
Intelligent scheduling with deep fusion of hardware-software energy-saving principles for greening stochastic nonlinear heterogeneous super-systems
2019
Applied intelligence (Boston)
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model of adaptive green scheduling for stochastic nonlinear heterogeneous super-systems, and a scheduling algorithm with distributed evolutionary intelligence. ...
decision-making based on mathematical model. ...
Large-scale real-time scheduling generally requires reducing energy consumption without reducing performance. ...
doi:10.1007/s10489-019-01424-5
fatcat:pygras6ojja7ppfto66z6vw4nu
A Survey on Job Scheduling in Big Data
2016
Cybernetics and Information Technologies
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Various scheduling algorithms of the MapReduce model using Hadoop vary with design and behavior, and are used for handling many issues like data locality, awareness with resource, energy and time. ...
Big Data Applications with Scheduling becomes an active research area in last three years. The Hadoop framework becomes very popular and most used frameworks in a distributed data processing. ...
It is a real time enhancement to Spark Streaming based on Spark's framework [24] . Spark is a category of efficient Big Data processing platform based on memory and alike to Hadoop MapReduce. ...
doi:10.1515/cait-2016-0033
fatcat:psrtc3l3dzgkfklqjl6hr3qczi
Proactivecloud Resources Management At Theedge Forefficientreal-Time Big Data Processing
2017
Zenodo
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ProactiveCloud Resources Management at theEdge forefficientReal-time Big Data Processing. ...
PRESTOCLOUD -VISION
A dynamic, distributed architecture for proactive cloud resources
management,
reaching the extreme edge of the network
• cloud processing if required based on current workload ...
network virtualization dynamic monitoring in real-time processing architectures for Big Data situation-aware and context-driven adaptation recommender systems real-time mobile stream processing ...
doi:10.5281/zenodo.1138578
fatcat:ll3vehr6crhb5i2yjlkhzaca5i
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