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2008 2008 IEEE International Symposium on Parallel and Distributed Processing  
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

Sonali T., Anjali R.
2016 International Journal of Computer Applications  
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

Mahendra Vucha, Arvind Rajawat
2014 International Journal of Embedded Systems and Applications  
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

Mahendra Vucha, Arvind Rajawat
2015 International Journal of Embedded Systems and Applications  
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]

Shoukat Ali, Tracy D. Braun, Howard Jay Siegel, Anthony A. Maciejewski, Noah Beck, Ladislau Bölöni, Muthucumaru Maheswaran, Albert I. Reuther, James P. Robertson, Mitchell D. Theys, Bin Yao
2005 Advances in Computers  
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  
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

E.K. Hamza
2020 Advances in Systems Science and Applications  
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

Altaf Hussain, Faisal Azam, Muhammad Sharif, Mussarat Yasmin, Sajjad Mohsin
2016 Nepal Journal of Science and Technology  
<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

Milosz Ciznicki, Krzysztof Kurowski, Jan Węglarz
2014 Foundations of Computing and Decision Sciences  
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]

Alexandre Da Silva Veith, Edison Pignaton de Freitas AVALON
2017 arXiv   pre-print
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

Veith Alexandre da Silva, Anjos Julio C.S. dos, de Freitas Edison Pignaton, Lampoltshammer Thomas J., Geyer Claudio F.
2016 IFAC-PapersOnLine  
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

Cong Du, Xian-He Sun, Ming Wu
2007 Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07)  
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

Jinglian Wang, Bin Gong, Hong Liu, Shaohui Li
2019 Applied intelligence (Boston)  
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

M. Senthilkumar, P. Ilango
2016 Cybernetics and Information Technologies  
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

Harald Schöning
2017 Zenodo  
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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