[HTML][HTML] MapReduce scheduling algorithms in Hadoop: a systematic study
Hadoop is a framework for storing and processing huge volumes of data on clusters. It uses
Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process …
Hadoop Distributed File System (HDFS) for storing data and uses MapReduce to process …
Task scheduling in big data platforms: a systematic literature review
Abstract Context: Hadoop, Spark, Storm, and Mesos are very well known frameworks in both
research and industrial communities that allow expressing and processing distributed …
research and industrial communities that allow expressing and processing distributed …
A delay-based dynamic scheduling algorithm for bag-of-task workflows with stochastic task execution times in clouds
Abstract Bag-of-Tasks (BoT) workflows are widespread in many big data analysis fields.
However, there are very few cloud resource provisioning and scheduling algorithms tailored …
However, there are very few cloud resource provisioning and scheduling algorithms tailored …
Budget aware scheduling algorithm for workflow applications in IaaS clouds
K Kalyan Chakravarthi, L Shyamala, V Vaidehi - Cluster Computing, 2020 - Springer
Cloud computing, a novel and promising model of Service-oriented computing, provides a
pay-per-use framework to solve large-scale scientific and business workflow applications …
pay-per-use framework to solve large-scale scientific and business workflow applications …
[HTML][HTML] Elastic scheduling of scientific workflows under deadline constraints in cloud computing environments
N Anwar, H Deng - Future Internet, 2018 - mdpi.com
Scientific workflow applications are collections of several structured activities and fine-
grained computational tasks. Scientific workflow scheduling in cloud computing is a …
grained computational tasks. Scientific workflow scheduling in cloud computing is a …
An intelligent clustering algorithm for high-dimensional multiview data in big data applications
Q Tao, C Gu, Z Wang, D Jiang - Neurocomputing, 2020 - Elsevier
There are many high-dimensional multiview data in various big data applications. It is very
difficult to deal with those high-dimensional multiview data for the classic clustering …
difficult to deal with those high-dimensional multiview data for the classic clustering …
Cost-based Data Prefetching and Scheduling in Big Data Platforms over Tiered Storage Systems
H Herodotou, E Kakoulli - ACM Transactions on Database Systems, 2023 - dl.acm.org
The use of storage tiering is becoming popular in data-intensive compute clusters due to the
recent advancements in storage technologies. The Hadoop Distributed File System, for …
recent advancements in storage technologies. The Hadoop Distributed File System, for …
SPO: a secure and performance-aware optimization for MapReduce scheduling
MapReduce is a common framework that effectively processes multi-petabyte data in a
distributed manner. Therefore, MapReduce is widely used in heterogeneous environments …
distributed manner. Therefore, MapReduce is widely used in heterogeneous environments …
MapReduce: an infrastructure review and research insights
In the current decade, doing the search on massive data to find “hidden” and valuable
information within it is growing. This search can result in heavy processing on considerable …
information within it is growing. This search can result in heavy processing on considerable …
Replica-aware task scheduling and load balanced cache placement for delay reduction in multi-cloud environment
C Li, J Zhang, H Tang - The Journal of Supercomputing, 2019 - Springer
With the development of content-sharing and collaborative computing services such as
online social networks, scientific workflow, there are huge amounts of data generated. To …
online social networks, scientific workflow, there are huge amounts of data generated. To …