Deadline-aware MapReduce job scheduling with dynamic resource availability
As MapReduce is becoming ubiquitous in large-scale data analysis, many recent studies
have shown that the performance of MapReduce could be improved by different job …
have shown that the performance of MapReduce could be improved by different job …
LsPS: A job size-based scheduler for efficient task assignments in Hadoop
The MapReduce paradigm and its open source implementation Hadoop are emerging as an
important standard for large-scale data-intensive processing in both industry and academia …
important standard for large-scale data-intensive processing in both industry and academia …
A constraint programming based Hadoop scheduler for handling MapReduce jobs with deadlines on clouds
N Lim, S Majumdar, P Ashwood-Smith - Proceedings of the 6th ACM …, 2015 - dl.acm.org
A novel MapReduce constraint programming based matchmaking and scheduling algorithm
(MRCP) that can handle MapReduce jobs with deadlines and achieve high system …
(MRCP) that can handle MapReduce jobs with deadlines and achieve high system …
LSTPD: least slack time-based preemptive deadline constraint scheduler for Hadoop clusters
Big data refers to numerous forms of complex and large datasets which need distinctive
computational platforms in order to be analyzed. Hadoop is one of the popular frameworks …
computational platforms in order to be analyzed. Hadoop is one of the popular frameworks …
A load-aware scheduler for MapReduce framework in heterogeneous cloud environments
HH You, CC Yang, JL Huang - … of the 2011 ACM Symposium on Applied …, 2011 - dl.acm.org
MapReduce is becoming a popular programming model for large-scale data processing in
cloud computing environments. Hadoop MapReduce is the most popular open-source …
cloud computing environments. Hadoop MapReduce is the most popular open-source …
Improving MapReduce scheduler for heterogeneous workloads in a heterogeneous environment
Big data is largely influencing business entities and research sectors to be more data‐
driven. Hadoop MapReduce is one of the cost‐effective ways to process large scale …
driven. Hadoop MapReduce is one of the cost‐effective ways to process large scale …
MRCP-RM: a technique for resource allocation and scheduling of MapReduce jobs with deadlines
N Lim, S Majumdar… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Resource allocation and scheduling on clouds are required to harness the power of the
underlying resource pool such that the service provider can meet the quality of service …
underlying resource pool such that the service provider can meet the quality of service …
PRISM: Fine-grained resource-aware scheduling for MapReduce
MapReduce has become a popular model for data-intensive computation in recent years. By
breaking down each job into small map and reduce tasks and executing them in parallel …
breaking down each job into small map and reduce tasks and executing them in parallel …
A MapReduce task scheduling algorithm for deadline constraints
The current works about MapReduce task scheduling with deadline constraints neither take
the differences of Map and Reduce task, nor the cluster's heterogeneity into account. This …
the differences of Map and Reduce task, nor the cluster's heterogeneity into account. This …
CASH: context aware scheduler for Hadoop
KA Kumar, VK Konishetty, K Voruganti… - Proceedings of the …, 2012 - dl.acm.org
Hadoop MapReduce infrastructure has been designed to solve problems that can be broken
down into tasks that can be solved in parallel. The key reason for MapReduce's popularity is …
down into tasks that can be solved in parallel. The key reason for MapReduce's popularity is …