A comprehensive survey of load balancing strategies using hadoop queue scheduling and virtual machine migration
NS Dey, T Gunasekhar - IEEE Access, 2019 - ieeexplore.ieee.org
The recent growth in the demand for scalable applications from the consumers of the
services has motivated the application development community to build and deploy the …
services has motivated the application development community to build and deploy the …
Hopper: Decentralized speculation-aware cluster scheduling at scale
As clusters continue to grow in size and complexity, providing scalable and predictable
performance is an increasingly important challenge. A crucial roadblock to achieving …
performance is an increasingly important challenge. A crucial roadblock to achieving …
Energy-aware scheduling of mapreduce jobs for big data applications
The majority of large-scale data intensive applications executed by data centers are based
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
Encoded bitmap indexing for data warehouses
MC Wu, AP Buchmann - Proceedings 14th International …, 1998 - ieeexplore.ieee.org
Complex query types, huge data volumes, and very high read/update ratios make the
indexing techniques designed and tuned for traditional database systems unsuitable for …
indexing techniques designed and tuned for traditional database systems unsuitable for …
Wide-area analytics with multiple resources
Running data-parallel jobs across geo-distributed sites has emerged as a promising
direction due to the growing need for geo-distributed cluster deployment. A key difference …
direction due to the growing need for geo-distributed cluster deployment. A key difference …
Fuzzy joins using mapreduce
Fuzzy/similarity joins have been widely studied in the research community and extensively
used in real-world applications. This paper proposes and evaluates several algorithms for …
used in real-world applications. This paper proposes and evaluates several algorithms for …
Dynamicmr: A dynamic slot allocation optimization framework for mapreduce clusters
MapReduce is a popular computing paradigm for large-scale data processing in cloud
computing. However, the slot-based MapReduce system (eg, Hadoop MRv1) can suffer from …
computing. However, the slot-based MapReduce system (eg, Hadoop MRv1) can suffer from …
Joint optimization of overlapping phases in MapReduce
MapReduce is a scalable parallel computing framework for big data processing. It exhibits
multiple processing phases, and thus an efficient job scheduling mechanism is crucial for …
multiple processing phases, and thus an efficient job scheduling mechanism is crucial for …
Two sides of a coin: Optimizing the schedule of mapreduce jobs to minimize their makespan and improve cluster performance
A Verma, L Cherkasova… - 2012 IEEE 20th …, 2012 - ieeexplore.ieee.org
Large-scale MapReduce clusters that routinely process petabytes of unstructured and semi-
structured data represent a new entity in the changing landscape of clouds. A key challenge …
structured data represent a new entity in the changing landscape of clouds. A key challenge …
Deadline-based workload management for MapReduce environments: Pieces of the performance puzzle
Hadoop and the associated MapReduce paradigm, has become the de facto platform for
cost-effective analytics over “Big Data”. There is an increasing number of MapReduce …
cost-effective analytics over “Big Data”. There is an increasing number of MapReduce …