Parallel database systems: the future of high performance database systems
Communications of the ACM
Task scheduling in parallel and distributed systems
Task scheduling in parallel and distributed systems
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Resilient workload manager: taming bursty workload of scaling internet applications
ICAC-INDST '09 Proceedings of the 6th international conference industry session on Autonomic computing and communications industry session
Controversial users demand local trust metrics: an experimental study on Epinions.com community
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads
Proceedings of the VLDB Endowment
Communications of the ACM
Benchmarking cloud serving systems with YCSB
Proceedings of the 1st ACM symposium on Cloud computing
A bayesian approach to online performance modeling for database appliances using gaussian models
Proceedings of the 8th ACM international conference on Autonomic computing
Provisioning data analytic workloads in a cloud
Future Generation Computer Systems
Estimating resource costs of data-intensive workloads in public clouds
Proceedings of the 10th International Workshop on Middleware for Grids, Clouds and e-Science
Towards building performance models for data-intensive workloads in public clouds
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
| Hi-index | 0.00 |
The promise of "infinite" resources given by the cloud computing paradigm has led to recent interest in exploiting clouds for large-scale data-intensive computing. Given this supposedly infinite resource set, we need a management function that regulates application workload on these resources. This doctoral research focuses on two aspects of workload management, namely scheduling and provisioning. We propose a novel framework for workload execution and resource provisioning, and associated models, algorithms, and protocols.