A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing
By S. Ostermann, Alexandru Iosup, Nezih Yigitbasi, Radu Prodan, Thomas Fahringer, Dick H. J. Epema. Cloud Computing, 2009
560 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management
View Paper: https://www.semanticscholar.org/paper/a3b50387386729f90f67ddc4cc899e71355613f4
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Marty A. Humphrey
- Ming Mao
- Rajkumar Buyya
- Maria Alejandra Rodriguez
- Ewa Deelman
- Giuseppe Aceto
- Antonio Pescapè
- Gideon Juve
In Information Systems
- Marty A. Humphrey
- Ming Mao
- Rajkumar Buyya
- Maria Alejandra Rodriguez
- Ewa Deelman
- Ignacio Martín Llorente
- Antonio Pescapè
- Alessio Botta
In Information Systems and Management
- Marty A. Humphrey
- Ming Mao
- Rajkumar Buyya
- Maria Alejandra Rodriguez
- Ewa Deelman
- Gideon Juve
- Ignacio Martín Llorente
- Jia Yu
Citations in the corpus
- Cost- and deadline-constrained provisioning for scientific workflow ensembles in IaaS clouds (2012, background): “These systems are regarded by the scientific community as a potentially attractive source of low-cost computing resources [4], [5].”
- Deadline Based Resource Provisioningand Scheduling Algorithm for Scientific Workflows on Clouds (2014, methodology): “We assume that for every VM type, the processing capacity in terms of floating point operations per second (FLOPS) is available either from the provider or can be estimated [17].”
- Cloud monitoring: A survey (2013, methodology): “Moreover, most of these research works have been conducted on Amazon EC2 [62,72,75,76,67] while a few others used also other kinds of testbeds, typically located at the researchers’ premises [75,67].”
- Cloud brokering mechanisms for optimized placement of virtual machines across multiple providers (2012, background): “[23] investigate the feasibility of using EC2 for scientific applications through a set of benchmarks that evaluate CPU, memory, I/O, etc.”
- A Performance Study on the VM Startup Time in the Cloud (2012, background): “[10] covers five instance types for single-and multiple-instance requests in EC2.”
- Runtime measurements in the cloud (2010, background): “Other authors [17, 24] evaluate the different cloud services of Amazon in terms of cost and performance, but he does not provide any evaluation of the possible impact that performance variance may have on users applications.”