Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
15
Taming the Cloud Object Storage with MOS
"... Abstract Cloud object stores today are deployed using a single set of configuration parameters for all different types of applications. This homogeneous setup results in all applications experiencing the same service level (e.g., data transfer throughput, etc.). However, the vast variety of applica ..."
Abstract
- Add to MetaCart
of applications expose extremely different latency and throughput requirements. To this end, we propose MOS, a Micro Object Storage architecture with independently configured microstores each tuned dynamically for a particular type of workload. We then expose these microstores to the tenant who can then choose
Towards a Method for Decision Support in Multi-cloud Environments
"... Abstract—Providers of cloud services as well as the cloud services themselves differ in the business models, functionality, quality of service, cost, value, etc. which makes the choice of a provider and a service difficult. Beyond that the complexity and lack of transparency with respect to cost and ..."
Abstract
-
Cited by 1 (1 self)
- Add to MetaCart
to assist a decision maker in choosing providers and services in a multi-cloud environment. We characterize the needs for the DSM in the multi-cloud context and propose an initial version of the process for the DSM. Based on the method proposed and the needs identified, we elaborate to what degree
THE MOSAIC BENCHMARKING FRAMEWORK: DEVELOPMENT AND EXECUTION OF CUSTOM CLOUD BENCHMARKS
"... Abstract. A natural consequence of the pay-per-use business model of Cloud Computing is that cloud users need to evaluate and to compare different cloud providers in order to choose the best offerings in terms of trade-off between performance and cost. But at the state of the art, in cloud environme ..."
Abstract
- Add to MetaCart
Abstract. A natural consequence of the pay-per-use business model of Cloud Computing is that cloud users need to evaluate and to compare different cloud providers in order to choose the best offerings in terms of trade-off between performance and cost. But at the state of the art, in cloud
1Optimizing Multi-Objective Evolutionary Algorithms to Enable Quality-Aware Software Provisioning
"... Abstract—Elasticity is a key feature for cloud infrastructures to continuously align allocated computational resources to evolving hosted software needs. This is often achieved by relaxing quality criteria, for instance security or privacy because quality criteria are often conflicting with performa ..."
Abstract
- Add to MetaCart
to be suitable candidates to find these trade-offs and have been even applied for cloud architecture optimizations. Still though, their runtime efficiency limits the widespread adoption of such algorithms in cloud engines, and thus the consideration of quality criteria in clouds. Indeed MOEAs produce many dead
Effective runtime monitoring of distributed
"... devices in the Internet of Things (IoT) and other data sources are increasingly bridging the gap between the physical and digital world by providing fine-grained data about real-world events. Enterprise software systems are adopting the paradigm of event-based systems (EBS) to enable them to react t ..."
Abstract
- Add to MetaCart
to meaningful events in a timely manner. Smart supply chains fusing dynamic sensor data with information provided by backend-systems are one such example of event-based enterprise systems. Monitoring their global state in an effective way for runtime governance remains an open research challenge: providing
4. TITLE AND SUBTITLE A Practical Theory of Micro-Solar Power Sensor Networks
, 2009
"... Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments ..."
Abstract
- Add to MetaCart
Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information,
Results 1 - 10
of
15
