Availability analysis for deployment of in-cloud applications
Proceedings of the 4th international ACM Sigsoft symposium on Architecting critical systems
Cloud API issues: an empirical study and impact
Proceedings of the 9th international ACM Sigsoft conference on Quality of software architectures
Safe deployment for reconfigurable cyber-physical systems
Proceedings of the 18th international doctoral symposium on Components and architecture
Search-based genetic optimization for deployment and reconfiguration of software in the cloud
Proceedings of the 2013 International Conference on Software Engineering
Deployment optimization of software objects by design-level delay estimation
The Journal of Supercomputing
| Hi-index | 0.00 |
A distributed system's allocation of software components to hardware nodes (i.e., deployment architecture) can have a significant impact on its quality of service (QoS). For a given system, there may be many deployment architectures that provide the same functionality, but with different levels of QoS. The parameters that influence the quality of a system's deployment architecture are often not known before the system's initial deployment and may change at runtime. This means that redeployment of the software system may be necessary to improve the system's QoS properties. This paper presents and evaluates a framework aimed at finding the most appropriate deployment architecture for a distributed software system with respect to multiple, possibly conflicting QoS dimensions. The framework supports formal modeling of the problem and provides a set of tailorable algorithms for improving a system's deployment. We have realized the framework on top of a visual deployment architecture modeling and analysis environment. The framework has been evaluated for precision and execution-time complexity on a large number of simulated distributed system scenarios, as well as in the context of two third-party families of distributed applications.