Verifying that a software system shows certain non-functional properties is a primary concern for cloud applications. Given the heterogeneous technology offer and the pricing models currently available in the cloud market it is extremely complex to find the deployment that fits the application requirements and provides the best Quality of Service (QoS) and cost trade-offs. This task can be very challenging, even infeasible if performed manually, since the number of solutions may become extremely large depending on the number of possible providers and available technology stacks. Furthermore, with the increasing adoption of cloud computing, there is a need for fair evaluation of cloud systems. Today's cloud services differ among others by cost, performance, consistency guarantees, load-balancing, caching, fault tolerance, and SLAs. Moreover, cloud systems are inherently multi-tenant and their performance can vary over time, depending on the congestion level, provider policies, and the competition among running applications. System architects and developers are challenged with this variety of services and trade-offs. Hence, the purpose of a cloud benchmark should be to help developers when choosing the right architecture and services for their applications. In this paper we propose a joint benchmarking and optimization methodology to support the design and migration of legacy applications to Cloud. Our approach is effective in identifying the deployment of minimum costs, which provide also QoS guarantees.

Evangelinou, A., Ciavotta, M., Kousiouris, G., Ardagna, D. (2015). A Joint Benchmark-Analytic Approach for Design-Time Assessment of Multi-Cloud Applications. In 1st International Conference on Cloud Forward: From Distributed to Complete Computing (pp.67-77). Elsevier B.V. [10.1016/j.procs.2015.09.224].

A Joint Benchmark-Analytic Approach for Design-Time Assessment of Multi-Cloud Applications

Ciavotta, M;
2015

Abstract

Verifying that a software system shows certain non-functional properties is a primary concern for cloud applications. Given the heterogeneous technology offer and the pricing models currently available in the cloud market it is extremely complex to find the deployment that fits the application requirements and provides the best Quality of Service (QoS) and cost trade-offs. This task can be very challenging, even infeasible if performed manually, since the number of solutions may become extremely large depending on the number of possible providers and available technology stacks. Furthermore, with the increasing adoption of cloud computing, there is a need for fair evaluation of cloud systems. Today's cloud services differ among others by cost, performance, consistency guarantees, load-balancing, caching, fault tolerance, and SLAs. Moreover, cloud systems are inherently multi-tenant and their performance can vary over time, depending on the congestion level, provider policies, and the competition among running applications. System architects and developers are challenged with this variety of services and trade-offs. Hence, the purpose of a cloud benchmark should be to help developers when choosing the right architecture and services for their applications. In this paper we propose a joint benchmarking and optimization methodology to support the design and migration of legacy applications to Cloud. Our approach is effective in identifying the deployment of minimum costs, which provide also QoS guarantees.
Si
paper
Benchmarking; Cloud applications; QoS; Model Driven Design;
English
International Conference on Cloud Forward: From Distributed to Complete Computing, 2015 6-8 october
9781510814806
Evangelinou, A., Ciavotta, M., Kousiouris, G., Ardagna, D. (2015). A Joint Benchmark-Analytic Approach for Design-Time Assessment of Multi-Cloud Applications. In 1st International Conference on Cloud Forward: From Distributed to Complete Computing (pp.67-77). Elsevier B.V. [10.1016/j.procs.2015.09.224].
Evangelinou, A; Ciavotta, M; Kousiouris, G; Ardagna, D
File in questo prodotto:
File Dimensione Formato  
holaConf.pdf

Solo gestori archivio

Dimensione 546.22 kB
Formato Adobe PDF
546.22 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/186591
Citazioni
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 1
Social impact