TY - GEN
T1 - Optimization of deployment topologies for distributed enterprise applications
AU - Willnecker, Felix
AU - Krcmar, Helmut
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/7/18
Y1 - 2016/7/18
N2 - Enterprise applications are typically implemented as distributed systems composed of several components. Deciding where to deploy which component is a difficult task that today is usually assisted by logical topology recommendations. Choosing inefficient topologies allocates the wrong amount of resources, leads to unnecessary operation costs, or results in poor performance. Testing different topologies to find good solutions takes a lot of time and might delay productive operations. Therefore, this work introduces a software based deployment topology optimization approach for distributed enterprise applications. We use an enhanced performance model generator that extracts models from running applications. The extracted model is used to simulate performance metrics (e.g., resource utilization, response times, throughput) of an enterprise application. Subsequently, we introduce a deployment topology optimizer, which selects an optimized topology for a specified workload. The following two optimization goals are presented in this work: (i) minimum response time for an optimized user experience and (ii) maximize resource utilization for cost-effective topologies. To evaluate the approach we use the SPECjEnterpriseNEXT industry benchmark as distributed enterprise application. The evaluation demonstrates the accuracy of the simulation compared to the actual deployment and the pre-eminence of the selected topology compared to runner-up topologies.
AB - Enterprise applications are typically implemented as distributed systems composed of several components. Deciding where to deploy which component is a difficult task that today is usually assisted by logical topology recommendations. Choosing inefficient topologies allocates the wrong amount of resources, leads to unnecessary operation costs, or results in poor performance. Testing different topologies to find good solutions takes a lot of time and might delay productive operations. Therefore, this work introduces a software based deployment topology optimization approach for distributed enterprise applications. We use an enhanced performance model generator that extracts models from running applications. The extracted model is used to simulate performance metrics (e.g., resource utilization, response times, throughput) of an enterprise application. Subsequently, we introduce a deployment topology optimizer, which selects an optimized topology for a specified workload. The following two optimization goals are presented in this work: (i) minimum response time for an optimized user experience and (ii) maximize resource utilization for cost-effective topologies. To evaluate the approach we use the SPECjEnterpriseNEXT industry benchmark as distributed enterprise application. The evaluation demonstrates the accuracy of the simulation compared to the actual deployment and the pre-eminence of the selected topology compared to runner-up topologies.
KW - architecture optimization
KW - deployment topology optimization
KW - enterprise applications
KW - memory management simulation
KW - performance model generation
UR - http://www.scopus.com/inward/record.url?scp=84983437080&partnerID=8YFLogxK
U2 - 10.1109/QoSA.2016.11
DO - 10.1109/QoSA.2016.11
M3 - Conference contribution
AN - SCOPUS:84983437080
T3 - Proceedings - 2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA 2016
SP - 106
EP - 115
BT - Proceedings - 2016 12th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International ACM SIGSOFT Conference on Quality of Software Architectures, QoSA 2016
Y2 - 5 April 2016 through 8 April 2016
ER -