An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Performance modeling and system management for multi-component online services
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Exploiting nonstationarity for performance prediction
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Performance estimation of distributed real-time embedded systems by discrete event simulations
EMSOFT '07 Proceedings of the 7th ACM & IEEE international conference on Embedded software
Calling the cloud: enabling mobile phones as interfaces to cloud applications
Proceedings of the 10th ACM/IFIP/USENIX International Conference on Middleware
IBM Systems Journal
Resource demand modeling for multi-tier services
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Probabilistic performance modeling of virtualized resource allocation
Proceedings of the 7th international conference on Autonomic computing
Automatic estimation of performance requirements for software tasks of mobile devices
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Diagnosing performance changes by comparing request flows
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Modeling performance of a parallel streaming engine: bridging theory and costs
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Mobile devices are becoming the main entry points to the growing number of cloud applications and services. Unlike traditional approaches, we pursue a flexible architectural model where cloud hosted applications are distributed between mobile devices and the cloud in a bid to improve interaction performance. Given the increasing variety of mobile platforms or virtual instances, in this paper we approach the problem of estimating performance for such applications in two steps. First, we identify the factors that impact interaction response times, such as the application distribution schemes, workload sizes and intensities, or the resource variations of the mobile-cloud setup. Second, we attempt to find correlations between these factors and to understand how to build a unified and generic performance estimation model.