Resource Management of Replicated Service Systems Provisioned in the Cloud

Staff - Faculty of Informatics

Start date: 11 February 2015

End date: 12 February 2015

You are cordially invited to attend the PhD Dissertation Defense of Mathias BJOERKQVIST on Wednesday, February 11th 2015 at 15h30 in room 251 (Main building)

Abstract:
Service providers seek scalable and cost-effective cloud solutions for hosting their applications. Despite significant recent advances facilitating the deployment and management of services on cloud platforms, a number of challenges still remain. Service providers are confronted with time-varying requests for the provided applications, inter-dependencies between different components, performance variability of the procured virtual resources, and cost structures that differ from conventional data centers. Moreover, fulfilling service level agreements, such as the throughput and response times percentiles, becomes of paramount importance for ensuring business advantages.

In this thesis, we explore service provisioning in clouds from multiple points of view. The aim is to best provide service replicas in the form of VMs to various service applications, such that their tail throughput and tail response times, as well as resource utilization, meet the service level agreements in the most cost effective manner. In particular, we develop models, algorithms and replication strategies that consider multi-tier composed services provisioned in clouds. We also investigate how a service provider can opportunistically take advantage of observed performance variability in the cloud. Finally, we provide means of guaranteeing tail throughput and response times in the face of performance variability of VMs, using Markov chain modeling and large deviation theory. We employ methods from analytical modeling, event-driven simulations and experiments. Overall, this thesis provides not only a multi-faceted approach to exploring several crucial aspects of hosting services in clouds, i.e., cost, tail throughput, and tail response times, but our proposed resource management strategies are also rigorously validated via trace-driven simulation and extensive experiments.

Dissertation Committee:

  • Prof. Walter Binder, Università della Svizzera italiana, Switzerland (Research Advisor)
  • Prof. Rolf Krause, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Cesare Pautasso, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Heiko Schuldt, University of Basel, Switzerland (External Member)
  • Prof. Giuseppe Serazzi, Politecnico di Milano, Italy (External Member)