Wednesday, 20 November 2019
Monday, 17. December 2018 05:20

SPEC Kaivalya Dixit Distinguished Dissertation Award 2018 Winners

The Kaivalya Dixit Distinguished Dissertation Selection committee has chosen this year to select two winners based on the high quality of both submissions.

The first winning dissertation titled QoS-aware Deployment and Adaptation of Data Stream Processing Applications in Geo-Distributed Environments, authored by Matteo Nardelli of the University of Rome under the supervision of Professor Valeria Cardellini.

Nardelli addresses the problem of QoS-aware deployment and adaptation of data stream processing (DSP) applications in geo-distributed environments. The contributions are the formulation of the DSP operator placement problem, formulation of the run-time problem, design of a framework, optimizer and heuristics, and implementation into an open source framework.

The second winning dissertation titled Methods and Benchmarks for Auto-Scaling Mechanisms in Elastic Cloud Environments by Nikolas Herbst of the Julius-Maximilians-Universität Würzburg, under the supervision of Professor Samuel Kounev.

Herbst proposes several methods and related tools for automatically provisioning and scaling elastic resources for cloud systems. The thesis is also exceptional in the effort put into validation using plausible workloads.

The awards will be presented at the International Conference on Performance Engineering (ICPE 2019) in Mumbai, India in April 2019.

The award selection committee for 2018 was chaired by Evgenia Smirni (College of William and Mary) and consisted of the following members:

• André van Hoorn (Universität Stuttgart, Germany)
• Diwakar Krishnamurthy (University of Calgary, Canada)
• Arif Merchant (Google, USA)
• Erich Nahum (IBM Research, USA)
• Vittoria de Nitto Personè (University of Rome, Italy)
• Xipeng Shen (NCSU, USA)
• Xiaoyun Zhu (Hyperpilot, USA)

The SPEC Kaivalya Dixit Distinguished Dissertation Award aims to
recognize outstanding doctoral dissertations in the field of computer benchmarking, performance evaluation, and experimental system analysis in general. Nominated dissertations will be evaluated in terms of scientific originality, scientific significance, practical relevance, impact, and quality of the presentation.

Contributions of interest span the design of metrics for system evaluation as well as the development of methodologies, techniques and tools for measurement, load testing, profiling, workload characterization, dependability and efficiency evaluation of computing systems. Dissertations defended between October 2017 and September 2018, was eligible to be nominated.