The Engineering Strategic Hiring Initiative

Lena Mashayekhy
Resource Management in Cloud and Big Data Systems
Wayne State University
White 411
January 13, 2015

Cloud computing is a paradigm shift in computing, where services are offered and acquired on demand in a cost-effective way.  These services are often virtualized, and they can handle the computing needs of big data analytics.  The ever-growing demand for cloud services arises in many areas including healthcare, transportation, energy systems, and manufacturing.  However, cloud resources such as computing power,  storage, energy, dollars for infrastructure, and dollars for operations, are limited.  Effective use of the existing resources is a fundamental challenge that places the cloud resource management at the heart of the cloud providers' decision-making process.  In this talk, I will discuss my research work that addresses this fundamental challenge.

First, I will present the design of optimal and approximation mechanisms for Virtual Machine provisioning, allocation, and pricing in clouds.  The proposed mechanisms are designed to adapt to changing conditions (i.e., users requests) and to lead the system into an equilibrium in which users have incentives to report their resource requests and valuations truthfully.  Then, I will present the design of an energy-aware MapReduce scheduling algorithm for big data applications.  The proposed scheduling algorithm finds a detailed task placement of a MapReduce job minimizing the energy required for its execution.  Extensive experimental results show that the proposed algorithm is able to find near optimal job schedules consuming approximately 30% less energy on average than the schedules obtained by a common practice scheduler that minimizes the makespan.


Lena Mashayekhy is currently a PhD candidate in computer science at Wayne State University. Her research interests include Big Data Computing, Management of Big Data Systems, Cloud Computing, Parallel Algorithms, Distributed Systems, and Game Theory. Her research papers have been published in top-tier journals such as IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Cloud Computing. She received several awards for her research including: the 2014 INFORMS Service Science Best Paper Runner-Up Award, the 2014 INFORMS ENRE Best Student Paper Award, and the Ralph Kummler H. Award for Distinguished Achievement in Graduate Student Research. She is a student member of the ACM, the IEEE, and the IEEE Computer Society.