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Yousi Zheng
Columbus, OH
614-216-0788
zhengyousi@gmail.com
KEYWORDS
Research, Programming (C++, Java, Matlab, JavaScript, Python), Cloud Computing, Wireless, Networking
EDUCATION
Ph.D. Electrical and Computing Engineering (GPA: 3.98)
Ohio State University, Columbus, OH
Advisors: Prof. Ness Shroff and Prof. Prasun Sinha
May 2015
M.S Electronic Engineering
Tsinghua University, Beijing, China
2006 - 2009
B.S. Electronic Engineering
Tsinghua University, Beijing, China
2002 - 2006
AWARDS, HONORS
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Student Travel Award in CNSR conference, 2009 (One of the two awarded students ).
Overall Performance Fellowship awarded by Tsinghua University, 2007 (Based on GPA, social work and research).
Excellent Graduation Thesis Award of Dept. of Electronic Engineering in Tsinghua University, 2006 (Top 5%).
Systems Designer Certification of Chinese National Computer Technology and Software Qualification , 2005 (Chinese
official certification for advanced programmer).
Zhifu Chen Fellowship (2004) and Weilun Fund Fellowship (2003) for Excellent Academic Performance.
First Class Prize in College Physics Contest of Beijing, 2003 (Top 1%).
RESEARCH PROJECTS
Exploiting Large System Dynamics for Designing Simple Data Center Schedulers (2013-current)
The number and size of data centers has seen a rapid growth in the last few years. Hence, it is critical to develop scalable
scheduling mechanisms for processing the enormous number of jobs handled by popular paradigms such as the
MapReduce framework. In this work, I explore the possibility of simplifying the scheduling procedure by exploiting the
“largeness” of the data center system. I show that any work-conserving scheduler is asymptotically optimal under a wide
range of traffic loads, including the heavy traffic limit. This result implies, somewhat surprisingly, that when we have a
large number of machines, there is little to be gained by optimizing beyond ensuring that a scheduler should be workconserving. Further, I run extensive simulations, which indeed verify that when the total number of machines is large, stateof-the-art work-conserving schedulers have similar and close-to-optimal delay performance.
Forget the Deadline: Scheduling Interactive Applications in Data Centers (201 3-current)
An important class of applications that run on data centers such as web search, social network, online gaming, and
financial services, are delay sensitive. For these interactive applications, users have deadlines by which a job must be
completed at least partially. These deadlines vary across users and applications, which makes it especially challenging to
schedule jobs in a way that maximizes the overall performance of the data centers. For this problem under the general class
of utility functions, I show that one can always find a job arrival pattern for which the utility obtained by any causal
scheduler is less than or equal to 1.618 times that of the optimal non-causal scheduler. I then propose a simple deadline
agnostic scheduler called ISPEED (Interactive Services with Partial ExEcuti on and Deadlines), which is shown to be
utility optimal in the scenario without deadlines. What is remarkable is that while ISPEED makes decisions without the
need for knowing job deadlines, it can still achieve a competitive ratio of 2 in the original problem setting of utility
Yousi Zheng
Columbus, OH
614-216-0788
zhengyousi@gmail.com
maximization with deadlines. This is especially important because data center schedulers are often not privy to individual
job deadlines, and thus algorithms that are deadline dependent may be impractical in practice. Further, I compare ISPEED
with widely used schedulers using trace-driven simulations. For these trace driven simulations, we use our own traces
collected with the Google search engine, and also a trace for Bing (collected at Microsoft Research). Our evaluations
further confirm that the deadline-agnostic nature of ISPEED makes it robust over a wide range of scenarios and clearly
outperforms the state-of-the-art schedulers.
A New Analytical Technique for Designing Provably Efficient MapReduce Schedulers (2011-2013)
With the rapid increase in size and number of jobs that are being processed in the MapReduce framework, efficiently
scheduling jobs under this framework is becoming increasingly important. I consider the problem of minimizing the total
flow-time of a sequence of jobs in the MapReduce framework, where the jobs arrive over time and need to be processed
through both Map and Reduce procedures before leaving the system. I show that for this problem for non-preemptive tasks,
no on-line algorithm can achieve a constant competitive ratio. I then construct a slightly weaker metric of performance
called the efficiency ratio. An online algorithm is said to achieve an efficiency ratio of c when the flow-time incurred by
that scheduler divided by the minimum flow-time achieved over all possible schedulers is almost surely less than or equal
to c. Under some weak assumptions, I show a surprising property that, for the flow-time problem, any work-conserving
scheduler has a constant efficiency ratio in both preemptive and non -preemptive scenarios. More importantly, I am able to
develop an online scheduling algorithm ASRPT (Available Shortest Remaining Processing Time) with a very small
efficiency ratio (2), and through simulations I show that it outperforms the state-of-the-art schedulers.
Design of a Power Efficient Cloud Computing Environment: Heavy Traffic Limits and QoS (2009-2011)
Cloud computing is fast being deployed by the industry as a means to provide efficient computing resources. A significant
fraction of the overall cost of cloud computing operation is the amount of power it consumes, which is related to the
number of machines in operation. In order to efficiently manage the power cost associated with cloud computing, I develop
the foundations for designing a cloud computing environment. I consider a GI/H/n queueing system, which has multiple
servers in the queue. Instead of stochastic differential equations, I propose two heavy traffic limits for this system, which
can be easily applied in practical systems. Using the insights gained from our heavy traffic studies, I determine the
minimum number of operational machines needed in the cloud to satisfy its QoS requirement. Finally, using simulation
studies I show that different number of operational machines is critical for different QoS requirements.
Localization Algorithm for Wireless Sensor Networks and Cognitive Radio (200 7-2009)
Localization information is widely used in various location-dependent applications in Ad Hoc, Wireless Sensor Networks
(WSN), and Cognitive Radio (CR). In this work, I analyze the effect of beacon nodes placement strategy on location
estimation accuracy, and propose a placement strategy which has more accurate location estimation. This placement
strategy need no additional hardware, and can be easily implemented. Based on this placement strategy, Precise Long
Range DV-Hop (PLR DV-Hop) algorithm is proposed for wireless sensor networks. As a novel technique which can
effectively improve precious electromagnetic spectrum sources, cognitive radio is rapidly and widely implemented. Many
applications in cognitive radio request position information of the primary users should be achieved during radio-sensing
analysis process, so localization algorithm becomes an important issue in related researches. In this work, I also propose a
practical Robust Distributed Localization (RDL) algorithm for cognitive radio, which makes the secondary nodes
effectively and accurately get the location information of primacy users. Simulation results on the testbed (via Matlab and
C++) show that the proposed algorithms perform better than the state-of-the-art algorithms in 3 aspects: less power, more
accurate, and more robust.
Signal Processing System for Integrated Ship System (2005-2007)
In an integrated ship system, I propose an adapti ve algorithm, which can quickly and precisely trace and capture moving.
To implement the algorithm, I design a signal processing board on FPGA (Xilinx Spartan3), and implement the algorithm
in the board using VHDL hardware language. I also design and implement communication function between computer and
the signal processing board in the integrated ship system.
Yousi Zheng
Columbus, OH
614-216-0788
zhengyousi@gmail.com
INTERNS HIPS
AT&T Labs, San Ramon, CA (Summer 2013)
LTE is focus on the standard and techniques of next generation of wireless communication and networking. However,
there are several unsolved issues in the AT&T running system. I do the data analysis based on the data of running AT&T
LTE system, build up the physical and MAC layer models, and propose improved method or solution. This work includes
KPI correlation in VoLTE (using Python), modeling and evaluation of Carrier Aggregation (using Python and Matlab),
and performance analysis and improvement of Small Cell (using Python).
Nokia Siemens Networks, Beijing, China (2007-2008)
IEEE 802.16m and 3GPP LTE are important steps for the next generation of wireless communications. I p ropose a
frequency domain scheduling algorithm (FDSA) and a link adaptive mechanism with FDSA in the physical layer in IEEE
802.16m. I implement the algorithms in the testbed of NSN, and show the throughput improvement of FDSA compared to
the widely used scheduling method in current systems. I also design and implement efficient ACK code mapping and CRC
error detection in 3GPP LTE testbed, using C++ and Matlab.
Flextronics, Zhuhai, China (Summer 2005)
I propose technological support for Motorola iDEN phones debug line. Meanwhile, I analyze circuit issues, design circuit
checking list, and update maintenance handbook.
PUBLICATIONS
[1] Yousi Zheng, Bo Ji, Prasun Sinha, Ness Shroff, “Forget the Deadline: Scheduling Interactive Applications in Data Centers”, under
review.
[2] Yousi Zheng, Ness Shroff, Prasun Sinha, “Heavy Traffic Limits for GI/H/n Queues: Theory and Application”, under review.
[3] Yousi Zheng, Ness Shroff, R. Srikant, Prasun Sinha, “Exploiting Large System Dynamics for Designing Simple Data Center
Schedulers”, INFOCOM’15.
[4] Yousi Zheng, Ness Shroff, Prasun Sinha, “A New Analytical Technique for Designing Provably Efficient M apReduce Schedulers”,
INFOCOM’13.
[5] Yousi Zheng, Ness Shroff, Prasun Sinha, “Performance Analysis of Work-Conserving Schedulers in M inimizing the Total FlowTime with Phase Precedence”, Allerton'12.
[6] Yousi Zheng, Ness Shroff, Prasun Sinha, Jian Tan, “Design of a Power Efficient Cloud Computing Environment: Heavy Traffic
Limits and QoS”, INFORMS '11.
[7] Lei Wan, Yousi Zheng, Shunliang M ei, “Low complexity user selection scheme for limited feedback M U-M IMO systems”, Journal
of Tsinghua University (Science and Technology), 2010, Issue 4, pp 632-635
[8] Yousi Zheng, Han Wang, Lei Wan, Xiaofeng Zhong, “A Placement Strategy for Accurate TOA Localization Algorithm”, CNS R’09.
[9] Han Wang, Yousi Zheng, Xiaokang Lin, “A Parallel Double-Step CORDIC Algorithm for Digital Down Converter”, CNS R’09.
[10] Yousi Zheng, Lei Wan, Jianfeng Kang, Xiaofeng Zhong, “A Frequency Domain Scheduling Algorithm for IEEE 802.16 OFDM A
Systems”, WOCN’09.
[11] Lei Wan, Yousi Zheng, Xiaofeng Zhong, “Adaptive Codebook for Limited Feedback System”, WOCN’09.
[12] Yousi Zheng, Lei Wan, Shunliang M ei, “A Robust Distributed Localization Algorithm for Cognitive Radio”, APCC’08.
[13] Yousi Zheng, Lei Wan, Zhi Sun, Shunliang M ei, “A Long Range DV-Hop Localization Algorithm with Placement Strategy in
Wireless Sensor Networks”, WiCOM’08.
SOFTWARE SKILLS
Languages
Tools
Skill
C++, Java, JavaScipt, Python
Matlab, LaTex, HTML/CSS, jQuery, Hadoop
Probability, Statistics, Algorithm Design, Cloud Computing, Wireless Communication, Networking,
Optimization, Queueing Theory, Control, Information Theory