CS Colloquium Series @ UCY
Department of Computer Science - University of Cyprus
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Colloquium Coordinator: Demetris Zeinalipour
Colloquium: Load Management for Big Streaming Data, Prof. Panos K. Chrysanthis (University of Pittsburgh, USA), Thursday, July 31, 2014, 11:00-12:00 EET.
The Department of Computer Science at the University of Cyprus cordially invites you to the Colloquium entitled:
Load Management for Big Streaming Data
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Speaker: Prof. Panos K. Chrysanthis |
Abstract:
For the past few years, our group has been working on problems related
to Big Data through several projects. After briefly discussing these
projects, the rest of this talk will present DILoS, which focuses on
three of the eight Big Data's Vs, i.e., volume, velocity and
variability.
Today, the ubiquity of sensing devices as well as of mobile and web
applications continuously generates a huge volume of data which takes
the form of streams that are typically high-velocity (speed) and high-variability (bursty).
In order to meet the near-real-time requirements of the monitoring applications and of the
emerging ``Big Data'' applications, data streams need to be
continuously processed and analyzed. Such processing happens
inside Data stream management systems (DSMSs), which efficiently
support continuous queries (CQs). CQs inherently have different levels of criticality and hence
different levels of expected quality of service (QoS) and quality of
data (QoD). In order to provide different quality guarantees to different client stream
applications, we developed DILoS, a novel framework that exploits the
synergy between scheduling and load shedding in DSMS. In overload
situations, DILoS enforces worst-case response times for all CQs while
providing prioritized QoD, i.e., minimize data loss for query classes
according to their priorities. We further propose ALoMa, a new
adaptive load manager scheme that enables the realization of the DILoS
framework. ALoMa is a general, practical DSMS load shedder that
outperforms the state-of-the-art in deciding when the DSMS is overload
and how much load needs to be shed. We implemented DILoS in our real
DSMS prototype system (AQSIOS) and evaluate its performance for a
variety of real and synthetic workloads. Our experiments show that
our framework (1) allows the scheduler and load shedder to
consistently honor CQs' priorities and (2) maximizes the utilization
of the system processing capacity to reduce load shedding.
Short Bio:
Dr. Panos K. Chrysanthis is a Professor of Computer Science and the
founding director of the Advanced Data Management Technologies
Laboratory (ADMT Lab) [http://db.cs.pitt.edu] at the University of
Pittsburgh. His lab has a broad focus on user-centric data management
for scalable network-centric and collaborative applications and has
fostered interdisciplinary collaborations between computer science,
medicine and astronomy, both within and outside the University of
Pittsburgh -- he is an Adjunct Professor at the Carnegie Mellon
University and at the University of Cyprus, Cyprus. In 1995, he
received one of the first NSF CAREER Awards for his pioneer work on
mobile data management and in 2010, he was recognized as a
Distinguished Scientist by ACM. In 2007, he was also elevated to the
level of a Senior Member of IEEE. He is currently on the editorial board of
IEEE TKDE and the Parallel and Distributed Databases Journal.
DILoS was developed in collaboration with Thao N. Pham (as part of her
PhD thesis) and Alexandros Labrinidis who is the co-director of the ADMT
lab. This work has been funded in part by two NSF Awards and a gift from
EMC/Greenplum.
Sponsor: The CS Colloquium Series is supported by a generous donation from  |