EE599-Lec26-Hwang-BigData2-Nov26-2013-Updated - What is...

1
Prof. Kai Hwang, USC, Nov. 22, 2013
Big-Data Analytics and Cloud Security
for Trusted Cloud Computing
Lec.26 of EE 599, Nov.26, 2013,
Prof. Kai Hwang
University of Southern California
1
boxshadowdwn
Four Research Frontiers : BigData, Clouds, Social Networks,
and the Internet of Things
boxshadowdwn Shortage of Big-data Analytics, Security and Privacy hinder the
acceptance of clouds, social networks and IoT services.
boxshadowdwn Crucial R/D Challenges are identified and some new Approaches
and Opportunities are revealed in this talk.
2
What is Data Science ?
s)
• Data Science
is the extraction
of actionable knowledge directly
from data through a process of
discovery, hypothesis, and
analytical hypothesis analysis.
• A
Data Scientist
is a
practitioner who has sufficient
knowledge of the overlapping
regimes of expertise in business
needs, domain knowledge,
analytical skills and
programming expertise to
manage the end-to-end scientific
method process through each
stage in the big data lifecycle.
Big Data
refers to digital
data volume, velocity and/or
variety whose management
requires scalability across
coupled horizontal resources
3
Prof. Kai Hwang, USC, Nov. 25, 2013
•
Practitioners
consider themselves Data Scientists
•
Phones, Sensors, Social Networks and IoT are new
sources of Big Data
square4
Radar, Light Synchrotrons, Smartphones,
Bio-imaging, RFID, Sensors, GPS, etc.
3
•
Hadoop and HDFS dominant
•
Business – main emphasis at NIST – interested in
analytics and assume HDFS
•
Academia seem more interested in data
management
•
Clouds vs. Grids and Grid of Clouds
Modern Big-Data Characteristics:
4
Prof. Kai Hwang, USC, Nov. 25, 2013
4
The Case of Photos (Images)

5
Prof. Kai Hwang, USC, Nov. 25, 2013
1. Government Operation:
National Archives and Records
Administration, Census Bureau
2. Commercial:
Finance in Cloud, Cloud Backup, Mendeley
(Citations), Netflix, Web Search, Digital Materials, Cargo shipping
3. Defense:
Sensors, Image surveillance, Situation Assessment
4. Healthcare and Life Sciences:
Medical records, Graph and
Probabilistic analysis, Pathology, Bioimaging, Genomics,
Epidemiology, People Activity models, Biodiversity
5. Deep Learning and Social Media:
Driving Car, Geolocate
images/cameras, Twitter, Crowd Sourcing, Network Science,
NIST benchmark datasets
51 Use Cases of Big Data:
from TB’s to PB’s
5
6
Prof. Kai Hwang, USC, Nov. 25, 2013
6. The Ecosystem for Research
: Metadata, Collaboration,
Language Translation, Light source experiments
7. Astronomy and Physics:
Sky Surveys, Large Hadron Collider
at CERN and Belle Accelerator in Japan
8.