J.J. Garcia-Luna-Aceves

 Cancer Genome Hub (CGhub)
 CGhub’s purpose was to store the genome’s sequenced as part of The Cancer Genome Atlas (TCGA) project.
 At about 300 GB/genome this translated to about
17,000 genomes over the 44 month lifetime of the project.
 Transmission requirements of archiving effort reached a sustained rate of 17 Gbps by the end of the 44 month project

Cancer Genomics Hub (UCSC) is Housed in SDSC CoLo:
Large Data Flows to End Users
1G
8G
Cumulative TBs of CGH
Files Downloaded
30 PB
15G
Data Source: David Haussler,
Brad Smith, UCSC

CGHub had to use current technology:
 Data organization and search: XML schema definitions
 Security: Existing techniques, HTTPS
 Big data transfer: Modified Bit Torrent (Gene Torrent or GT)
• HTTPS and Bit Torrent are problematic
• No caching with
HTTPS
• TCP limitations percolate to multiple connections under BT or GT
• A potential playground for DDoS?

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Is the Internet ready to support personalized medicine?
Is the future of genomic data really different?
 If not, what technology would be limiting progress?
First:
 Genomic data are really BIG DATA.
Personalized medicine will make genomic data volumes explode, and many other applications of genomic data will develop
Even if one site or a few mirrors are used for a personal genome, it has to be uploaded.

 Communication, storage and and computing technologies are not the problem:
– Production optical transport @ 1
Tbps http://www.lightreading.com/document.asp?d
oc_id=188442&
– Individual hosts able to transmit at 100 Gbps
– I/O throughput can keep up with the network speeds (i.e., disk will be able to handle 100 Gbps =
12.5 GBps).
– Memory and processing costs will continue to decline.

 Speed of light will not increase  but number of genomic data repositories or distance between them will
 Internet protocol stack was not designed for BIG
DATA transfer over paths with large bandwidthdelay products:
– TCP throughput
– DDoS vulnerabilities (e.g., SYN flooding)
– Caching vs privacy (e.g., HTTPS)
– Static directory services (e.g., DNS vs content directories).

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TCP and variations (e.g., BT) cannot be the baseline to support big data genomics
Storage must be used to reduce bandwidth-delay products
Simulation results
-4-day simulation
-20 locations
-40 Gbps links with 5 to
25ms latency
- ave. degree of 5
TCP (client/server)
Content centric approach

 TCP/IP architecture must change for BIG DATA, but how?
 Content Centric Network architectures (CCN) such as NDN and CCNx have been proposed
 The main advantage of CCN solutions is caching
 But…NDN and CCNx still at early stages of development
 Big Data Networking is all about bandwidth-delay product, not replacing IP addresses with names