Subject: I-D Action: draft-xiang-alto-exascale-network-optimization-03.txt

From: [email-masked]
Date: Mon, 03 Jul 2017 11:14:16 -0700

A New Internet-Draft is available from the on-line Internet-Drafts directories.

        Title           : Resource Orchestration for Multi-Domain Data Analytics
        Authors         : Qiao Xiang
                          Harvey Newman
                          Greg Bernstein
                          Haizhou Du
                          Kai Gao
                          Azher Mughal
                          Justas Balcas
                          Jingxuan Jensen Zhang
                          Y. Richard Yang
	Filename        : draft-xiang-alto-exascale-network-optimization-03.txt
	Pages           : 25
	Date            : 2017-07-03

Abstract:
   Data-intensive analytics is entering the era of multi-domain,
   geographically-distributed, collaborative computing, where different
   organizations contribute various resources to collaboratively
   collect, share and analyze extremely large amounts of data.  Examples
   of this paradigm include the Compact Muon Solenoid (CMS) and A
   Toroidal LHC ApparatuS (ATLAS) experiments of the Large Hadron
   Collider (LHC) program.  Massive datasets continue to be acquired,
   simulated, processed and analyzed by globally distributed science
   networks in these collaborations.  Applications that manage and
   analyze such massive data volumes can benefit substantially from the
   information about networking, computing and storage resources from
   each member's site, and more directly from network-resident services
   that optimize and load balance resource usage among multiple data
   transfers and analytics requests, and achieve a better utilization of
   multiple resources in clusters.

   The Application-Layer Traffic Optimization (ALTO) protocol can
   provide via extensions the network information about different
   clusters/sites, to both users and proactive network management
   services where applicable, with the goal of improving both
   application performance and network resource utilization.  In this
   document, we propose that it is feasible to use existing ALTO
   services to provides not only network information, but also
   information about computation and storage resources in data analytics
   networks.  We introduce a uniform resource orchestration framework
   (Unicorn), which achieves an efficient multi-resource allocation to
   support low-latency dataset transfer and data intensive analytics for
   collaborative computing.  It collects cluster information from
   multiple ALTO services utilizing topology extensions and leverages
   emerging SDN control capabilities to orchestrate the resource
   allocation for dataset transfers and analytics tasks, leading to
   improved transfer and analytics latency as well as more efficient
   utilization of multi-resources in sites.

The IETF datatracker status page for this draft is:
https://datatracker.ietf.org/doc/draft-xiang-alto-exascale-network-optimization/

There are also htmlized versions available at:
https://tools.ietf.org/html/draft-xiang-alto-exascale-network-optimization-03
https://datatracker.ietf.org/doc/html/draft-xiang-alto-exascale-network-optimization-03

A diff from the previous version is available at:
https://www.ietf.org/rfcdiff?url2=draft-xiang-alto-exascale-network-optimization-03

Please note that it may take a couple of minutes from the time of submission
until the htmlized version and diff are available at tools.ietf.org.

Internet-Drafts are also available by anonymous FTP at:
ftp://ftp.ietf.org/internet-drafts/