Logistical Networking
PIs: Micah Beck, Jack Dongarra, James S. Plank / Tennessee; Rich
Wolski / UCSB
Impact
and Connections
·IMPACT:
·Improved performance and
scalability of data-intensive distributed application
·Greater ease of and lower
cost of deployment of new wide area data management strategies
·Dramatically improved
flexibility in data-intensive collaboration
·CONNECTIONS:
·SciDAC: Net100, Data Grid,
Scalable Systems, Data Mgt, Computational Science (e.g. Climate, Supernovas)
·Base:Network Monitoring, Data
Grid, Transport Protocols, Storage Res. Mgt., IQ-Echo,
Milestones/Dates/Status
–IBP applications demonstrated at SC’01
–exNode support in NetSolve
–Reliability/performance coscheduling alpha
–Allocation policy simulation
– Initial generalized caching
infrastructure
–Initial logistical overlay network on ESNet
–Wide-area logistical peering mechanisms and policies
–Resolution for highly volatile storage resources
–Experimental IBP architectures
–Large scale measurement and simulations
Novel
Ideas
· Storage is too cheap to
hoard.
· Storage can be a
scalably shared network resource.
· Logistical Networking
gives applications and middleware uniform control over buffering and
routing of data.
· Data storage and data
transport can be viewed as points on a spectrum of data management
mechanisms.
· Monitoring and
prediction can replace reservation as a means of scheduling storage
resources.
· End-to-end networking
principles can apply to storage.
Logistical Networking: Developing
a communicative infrastructure with
persistence
Tasks:
-develop/deploy network storage depots
-develop layered storage stack &
tools
-develop/validate scheduling techniques
-optimize application performance
loci.cs.utk.edu
Date Prepared: 1/10/02
Logistical Networking – SciDAC High Performance
Networking
MICS Program Manager: Thomas Ndousse
6-12mos
12mos
12-18mos
18-36mos