Les Cottrell and Connie Logg, SLAC
Talk given at ORNL, June 24. 1996
Talk available at http://www.slac.stanford.edu/grp/scs/net/talk/ornl-96/ornl.htm
This performance is affected by the performance of the complete Distributed System, which includes:
Reduction examines the analysis reports and extracts the exceptions e.g.
NMS maps show when a managed critical interface becomes inactive (goes red)
SNMP and ping-polling of critical interfaces results in:
Node |
Avg |
50%tile |
(thresh) |
95%tile |
(thresh) |
---|---|---|---|---|---|
WWW
|
0.036s
|
0.05s
|
(<0.04s)
|
0.055s
|
(<0.1s)
|
Need a probe on every switch/hub port
RMON still handles layers 1 and 2 of OSI model
RMON 2 will enable trouble-shooting tools to
RMON2 also enhances configuration
IETF draft RMON version 2 published as proposed standard and RFC July 1995
Many RMON vendors are already providing proprietary protocol analysis above the OSI layer 2
Require distributed, easy-to-use, heterogeneous "system" management to enable focus to shift to service management
Need to make information digestible
Developing tools is costly and still has to be done in-house
Lots of challenges to come, switched network, RMON2, ATM, increased expectations (job security!)
Also by disappearance of NSFnet (and its coordination) as a network provider to Researchers and Education (R & E)
R & E seriously being impacted
Peering with NSI, NSF and other government agencies
Develop service quality metrics and perfomance measurements:
http://www.slac.stanford.edu/~cottrell/tcom/nmtf-tools.html
For example see the ping loss and response time degradation between SLAC and UCD over the 180 days from Dec '95 to Mar-96.
Note: difference in weekends vs workdays
# Mean Mean Stdev #Std Mean Mean Stdev #StdHot Links to alerts:# 10wks 1 wk 10wks From 10wks 1 wk 10wks From
#Nodename %Loss %Loss Loss Mean Avg Avg Avg Mean
AXPZE1.PD.INFN.IT 2.3 1.3 2.1 -0.5 368.4 156.7 72.1 -2.9
...
Node |
#pings |
#down |
#loss |
%loss |
min response |
max response |
avg response |
---|---|---|---|---|---|---|---|
physics.upenn.edu
|
240
|
0
|
17
|
7.1%
|
89ms
|
102ms
|
92ms
|
Service Predictability
Changes in Service Predictability
Will monitor end-to-end connections for:
Identify and develop metrics and reports to validate and qualify service quality
Extend deployment of monitoring:
"to a significant extent due to the lack of efficient financial pressure on service providers to strengthen the infrstructure" from Metrics for Internet Settlements, by Brian Carpenter CERN
Much effort therefore to identify critical networking metrics and tools than can be employed by users and ISPs to quantify Internet quality of service
Organizations involved include the Federal Networking Council (FNC) and its Advisory Committee (FNCAC), DARPA, Kansas University, Merit, NSF, ESnet/NMTF, National Laboratory for Applied Network Research (NLANR) working with MCI.