...
Together with this we could use the list of PingER perfSONAR hosts that respond to pings. Note that sometimes pings are blocked to a host but TCP port 80 packets work, e.g. adl-a-ext1.aarnet.net.au (202.158.195.68).
Project
We wrote a script ping-vs-tcp.pl. * for analyzing the PingER nodes, and anothter ping-vs-tcp-ps.pl for analyzing perfSONAR nodes.
| Code Block |
|---|
Usage: ping-vs-tcp.pl [opts] Opts: --vhelp print this USAGE information -D-debug debug_level (default=0) -p-prot protocol (6 or '') (default '') -a-port application port (default = 80) --ccount count of pings or npings to be sent (default = 10) Function: Ping the host provided in %NODE_DETAILS (the PingER database of hosts) For each host it gets the IP address either from NODE_DETAILS (IPv4) or using the dig command (IPv6). It then Pings and npings the host and gathers the min, average, maximum RTTs and losses and reports them to STDOUT., together with a time stamp and host information such as name, IP address, countrycontry, region etc. Externals: Requires nping (requires root/sudo privs), dig Input: It gets information on the PingER hosts from %NODE_DETAILS using: wget to get the required file from http://www-iepm.slac.stanford.edu/pinger/pingerworld/slaconly-nodes.cf. The required file is saved in in /tmp with a unique name /tmp/nodes-34589020.cf (where the number is based on the process number). Examples: ping-vs-tcp.pl ping-vs-tcp.pl -p-prot 6 -a-port 22 -c-count 10 | tee pg-v4-nd.txt ping-vs-tcp.pl --help Hint: To turn the output into a real csv file do something like: grep warning -v pg-v4-db.txt > pg-v4-nd.csv Version=0.4, 1/28/2018, Cottrell |
The output is in comma separated value format and is exported to Excel (one file for IPv4, one for IPv6) where it is analyzed to look at the histograms of Average(ping_rtt)-Average(nping_rtt) etc. The script was run from a host (pinger.slac.stanford.edu) located st SLAC in Northern California in the San Francisco Bay Area. It was run multiple times to ensure the behaviour was not dependent on time of day or day of week etc. To ensure the selected target hosts were not unique in some respect we also obtained a list of target hosts from the perfSONAR project, and repeated the analysis for them. Finally to ensure there was not something unique about making the measurements from SLAC, we repeated the measurements to the same sets of targets from MAs in China, Malaysia and Thailand.
...