Deployment
Monitoring Hosts
In 2010, following a series of workshops and site visits, the team at SEECS /NUST and SLAC worked with Pakistan’s Education and Research Network (PERN) and Pakistani Universities to put together an end-to-end (E2E) network monitoring infrastructure for PERN connected higher education sites. By the end of 2010 they had have installed the PingER monitoring tools and started gathering data at 18 sites in Pakistan. This includes 4 sites (SEECS/NIITNUST, COMSATS, PERN and NCP/Quaid-i-Azam) which have been in place for a longer time. In addition they are working on a further 8 monitoring sites. Over 2010 the number of monitoring host – remote host pairs (both in Pakistan) has increased from about 30 to over 220.
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The growth in the number of monitors and host pairs being monitored over 2010, is seen below (spreadsheet):
Map of sites
The locations of the Pakistani monitoring (red) and remote(red and blue) hosts are seen in the maps below.
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Pakistani PingER sites with lines showing the minimum RTT in msec. seen from NUST | Details of PingER sites in Islamabad, the lines show the average RTT seen from NUST | Details of PingER sitesv in Islamabad, the lines show the minimum RTT from PERN |
It is interesting to see (right hand map above) the large differences in minimum RTT between PERN and say NCP (at Quaid i Azam university in N.E. Islamabad) of < 10msec (blue line or more exactly 1.3msec) and that between PERN and NUST in the S.W. corner of between 40-80msec (red line or more exactly 44msec.). Presumably this is due to the routing of PERN connections in Islamabad region. Also interesting to see (middle map above) is that the connection from NUST to the DSL site (blue line) is much less than that to the physically closer NUST host.
Archive, analysis site
IN 2010, a second instance of the SLAC archive-analysis site was set up at NUST. This provides backup for data and access, and improved performance for Pakistani users.
Measurements
Using PingER, the monitoring hosts ping each remote host with 10 pings every 30 minutes. From this data we are able to measure minimum and average Round Trip Times (RTT), jitter, loss, unreachabilty (all 10 pings fail) and derive throughput and Mean Opinion Score (MOS). The data is gathered from the monitoring sites on a daily basis by the archiving and analysis sites at SEECS (this was also set up in the last 18 months) sites at NUST, SLAC and FNAL.
RTT and Losses for 2010
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| Various percentiles for the Inter Packet Delay Variation (IPDV ) or jitter) between Pakistani monitoring hosts and remote host pairs. The line shows the number of pairs with measurements contributing to the results. Spreadsheet | The blue dots are the median losses seen between all pairs of monitoring and remote hosts for each month. The error bars show the extent of the 25 and 75 percentiles. The red dots are the number of pairs contributing to the packet loss measurements. |
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To try and show the network performance trends within Pakistan in 2010 Amber created a graph showing the inter-regional average RTT performance over the whole year.
Unreachability
A host is considered unreachable if none of the pings sent to it are responded to. To illustrate this we chose a reliable host at SLAC (pinger.slac.stanford.edu) and analyzed the unreachability of Pakistani hosts seen from SLAC.
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Table of unreachability seen from SLAC to Pakistani hosts in 2010. Higher values (bad) are colored redder. The data is sorted by increasing unreachability in Jan 2011. Spreadsheet | Chart of the unreachability of Pakistani hosts seen from SLAC Dec 2010 and Jan 2011 | Smokeping examples of unreachabilltyseen from SLAC for 120 days Oct 2010 - Jan 2011. |
It is seen that several hosts exhibit high unreachability. The reasons behind the high unreliability are usually site specific and vary from lack of reliable power and a source of backup power, floods, lack of access to the site when there are problems that require physical access, lack of expertise, and lack of interest from a site.
Understanding the large variations Jan-Apr 2010
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We then looked to see what portion of the larger IPDV early in the year was related to adding now new monitoring and remote hosts. If we select the same host-pairs in both say Nov 2010 and April 2010 then the improvement ((ipdv(Apr)-ipdv(Nnov))/ipdv(Apr) in IPDV is about 47%. Thus things have improved with lower IPDVs for the selected host pairs.
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