On January 31st, 2008, the NY Times, BBC, The Guardian, CNN and many others reported that one undersea cable was damaged near Alexandria, Egypt, and the other another in the waters off Marseille, France. The two cables were damaged Wednesday morning , which are separately managed and operated, of January 30th 2008. They were damaged within hours of each other. Operators believe the damage was caused by ship's anchors during a heavy storm at sea. One of the cables, Sea Me We 4, is owned by 16 telecommunications companies along its route. The second cable, known as the Flag (for Fiber-optic Link Around the Globe) System, runs from Britain to Japan. The cables are separately managed and operated. The outages mainly affected the Middle East and Asia. Most disrupted communications were quickly rerouted through other cables. We decided to look at the impact on Internet connectivity as seen by the PingER project measurements.
Looking at the hourly ping losses (there are ~20 pings in an hour, so a loss of 1 ping is 5% loss) seen from SLAC for January 30th 2008 for large increases in losses which persisted to the end of the day (to avoid regular diurnal change), the main effects seen were on:are shown in Table 1. The Loss before is the average loss before the outage, the Loss after is the loss after the outage started. The Sites affected is the number of sites monitored in the country that observed an effects, the total is the total number of sites monitored in the country. The impact of such losses can make many applications unusable.
Country | Loss before | Loss after | Sites affected / total |
---|---|---|---|
Sudan | < 4.5% | > 15% | 3/3 |
Bahrein | 0% | >10% | 2/2 |
UAE | <4.5% | >20% | 1/1 |
Jordan | 0% | >15% | 4/4 |
Oman | 0% | >15% | 1/1 |
Qatar | 0% | >4.5% | 1/1 |
Saudi Arabia | 0% | >4.5% | 2/3 |
India | 0% | >50% | 2/8 |
Table 1: Hourly Ping Losses
Since the effect may have been transitory while the data was re-routed we looked for increases in losses on January 30th. The effect was seen in about 15 countries of the over 150 countries monitored by PingER. This is shown in Table 2 below.
Coiuntry Country | Loss before | Los Loss after | Sites affected / total |
---|---|---|---|
Egypt | <1% | >7.5% | 3/3 |
Sudan | <5% | >30% | 3/3 |
Hong Kong | <0.75% | >11% | 1/1 |
UAE | <4% | >18% | 1/1 |
Bahrein | <1.5% | >7% | 2/2 |
Jordan | <3% | >7% | 3/4 |
Oman | <8% | >13% | 1/1 |
Saudi Arabia | <1.2% | >7% | 2/3 |
Syria | <3% | >7% | 1/1 |
Indonesia | < 2% | >8 | 1/7 |
Thailand | <0.2% | >8% | 1/6 |
Bangladesh | <5% | > 7% | 2/2 |
India | <3% | > 40% | 2/8 |
Sri Lanka | <3% | >6% | 2/5 |
Maldives | <1% | >12% | 1/3 |
Table 2: Daily Ping Losses
The diffrences differences between the dialy daily and hourly tables may refelect reflect the sites/countries abilities to switch to alternate routes.
Looking further into data by PingER we can estimate the approximate start time for this event. The exact time is a bit harder to explain but it is generally between 5 AM and 7 AM GMT on January 30th 2008 for most of the countries in table 1 with the only exception of Bahrain where it all started at 9AM. The difference differences might be due to to the measurement sampling rate or monitoring hosts host clock synchronization issueissues.
PingER calculates throughput of different nodes from the Round Trip Time (RTT) and loss using the Mathis formula. It is interesting to see the effect on throughput of the regions suffered from fibre outage. Below is the table which gives us the us insight on the throughput of countries effected affected by this outage.
Countries | Throughput before (kbits/s) | Throughput after (kbits/s) | Sites affected / total |
---|---|---|---|
UAE | 1200 | 21 .31 | 1/1 |
Bahrain | 800 | 23 | 2/2 |
Jordan | 500 | 30 | 3/4 |
Oman | 125 | 18 .42 | 1/1 |
Saudi Arabia | 800 | 30 | 2/3 |
Bangladesh | 400 | 35 | 2/2 |
India | 800 | 38 | 2/8 |
The above table shows the average of throughput before and after fibre outage. The results clearly show the problem faced by countries of the regions which got badly hit by this outageorder of magnitude reductions in throughput.