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09:00:01 up 11 days, 14:19, 0 users, load average: 0.41, 0.70, 0.75 | temp=41.2'C | Start
09:00:09 up 11 days, 14:19, 0 users, load average: 0.73, 0.76, 0.77 | temp=41.2'C | SID plot Finished
Which one of you is Bald Fox? lol
This bunker was used as the plotting room for the South Foreland Battery. This is just the entrance. I believe the rest of the bunker lies in that hole. The bunker is located in a wooded area in St. Margret's Bay, Dover, England. Not far from the South foreland Lighthouse.
11:00:02 up 4 days, 16:19, 0 users, load average: 0.52, 0.61, 0.66 | temp=41.2'C | Start
11:00:10 up 4 days, 16:19, 0 users, load average: 0.74, 0.66, 0.68 | temp=42.2'C | SID plot Finished
The basic approach to construct a map of the internet as a graph is as follows: one runs the traceroute tool from some machines, called monitors, towards some others, called destinations, and then merges all the obtained paths.
The view obtained from each monitor is roughly a tree, and may be modeled as a BFS tree. Although this approximation is rather rough in general, it seems reasonable for the nodes close from the monitor.
The properties of a BFS (for instance, the number of nodes at a each level, called profile of the BFS) are consequences of some properties of the underlying graph. Therefore, one may try to deduce the properties of the internet topology from the ones of the BFS-like measurements we have of it.
The plot above illustrates this approach. It contains three pairs of curves, each pair being composed of a simulation curve and a theoretical prediction which we established. From left to right, the first plot is obtained on power-law graphs, random Poisson graphs and regular graphs, each containing one million nodes. Each curve represents the proportion of nodes at a given distance from the root of a BFS, i.e. the profile of the BFS.
It appears clearly that the shapes of these plots make it possible to distinguish between the three types (power-law, Poisson and regular) of random graphs. Also, our theoretical predictions fit the experiments very well, even though the variance is higher for power-law graphs.
14:00:01 up 1 day, 20:31, 0 users, load average: 0.23, 0.32, 0.38 | temp=41.2'C | Start
14:00:06 up 1 day, 20:31, 0 users, load average: 0.38, 0.35, 0.39 | temp=42.2'C | SID plot Finished
This plot shows how distance between hosts seen among traceroute outputs and the targets of these traceroutes are likely to be multiple regarding to their average distance.
The data is gathered as follows. We first pick up 60 random, ping-answering IP addresses. We then send successively one traceroute from each of 516 Planetlab hosts (called "sources"), towards each of thoses IPs (called "targets"). For a given target, a traceroute is sent a few seconds after the previous one ended (either with a success or a failure). So far we gathered about 31 thousands raw traceroute outputs over about 10 hours.
For each route given by traceroute towards a given target, we look up the distance (in hops) within the route between the target and each address (or node) present in the route - we call this number "trace route distance". This way we get for every target and for each address, its average traceroute distance (which we round to the nearest integer) to target over sources, and whether it appears at least twice at two different distances. Then we compute globally the proportion of nodes appearing at a given, rounded average traceroute distance, that appear at least at two different traceroute distances.
Between average distance 7 and 27, the plot can be compared to an affine function, with a coefficient of 0.7% per hop. Indeed, there is a (statistical) chance at each hop to cross a router balancing between routes of different length, leading to different traceroute distances. Therefore the likeliness to be seen at multiple traceroute distances increases with distance to the target.
The rightmost part of the plot may be quite inaccurate since it is mostly based upon nodes very close to the sources that have no reason to be seen multiple times for a given target source-round (remember that every source performs exactly one traceroute). It should anyway be looked close: how can we explain such a ceiling?
The leftmost part of the plot is far more relevant, since the nodes very close to the target are expected to be seen by many sources. The 0-1-distance bracket is naturally empty, since only targets can have occurences of traceroute distance < 1 (that is, exactly 0). The 1-1.5-distance bracket may seem critically low but it can be explained as follows: since the nodes with an average traceroute distance < 1.5 must have a least 50% of their occurences at traceroute distance 1, then these nodes are very unlikely to be exposed to load-balancing and thus to have multiple traceroute distance occurences.
But the very odd part is the 1.5-3.5-distance bracket. The very high rate of multiple traceroute distance node hints that the nodes of average traceroute distance between 1.5 and 3.5 are very exposed to load balancing, thus yielding the question: where is located the load-balancing involved in these variations?
Close to the target, confusing only the last hops? Then how to explain the local minimum at the 5.5-6.5-distance bracket? Far away from the target, "pushing" some nodes far closer to the target than seen on other routes? Then how to explain the positive coefficient in the linear part of the plot? Would there be two (or more) concurrent processes, with distinct domains of predominance, balancing at average distance 6?
My car (in black) is sitting on the side street between the plot and my neighbours (shown on Vorplan as WEG)
This is a view to the West of plot 5, looking specifically at an area identified as potentially having Anthrax Spores.
Notice a distinct lack of growth in comparison to the surrounding area.
14:00:01 up 2 days, 20:47, 0 users, load average: 1.03, 0.86, 0.75 | temp=48.7'C | Start
14:00:09 up 2 days, 20:48, 0 users, load average: 1.26, 0.92, 0.77 | temp=48.7'C | SID plot Finished
Grimm is the plot bunny who screams "more violence!" whenever the story slows enough to allow his voice to be heard. He's something of an asset - I am writing a revenge-oriented horror story this year, after all - but he wants to wreak his wrath on all that stands in his path, along his path, or within 180* of any potential paths he might want to take.
01:00:01 up 9 days, 6:19, 0 users, load average: 1.20, 0.92, 0.82 | temp=41.2'C | Start
01:00:09 up 9 days, 6:19, 0 users, load average: 1.35, 0.96, 0.83 | temp=41.2'C | SID plot Finished
Title: Plot Plant
Digital Publisher: Digital: Cushing Memorial Library and Archives, Texas A&M University, College Station, Texas
Physical Publisher: Physical: Agricultural Communications Office of the Texas Agricultural Extension Service, Texas A&M University
Description: year (coverage): Unknown
Date Issued: 2011-08-17
Dimensions: 4 x 5 inches
Format Medium: Photographic negative
Type: image
Identifier: Photograph Location: Agricultural Communications Collection, Box 40, File 40-676
Rights: It is the users responsibility to secure permission from the copyright holders for publication of any materials. Permission must be obtained in writing prior to publication. Please contact the Cushing Memorial Library for further information
DLF group announced a new residential plots in sector 91 & 92 Gurgaon and very good connectivity with KMP Expressway. DLF plots in Gurgaon are highly promising, because property prices in Gurgaon are going upwards. DLF plots is not only beneficial for those who are in search of residential property in Gurgaon but for those also who are interested in high returns from investment on property. The sizes of DLF Plots are 224 Sq yd - 500 Sq yd.
For any integer x from 1 to 254, I launched a query on yahoo.com on the word yoooooo, with x o's. In other words, I first launched a query on yo, then yoo, yooo, yoooo, yooooo, and so on. Why would I do so? Ask Fabien!
For each such query, I recorded the number of answers found by yahoo, and thus I ended with a number of answers for each value between 1 and 254, which is plotted above (black dots). (I had to stop at 254 because yahoo does not seem to accept queries on longer words).
For the sake of comparison, I did the same thing with various letters in place of o, and other variants. For instance, what I would call the yaaaaa distribution is very similar to the yooooo one. The yxxxxx one, represented on the plot by blue dots, is quite different (significantly below, and maybe sharper slope).
The green line in the plot represents y ~ x^-3 (i.e. the inverse of x to the cube). It fits pretty well the yooooo distribution, showing that it is close to a power-law of exponent 3...
14:00:02 up 12 days, 19:19, 0 users, load average: 0.77, 0.66, 0.70 | temp=40.6'C | Start
14:00:09 up 12 days, 19:19, 0 users, load average: 0.87, 0.68, 0.70 | temp=41.2'C | SID plot Finished
Plot 100: Catherine Wilcock Stephen (58) 1972
Francis Beattie Stephen (73) 1979 – Head Glassblower grandfather
STEPHEN
In Loving Memory
of
CATHERINE WILLCOCK
beloved wife of
Francis
and loving mother of
Dorothea & Frank
passed away 29th Mar. 1972.
aged 58.
FRANCIS BEATTIE
beloved husband of
Catherine
and a loving father
and grandfather
passed away 26th May 1979
aged 76.