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All in all the traf c mixes observed on three Ethernets (two carrying mostly localarea traf c, and one, at AT&T, carrying mostly wide-area traf c) re ect different, but not uncommon, TCP connection usage patterns. We have applied the same analysis techniques to some of the LBL and DEC traces collected prior to 1996 that were used for the study by Paxson and Floyd [35] (available through the Internet Traf c Archive [21]). Most of the results are similar to the results we get for the CMU and AT&T datasets. In the cases where the results differ we will brie y comment on how and why they differ. The key to understanding the difference is that the use of the network has changed with more and more people using the Web and better and better wide-area networking connectivity. The main difference between the traces is that the amount of HTTP traf c in some of the traces considered here is substantially larger than in the LBL and DEC traces we considered. In addition, we selectively analyze more recent traces collected from a commercial ISP, AT&T's WorldNet. For these traces the Web is the dominant application. HTTP transfers are responsible for more than 85% of all of the TCP connections and more than 50% of all the packets. The difference between the percentages is because Web downloads on average involve a smaller number of packets than some of the other applications. 15.4 SELF-SIMILARITY OF CONNECTION ARRIVAL PROCESS



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A memory access failure, leading to an exception, may be caught with a signal handler that prints out some diagnostic information However, if the diagnostic routine tries to allocate memory to format a print string, the diagnostic routine is likely to fail as well Providing as much information as possible about memory-related problems such as access protection faults may be helpful to developers looking to fix the problem It won t help bring the application back quickly; you ll need to restart the application or do a failover to recover Note that Unix operating system.





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Intuitively, an arrival process is consistent with a Poisson process if it is a superposition of many independent sources whose activity is more or less memoryless. Before the Web became the dominant application of the Internet, this was mostly true for the then dominant applications: TELNET and FTP CONTROL. Just because a user had initiated one telnet session did not necessarily imply that he=she was going to be more likely to initiate another telnet session. The Web changed this principle. Once a user starts browsing he=she is much more likely to download another set of Web pages than to stop after just one Web page. After all, nding the ``right'' information on the Web is not always easy. This implies that the arrival process may not be consistent with a Poisson process anymore. Indeed, the arrival process of TCP connections shows self-similar behavior. To support this claim Fig. 15.1 shows a series of plots of the arrival process (i.e., number of connection arrivals per time unit) for HTTP connection arrivals for three different choices of time units for the external AT&T trace from 18 November to 8 December 1995. Starting with a time unit of 312.5 minutes (Fig. 15.1(a)), the subsequent plot is obtained from the previous one by decreasing the time unit by a factor of 25, increasing the time resolution by the same factor, and concentrating on a random subinterval of the previous plot. All plots look very ``similar'' to each other regardless of the chosen time scale. The burstiness of the connection arrival does not seem to decrease as the time resolution is decreased. Rather we see the same degree of variability for all time resolution. Similar plots can be obtained for other datasets as well as other applications or shorter time intervals.

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failures, or panics, are sometimes due to memory access problems within the kernel. Other application-specific failures, such as floating-point exceptions, should also deliver a signal to the offending process. If possible, the process can take corrective action sometimes these failures are due to code that attempts to be more precise than input or data items allow, resulting in an underflow or divide-by-zero problem. In other cases, a floating-point exception is entirely unexpected, and dumping out whatever state information is relevant will help in diagnosing the problem further. None of these graceful exit techniques improves recovery or reliability; they merely make life easier the next time by helping your development teams locate and eliminate problems or by gently steering users to corrective action. However, the best failure is one that doesn t happen, so we re going to turn our focus to preventing application-level failures, starting with adding resiliency and recovery in the face of system resource exhaustion.

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