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Our analysis of TCP connections is based on trace analysis of transmission control protocol=Internet protocol (TCP=IP) internetwork traf c. The traces were collected on three different Ethernet segments at Carnegie Mellon University (CMU), AT&T Bell Laboratories, and AT&T Labs Research using the tcpdump packet capture tool [24] running the Berkeley Packet Filter [28]. The number of packets that tcpdump reported dropped by the kernel was negligible. The rst set of traf c data was collected on an Ethernet segment of the School of Computer Science at CMU that is one of a total of 18 Ethernet segments that are bridged through a backbone with an aggregate 0.5 Gbit=s throughput. The workstation we used for the trace collection (DEC Alpha 400=300 with 64 Mbytes RAM) is connected to a segment that connects approximately 120 systems, including UNIX workstations, MacIntoshs, and PCs. The second traf c data set was collected on an Ethernet segment at AT&T Bell Laboratories. The third traf c data set was collected on the same Ethernet segment shortly after the split of AT&T Bell Laboratories into AT&T Labs Research and Lucent Bell Laboratories. The workstation we used for the second set of traces (SGI with one 134 MHz MIPS R4600 processor and 64 Mbytes RAM) was connected to AT&T Bell Laboratories' internal network while the workstation for the third set of traces (SGI with one 100 MHz MIPS R4000 processor and 64 Mbytes RAM) was connected to an Ethernet segment outside AT&T's rewall. During some trace collection periods all TCP connections (including all World Wide Web access) to the external Internet passed this Ethernet segment. We refer to the second set of traces as the internal AT&T traces and to the third set as the external AT&T traces.

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Fig. 2.4 Logscale diagrams with biscaling. Internet UDP packet data displaying two scaling regimes, examples of biscaling. Left: Delay series. Regime I on the left (small j's) is related to continuous but nondifferentiable sample paths h P 0; 1 and regime II (large j's) to longrange dependence. Right: Loss series (1 for lost packets, else 0). Regime I corresponds to discontinuous sample paths h < 0 . In regime II there is trivial white noise scaling a 0 , indicating stationary SRD behavior.

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Threadjoin can be used to write clients such as the following PictureApp class (which invokes several made-up methods just for the sake of illustration) It creates a Runnable waiter

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the context of delays (left) and losses (right) experienced by consecutive user datagram protocol (UDP) packets sent over the Internet in a regular stream (see Andren et al. [12] for details of such data sets). In both gures the alignment at large scales corresponds to long-range dependence, whereas at small scales it is associated with highly irregular sample paths. Note that when second-order properties are insuf cient to fully describe the scaling nature of the process (an extreme example is afforded by multifractals), then the correct interpretation of each branch of the bisecting will require the examination of logscale diagrams across a range of orders, as discussed in Section 2.3.3. 2.3.2 Estimation Within the Logscale Diagram

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This section describes the image header for Symbian OS executable les, as de ned in the le F32IMAGE.H. There are three formats for the E32ImageHeader: Basic format header contains no compression, security or version number information J-format header may contain compression information. In addition to the basic format elds, if the compression type (at offset 1C) is nonzero, the header includes an extra eld holding the uncompressed size of the le V-format the executable contains versioning and security information. In addition to the basic and J-format elds, the header includes extra security and versioning related elds. Basic format elds: Offset (hex) 00 04 08 0C 10 14 UID 1 UID 2 UID 3 Checksum of UIDs. Signature ( EPOC = 0x434F5045). CRC-32 of entire header for V-format, CPU identi er for original and J-formats. Description of eld

In this subsection it is assumed that a scaling range j P j1 ; j2 has been correctly identi ed Sums over j, and regressions, are always taken over this range The estimators to be de ned are semiparametric, as they depend on the range of scales j P j1 ; j2 , where scaling is deemed to be present, and the scaling property P1 valid there, but not on any tightly speci ed parametric model 2321 Estimating the Scaling Exponent a Because of property P1, the measurement of a is reduced to the determination of the slope over the alignment region in the logscale diagram A natural way to achieve this in a statistical estimation context is through linear regression, the de ning hypothesis of which is Eyj a j a, where a is a real constant.

While it is common practice, the use of unsynchronized (or direct) access of internal result fields as seen in the waiter object is a bit delicate Since access is not synchronized, correctness relies on the fact that both thread termination and the join method intrinsically employ synchronized methods or blocks (see 227)

Because in general E log T log E , this condition is not exactly satis ed, however We therefore introduce small corrective deterministic factors g j , discussed below, and rede ne the yj as yj log mj g j , so that Eyj aj a by de nition Any kind of linear regression of yj on j constitutes an unbiased estimator of a, as the lack of bias does not require decorrelation between the yj , nor knowledge of their variances or distributions A weighted regression where the weights are related to the variances s2 of the yj is preferable, however, as this is the minimum variance j unbiased estimator (MVUE) for the regression problem [48] Intuitively this re nement is signi cant as we know that the s2 are far from equal.

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