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Empirical evidence in support of complex within-connection or local traf c characteristics in measured wide-area traf c that can be traced to the dominant TCP=IP protocol hierarchy of IP networks has been reported in the original comprehensive analysis of WAN traces by Paxson and Floyd [25] and, more recently, in work by Feldman et al [12] The original ndings of multifractal scaling behavior of measured aggregate WAN traf c are due to Riedi and Levy-Vehel [30] (see also Levy Vehel and Riedi [36]), followed by a similar study by Mannersalo and Norros [24] involving measured ATM WAN traces (for an earlier discussion on multifractal scaling and measured LAN traf c, see also Taqqu et al [35]) Motivated by the empirically observed multifractal scaling behavior in measured WAN traf c by Riedi and Levy Vehel [30], Feldmann et al [11] (see also Gilbert et al.



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Don t change binary images in-place. Make sure you do the distribution to a new directory, and then move the entire directory into place. Clients that were using the old binary will continue to do so until another reference opens the updated file. If you replace files on the fly, clients that are paging text (instructions) on demand from them may become confused and crash when the text pages change underneath them.





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[14]) present a more detailed investigation into the multifractal nature of network traf c and bring multifractals into the realm of networking by providing empirical evidence that WAN traf c is consistent with multifractal scaling because IP networks appear to act as conservative cascades In particular, they demonstrate that (1) conservative cascades are inherent to wide-area network traf c, (2) multiplicative structure becomes apparent when studying data traf c at the TCP layer, and (3) the cascade paradigm appears to be a traf c invariant for WAN traf c that can coexist with self-similarity By systematically investigating the causes for the observed multifractal nature of measured network traf c, they observe that the packet arrival patterns within individual TCP connections (where one or more TCP connections make up a session) appear to be consistent with a multiplicative structure.

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An example of software replication helps to illustrate these rules. Consider how you build up a directory in which local tools, libraries, manual pages, and other locally important files reside. The standard approach is to have one tools directory on a large file server that all clients share; changes are made to the file server, and all of the clients see them within a short window. Note that the quick-and-dirty method introduces a SPOF at the file server and isn t scalable for performance. If your client load is going to increase over time, you ll need to be able to crank up the horsepower of the tools directory server at the same time, and that means multiple copies of it, close to where its users are on the network. The single tools directory also leaves you open to process weakness in change management. What if your latest software installation has a broken install script and trashes the tools directory With replication and change management you have built processes to recover from internal corruption. Test a new or modified tool by building a new area within the shared directory, verifying operation using the master, and then pushing the replication to the slave servers.

The latter, they argue, seems to be mainly caused by networking mechanisms operating on small time scales and results in aggregate network traf c that exhibits multifractal scaling behavior over a wide range of small time scales Although it is tempting to invoke the TCP=IP protocol hierarchy of modern data networks for motivating the presence of an underlying conservative cascade construction (eg, a Web session generates requests, each request gives rise to connections, each connection is made up of ows, ows consist of individual packets), Feldmann and co-workers demonstrate that the multiplicative structure associated with a conservative cascade construction is most apparent when studying network traf c at the TCP layer, where the network behavior (ie, the way the packets within a TCP connection are sent across the network) is largely decoupled from the user behavior.

Moreover, Feldmann and co-workers suggest that the transition from multifractal to self-similar scaling occurs around time scales on the order of the typical round-trip of a packet within the network under consideration..

Database replication buys you protection against several disasters: corruption of your primary database, failure of an operational system when the MTTR is measured in seconds not minutes, and in some cases protection from a fullfledged physical disaster. Database replication can rely on variations of file distribution tricks, using log replay, built-in database features such as distributed transaction management, or third-party transaction processing and queuing systems that guarantee delivery of transactions to multiple database instances on multiple servers.

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