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Turing Test The usual caution for measuring anything online is in play here: Be certain you can tell whether you are measuring human activity or bot activity. This is not to say that robots are bad it s just important to know the difference. Robots can scrape, follow, friend, tweet, and retweet, and while that sounds like an abomination of the intent of a social network, bear in mind that one of those nodes in Figure 2.8 may indeed be a small piece of software somewhere. When it s time to tote up how many people had an opportunity to see your message, make sure you re only counting the people. When you think about in uence (see 3: Getting Respect Identifying In uence), then the complexity becomes even more multifaceted.



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Failovers Services and Applications Client Management Local Environment Networking Disk and Volume Management Reliable Backups Good System Administration Practices INVESTMENT

Plj Flj t u dHjl ujx :

Clustering, by the modern definition, means that there is a second system1 configured as a standby for a primary server. If the primary server fails, the standby node automatically steps in and, after a brief interruption in service, takes over the functions of the original primary. Since the standby server can step in and quickly take over for the primary, downtime due to a failure in the primary is limited to that takeover time. In this chapter, after a brief diversion to take a look at the history of clustering, we examine server failover, the physical components that make up a cluster, and how best to configure them to maximize the cluster s availability.

17:28





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It would be arrogant to assume that modern forms of clustering software are the only ones that have ever been available, or even that they are necessarily the best. The most famous early commercialization of clustering took place at Digital Equipment Corporation (DEC; they were acquired by Compaq in 1998; Compaq was in turn acquired by Hewlett-Packard in 2001). DEC s VMS operating system was introduced in 1978, and it quickly achieved great success. In an attempt to maintain and grow that success and to compete with fault-tolerant

Expressed in the form of transforms, Eqs. (17.27) and (17.28) become ^ 1 gk s ^ ^ Pjk sjx % hjk sjx s for j T k and ^ Pjj sjx % ^ 1 gj sjx P f^lj s ^ hjl sjx Plj : s s l 17:30 P^ f^ s hjl sjx Plk lk s l 17:29

There can, of course, be more than one standby system in a cluster, and far more complex configurations. We discuss clustering configuration options in detail in 17, Failover Configurations.

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Numerical inversion can easily be applied with Eqs. (17.29) and (17.30). However, since the time-domain formulas (17.27) and (17.28) involve single convolution integrals, numerical computation of Eqs. (17.27) and (17.28) in the time domain is also a feasible alternative. Moreover, if the underlying distributions have special structure, then the integrals in Eqs. (17.27) and (17.28) can be calculated analytically. For example, analytical integration can easily be done when all holding-time distributions are hyperexponential. In Duf eld and Whitt [15, Section 3] we give a numerical example illustrating how the two approximations compare to the exact conditional mean for a single source with four levels. 17.6 THE VALUE OF INFORMATION

We can use the source model to investigate the value of information. We can consider how prediction is improved when we condition rst, on, only the level and, second, on both level and age. The reference case is the steady-state mean M

The really tricky bit about tracking retweets is that they tend to morph from one to the next, just like that good old game of Telephone. People change the tweets they repeat so a strict algorithm of looking for the same phrase is going to run into trouble. The paper Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter (www.danah.org/papers/TweetTweetRetweet.pdf), published in the IEEE Proceedings of HICCS-43 ( January 2010), describes how human nature confounds Twitter tracking tools. The paper states, Given the inherent dif culty in keeping track of who truly pays attention to whom is hopeless.

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