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This one speaks for itself. If you said something that is worthy of repeating, then you get a gold star. You also get to think long and hard about why your pearls of wisdom were worth repeating. You must have said something that was fun, interesting, or useful, and if you don t know which, you are wasting your time. Fun and interesting are great for holding the attention of a crowd, but just like funny television ads that you describe to your friends the next day but cannot recall the product, you are not creating value. If everybody remembers Burger King for having the zaniest ads, does that drive food sales Retweets alone are not going to tell you. But as metrics that point the way to value generation, retweets beat the heck out of following/follower ratios. Things get interesting, of course, if you layer retweets with who is doing the retweeting. If only those who have three followers are retweeting your pithy prose, then a million retweets will only make you feel good for engaging a high number of low-value people.



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As we move on to discuss replication, we move up to Level 9 on the Availability Index, as shown in Figure 18.1. Replication most commonly means file and data replication, but as we will discuss in 19, Virtual Machines and Resource Management, processes can also be replicated to make them more highly available, and as we discussed in 16, Failover Management and Issues, process states can also be replicated to increase their availability. In this chapter, we limit our discussion to the replication of files and data.

Mukherjee and A Adas An MPEG2 traf c library and its properties http:==wwwknoltexcom=papers=mpeg2Libhtml 20 I Norros On the use of fractional Brownian motion in the theory of connectionless networks IEEE J Select Areas Communi 13(6):August 1995..

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21. P. Pancha and M. El Zarki. Variable bit rate video transmission. IEEE Commun. Mag., 32(5):54 66, May 1994. 22. O. Rose. Statistical properties of MPEG video traf c and their impact on traf c modeling in ATM systems. University of Wuerzburg, Institute of Computer Science Research Report Series, Report No. 101, February 1995. 23. D. C. Verma, H. Zhang, and D. Ferrari. Delay jitter control for real-time communication in a packet switching network. Technical Report 90 007, International Computer Science Institute, University of California, Berkeley, January 1991. 24. T. Yang and J. Pan. Measurement-based loss scheduling scheme. In Proc. IEEE INFOCOM'96, pp. 1062 1071, March 1996. 25. L. Zhang. A new architecture for packet switching network protocols. Ph.D. Thesis, MIT, Department of Electrical Engineering and Computer Science, August 1989. 26. H. Zhang. Service disciplines for guaranteed performance service in packet-switching networks. Proc. of IEEE, 83(10):October 1995. 27. H. Zhang and E. W. Knightly. Providing end-to-end statistical performance guarantees with bounding interval dependent stochastic models. In Proc. ACM SIGMETRICS'94, pp. 211 220, May 1994.

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Self-Similar Network Traf c and Performance Evaluation, Edited by Kihong Park and Walter Willinger Copyright # 2000 by John Wiley & Sons, Inc. Print ISBN 0-471-31974-0 Electronic ISBN 0-471-20644-X

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

Since the statistical analysis of Ethernet local-area network (LAN) traces in Leland et al. [20], there has been signi cant progress in developing appropriate mathematical and statistical techniques that provide a physical-based, networking-related understanding of the observed fractal-like or self-similar scaling behavior of measured data traf c over time scales ranging from hundreds of milliseconds to seconds and beyond. These techniques explain, describe, and validate the reported large-time scaling phenomenon in aggregate network traf c at the packet level in terms of more elementary properties of the traf c patterns generated by the individual users and=or applications. They have impacted our understanding of actual network traf c, to the point where we now know why aggregate data traf c exhibits fractal scaling behavior over time scales from a few hundreds of milliseconds onward. In fact, a measure of the success of this new understanding is that the corresponding mathematical arguments are at the same time rigorous and simple, are in full agreement with the networking researchers' intuition and with measured

Replication is the copying of data from one system and its disks to another system and its completely independent and redundant set of disks. Replication is not the same as disk mirroring, because mirroring treats both sets of disks as a single, logical volume with enhanced availability, while replication treats the disk sets as two completely independent items. Mirroring is confined to a single computer system, while replication moves data from one system to another. When replication is done properly, the same ACID properties present in database systems will be in the replicated databases. (See the Database Servers section in 14, Data and Web Services for a discussion of ACID properties.) The end result is two consistent and equally viable data sets ideally in distinct physical locations. Since it further increases the data s availability, replication further increases your disk space requirements above RAID-1 or RAID-5, because each replicated disk set is usually a separate volume unto itself, with its own RAID implementation. Depending on the implementation, you could choose to replicate from a RAID 0+1 set to a RAID-5 set, or to a non-RAIDed set at your DR site. What you gain in return for the investment in disk spindles is the ability to recover from a large variety of performance and operational outages quickly, and with predetermined downtime.

Self-Similar Network Traf c and Performance Evaluation, Edited by Kihong Park and Walter Willinger ISBN 0-471-31974-0 Copyright # 2000 by John Wiley & Sons, Inc.

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