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One October afternoon I received a brown-paper package tied up with string, return address somewhere in the Ukraine. At the height of the anthrax mail scares here in New Jersey, I was tempted to microwave the package for several minutes. Despite all of the jokes about My Favorite Things, the contents, in fact, were something I wanted a Russian hockey jersey to add to my growing collection. I found the perfect item on eBay, won the auction, and paid for it using Billpoint, eBay s credit card payment service. The seller received funds in whatever currency she wanted; I was fairly certain I was going to get the jersey because her feedback rating was quite high and she had a perfect record of delivering as promised on jersey auctions. eBay s intermediation allowed me to complete a transaction on the Internet that I never would have done in the real world out of fear of having my credit card number stolen. Hal



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with L x a slowly varying function at in nity, that is, lim L tx 1; L x Vt > 0:

While intermediation reigns in the business-to-consumer Internet space, it hasn t found applications yet in the operations world. However, the same model may prove valuable for creating networks of web services or other finegrain service points, where an intermediation facility brings producers and consumers of services together in a trusted environment where SLAs are consistently described and enforced. Increased intermediation means you need to have models and metrics for trusting other providers of software or network services. It also means that your reliability is a function of your own systems and those that you re relying on from third parties.





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L could, for instance, be a constant or a logarithmic function If Eq (62) holds, then we write P G > P n Regular variation is an important asymptotic concept in probabilistic analysis The main reference text is the book by Bingham et al [5] An early result concerning regular variation in queueing theory is due to Cohen [13] He proved the following result for the GI =G=1 queue under the rst-come- rstserved (FCFS) discipline: the tail of the waiting time distribution is regularly varying of index 1 n if and only if the tail of the service time distribution is regularly varying of index n; n > 1.

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Fault-tolerant hardware systems use multiple implementations of components, running in parallel, to provide redundancy if any individual slice of the system fails. We have discussed how to provide redundancy for easily partitioned, scalable applications like web servers, where multiple instances of the application can be run, with state sharing, across multiple operating system instances. But what if you re dealing with a stateful application that occasionally gets the wrong answer How can you improve the quality of software with respect to logical faults as well as external failures One concept that s not

This result has turned out to be very useful in relating the regularly varying tail behavior of on periods of on=off sources in uid queues to the buffer content [7, 8]; see also Jelenkovic and Lazar [23] and Rolski et al [32] Cohen's result implies that, in the case of regular variation, the tail of the waiting time distribution is one degree heavier than that of the service time distribution For 1 < n < 2, the mean of the service time distribution is nite, but the mean of the waiting time distribution is in nite The rst issue that we consider in this chapter is whether other service disciplines besides FCFS may lead to a less detrimental waiting time behavior We consider the M =G=1 queue with the processor sharing (PS) discipline and the M=G=1 queue with the last-come- rst-served preemptive resume (LCFS-PR) discipline.

new is Byzantine reliability,2 in which multiple implementations of a chunk of code are run in parallel and vote on correct outputs. Historically, Byzantine reliability models haven t held up because each implementation of the object was subject to most of the same failures that is, there was too much correlation between the typical coding faults you d find in multiple attempts to create independent software. Being able to craft applications in smaller pieces whether it s through web services or other Java objects will probably make Byzantine reliability more attractive.

Note that PS and LCFS-PR are well-known and important disciplines, that both play a key role in product-form networks For both disciplines, the waiting time tail behavior turns out to be regularly varying of index n iff the service time tail behavior is regularly varying of index n We refer to Anantharam [2] for a related investigation of the in uence of the service discipline on the tail behavior of a single server queue..

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