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An order 200 pips above the current market price is way too far off to leave out there We do actually want to sell in the near future, but we wanted to see how much enthusiasm was out there for it It s not like someone else was going to trade that far out of the market So really, why did you do it We want to sell We do That is for sure But we want to only sell after it s gone up a bit Hank has a theory that he has tested for many years that if he puts an order out there, way out there, that it will tempt people to bid I don t agree It is so far away that it is really just showing them our cards I like to hold my ideas closer than that How so I was now feeling better.



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To illustrate and compare performances of the rebuild algorithms we consider a system of N S = 5 active servers and one spare server. Each server has 200GB storage, so the system has a total of 1TB storage, including the redundant units. We assume a server transfer capacity of 600Mbps, e.g., using Gigabit Ethernet links. Figure 14.7 plots the data rebuild rate versus server utilization for all the rebuild algorithms. We include the data rebuild rate for reloading data from back-up for the sake of comparison. Note that this data rebuild rate is also the upper bound. We observe that for baseline rebuild, the data rebuild rate is constant at SS /(N S 1) for (1 1/(N S 1)), even if the remaining active servers are lightly loaded and have idle capacities available. As the system utilization approaches one, the rebuild rate drops quickly. Distributed rebuild performs better than baseline rebuild when the server utilization is low (e.g., 0.55), but it deteriorates earlier when the system utilization increases. This is because in distributed rebuild the active servers need to receive data transmissions from other servers in addition to sending data to other servers, and thus consume considerably more transfer capacity than baseline rebuild. Finally, as expected, the mixed distributed baseline rebuild gives the best performance in all cases.





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IRS-III13 (Domingue et al., 2004) is a framework and implemented platform which acts as a broker mediating between the goals of a user or client, and available deployed Web services. The IRS uses WSMO as its basic ontology and follows the WSMO design principles. Below we outline additional principles which have in uenced the IRS (Section 10.5.1). We then give an overview of the IRS-III architecture (in Section 10.5.2) and present the IRS extensions to WSMO (in Section 10.5.3). In the rest of the section we will use the terms IRS and IRS-III interchangeably.

600 Data Rebuild Rate (Mbps)

At least Harvey really did want to make a trade on the Euro I just didn t know where So the idea wasn t so.

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Figure 14.8 shows the time required to completely rebuild a server s worth of data (200GB). Interestingly, for system utilization 0.75 performances of the baseline rebuild algorithm and the mixed distributed baseline algorithm converge. This is because at high system utilization the remaining active servers become the bottleneck, and so it is better to switch to the baseline rebuild algorithm which consumes less transfer capacities of the active servers than distributed rebuild. In this case the mixed distributed baseline algorithm simply allocates all transfer capacity to baseline rebuild. Finally, we plot in Figure 14.9 the rebuild time versus the number of servers in the system under a system utilization of = 0.5. The key observation is that the baseline rebuild algorithm is not scalable the rebuild time increases with the number of servers in the system. This is because in baseline rebuild the maximum rebuild rate is limited by the transfer capacity of the spare server. Thus, as the number of servers increases, so will the number of data/redundant units that need to be sent to the spare server to rebuild an unavailable data unit, thereby resulting in longer rebuild time. By contrast, the rebuild times of distributed rebuild and mixed distributed baseline rebuild do not increase signi cantly with increases in the number of servers and so are much more

IRS-III is based on the following design principles: Supporting Capability Based Invocation: IRS-III enables clients (human users or application programs) to invoke a Web service simply by specifying a concrete desired capability. The IRS acts as a broker nding, composing, and invoking appropriate Web services in order to ful ll the request. Ease of Use: IRS interfaces were designed so that much of the complexity surrounding the creation of SWS-based applications are hidden. For example, the IRS-III browser hides some of the complexity

Rebuild Time (hours)

scalable. For example, under a system utilization of = 0.5, a mixed distributed baseline rebuild can complete the rebuild process in 2.61 hours and 2.87 hours for a 16-server and 64-server system, respectively. Thus, if no new server failure occurs within this period, the system can then resume normal operation and be ready to sustain a new server failure in the future.

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