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The lock is removed when T1 commits, at which time T1 reveals the new salary for employee 100 in all copies of the EMP table. It should be obvious that enforcing synchronous replication control has major performance drawbacks. Another major issue is dealing with site failures. If one of the sites storing a replica of a data item modi ed by T1 goes down during the execution of T1, T1 is blocked until the failed site is repaired. We will discuss the impact of site failure on transaction execution in 8. For these reasons, synchronous replication is only used when one computer is a backup of the other. In this scenario, two computers act as a hot standby for each other. Suppose we have two servers, A as the primary and B as the backup, that need to be identical at all times. In this setup, when A fails, transaction processing continues on B without interruption. Meanwhile, transactions that run on B are kept in a pending queue for application to A when it is repaired. When the A server restarts, it is not put back in service until it is synchronized with the B server. During synchronization, new transactions that arrive at either site are held in the job queue and are not run. Synchronizing A means that the pending transactions from B are applied to A in the same order that they ran on B. After all of the transactions in the pending queue have been processed against A, both servers are put back in service. At this time, transactions are processed from the front of the job queue and run against both copies.

In some cases, Control objects may contain other Control objects. For example, the first control on the Drawing toolbar contains other controls (this also demonstrates that you can include menu items on a toolbar). The concept of Controls within Controls will become clearer in 23, when I discuss menus.

(h) follows from the fact that Yk(S ) depends only on the current input (S) (S c symbols Xk and Xk ) (i) follows after we introduce a new timesharing random variable Q distributed uniformly on {1, 2, . . . , n} (j) follows from the de nition of mutual information (k) follows from the fact that conditioning reduces entropy (S c (S) (l) follows from the fact that YQ ) depends only on the inputs XQ and

replaced by new frequencies, good frequencies remain unchanged in the hop sequence, and non-AFH slaves remain synchronized while other slaves in the piconet are using the adapted hopping sequence [16]. In order to keep all devices in the piconet updated with the new hopping pattern, advertisement of the new hopping sequence is typically done by using LMP messages exchanged between the master and slaves in the piconet. How often a new hopping pattern should be advertised could be dynamically adjusted so that it tracks changes in the channel. Performance evaluation results of AFH are provided in [15] for le transfer protocol (FTP) and voice applications. Maximizing the throughput is the goal for FTP application and minimizing the delay is the goal for voice application. AFH improves the throughput by 25% for FTP application. The improvement is more obvious than that for voice application. When Bluetooth and WLAN coexist, the PER for WLAN drops if AFH is adopted. AFH allows additional scheduling techniques to be used simultaneously if there is a need to control the transmission of packets on the medium. AFH has been demonstrated as effective in dealing with static interference that comes from WLAN, but it is not applicable for multiple colocated Bluetooth piconets because in Bluetooth frequency channels are constantly changing, the hop pattern of one piconet is not known to another one, and multiple piconets are not necessarily synchronized in a typical noncollaborative scenario. Besides, the performance of AFH is also dependent on the update rate of the frequency classi cation to track the channel dynamics [15]. 7.4.2 Bluetooth Interference-Aware Scheduling

The single-point crossover operator that we have outlined here suffers from what is known as positional bias. That is, the performance of the genetic algorithm depends, in part, on the order in which the variables occur in the chromosome. So genes in loci 1 and 2 will often be crossed over together, simply because of their proximity to each other, whereas genes in loci 1 and 7 will rarely cross over together. Now, if this positioning re ects natural relationships within the data and among the variables, this is not such a concern, but such a priori knowledge is relatively rare. The solution is to perform multipoint crossover, as follows. First, randomly select a set of crossover points, and split the parent chromosomes at those points. Then, to form the children, recombine the segments by alternating between the parents, as illustrated in Figure 6.3.

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