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Accomplished software development professional with experience in all disciplines of mainframe and PC platforms. Proven track record of delivering quality results on schedule. Exceptional analysis and programming skills and extensive experience with Microsoft SQL Server, performance measurement and capacity planning. Effectively delivers technical training.

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INTERPRETATION We can see that P is in the direction of propagation with the help of Figure 1.23 by using the right-hand rule to nd E H. We may use Maxwell s equations from Table 1.2 to nd the magnitude of P .

GridMon [86] is a network performance monitoring toolkit to identify faults and inef ciencies. The toolkit is composed of a set of tools that are able to provide measures concerning different aspects related to network performance: connectivity, inter-packet jitter, packet loss, Round Trip Time (RTP) and TCP and UDP throughput. The main components of GridMon are shown in Figure 5.17. PingER is a collection of Perl scripts, which use the ICMP ping utility to send 10 ping requests to remote hosts. The results are recorded for later analysis. IperfER is based on NCSA s Iperf [87] utility, used for measuring the network s view of TCP or UDP throughput between two hosts. Iperf consists of client and server executables, which sit at either end of a TCP/UDP connection, streaming data

Peak usage is normally measured in terms of active users For example, if 500 users normally log on to the purchasing system over the lunch hour and 2,000 users normally log on around 7PM in the evening, then the peak expected workload for all log on/log off is 2,000 users Notice also that the peak expected workload is 2,000 users whether the user base is 2,000 users or 2,000,000 users When researching the peak workload of users for a particular group of transactions, specify that you are interested in numbers of active users at peak workload time rather than the number of concurrent users Concurrent user workloads are of interest for speci c tests such as database record lock contention, deadly embraces, or network packet collisions The actual occurrence of truly concurrent activity is rare.

Another popular search technique is simulated annealing. The name and inspiration come from annealing in metallurgy. By heating and controlled cooling of a material, the size of its crystals is increased and their defects are reduced [5]. The crucial point is the cooling time: If the annealing process is very fast, the atoms do not have enough time to find the correct position the system freezes in a suboptimal local minimum. If the process is done sufficiently slowly, the atoms have time to find a state of minimum energy. During a search process, the annealing paradigm is used to probabilistically control whether or not a step with decreasing objective function value f (x) is taken. The chance of accepting a worse solution is controlled by a cooling temperature parameter T , which is decreased during the course of the algorithm. An improvement step is always admitted. A deteriorating step is only considered with a certain probability that decreases with the temperature . Deteriorating steps are thus always possible, but their chances become ever smaller. For a detailed treatment of Simulated Annealing, see [6]. A simple program structure of a Simulated Annealing optimisation algorithm is shown in Figure 14.2. The variable Z is a uniformly distributed random value between zero and one, the chance for admitting

the continued turmoil threatens oil exports, and with the United States being the world s most oil-dependent nation, the economic consequences may be significant.

Both these displays are of interest only to the administrator of the web server and hackers seeking to disrupt the service. (You use access controls to limit their use to the administrator!)