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In short, the simulation lacks the randomness in workflows that actual usage of this dual processor configuration would encounter over the long-term. As a result, the performance of these simulations must be taken in that context, mindful of the limitations they have.
Potential Uses of this Simulation
This simulation would be very effective in defining how best to manage multiprocessor workloads in a complex server environment, including the planning of a data center to run Cloud-based applications. It is feasible Amazon Web Services has a comparable simulator running today to ensure their Cloud platform stays at its optimal performance levels. In addition, there is the ability to create a multicomputer network message processor design based on comparable simulations (Unger,...
For either of these uses to be effective, they must replicate the full, random workload of networks to ensure the user has a stable, reliable experience when using systems based on these architectures. The ability to align all of these elements together and deliver a reliable system is key, and simulations can help in this regard.
References
Serrazi, G. (2007) Shared-Memory Multiprocessor Systems -- Hierarchical Task Queue. University of Lugano, Advanced Learning and Research Institute. Retrieved March 7, 2012 from http://www.idsi.md/files/file/publicatii/PERFORMANCE_EVALUATION_Exercises_Zamsa.pdf
Unger, B.W., & Bidulock, D.S. (1982). The design and simulation of a multi-computer network message processor. Computer Networks, 6(4), 263-263.
This is why cloud computing is still an imprecise science at best, with significant lags in performance and inconsistent performance on large-scale performance requirements (Luo, 2010). VMWare is concentrating on these aberrations in performance to create optimized product and services mix for each of their software and hardware products, looking to ensure a high level of computer capacity utilization over time. Amazon's lessons learned in managing one of the
Progress and Performance Monitoring With any project that's intricate, involved and worth completing, the progress and performance need to be consistently monitored. Proper project monitoring allows all stakeholders in the project to determine if the project is on course or not. One method of monitoring the success and development of a project is via performance indicators. These indicators are flags which provide proper image of a project's impact, outcomes, outputs, and
Capacity planning has seen an increased emphasis due to the financial benefits of the efficient use of capacity plans within material requirements. This is particularly true as international competitors are using more efficient and productive means of managing their own capacity. Toyota is prime example of how short-term capacity management can be used to help improve profitability, shareholder return and costs. Insufficient capacity can quickly lead to deteriorating delivery performance,
Measures should be developed at every level of the organisation as this will help in the measurement of performance at those levels. Again all services and teams will have action plans that they will have to meet which will make sure that the organisation reaches its goal. There has also got to be indicators for individuals as this will determine their performance for their teams and the organisation. (Measures
Monitoring System of Starbucks Monitoring and Evaluation Systems Monitoring consists of everyday assessment of activities and projects, while evaluation entails the routine assessment of attained undertakings. Monitoring oversees the amount of work done while evaluation oversees the impact of the work done yet. There are number of audiences to be tapped upon for information regarding monitoring and evaluating post disaster projects such as: Agencies Funders Government Public Afflicted community In case of post disaster projects, monitoring and evaluation
Capacity Management/IT Performance Within organizations, regardless of their size and sophistication, not all networks are identical. Because of this as the data needed is broken into its component parts (known as packets or segments), there are a number of factors that affect their delivery and robust nature. Because of this degradation, which is simply a result of natural functions of data management, organizations continually need to monitor and improve the performance