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Many enterprise-level computer software programs will use thick and thin clients to connect users to the server. Thick clients are generally more expensive and run on a server. In contrast, thin clients are less expensive, run locally on the user’s machine without being connected to a central server, and rely heavily on communication with other devices. For many people new to computer technology, these terms may be completely unfamiliar terms that they do not know much about; their ignorance is not an instance where it would be fair for them to become too stringent in what they believe is wrong or right for them (Bossche et al., 2011).
Pros and cons include the possibility that a central server might be close to a disaster but could also handle increased users. This would be true for the user’s browser, but this may not mean much for Windows when the purpose of the server is to run an application since a single application can only use one process at a time (while in Unix and most BSD systems it can use any number of processes).
The philosophy behind thick clients and thin clients is completely different. Thick clients are generally more secure, as all data are stored on the server and read from it, while thin clients store their data locally in RAM instead of being transmitted to the server.
Some examples include the Microsoft Windows operating system, Apple’s Mac OS, and Sun’s Java. A thin client is a type of computer system and software architecture consisting of a program running on a client workstation and thin client software running on the server. The term “thin” refers to the fact that the local application relies on the Internet to communicate with other server processes run in a central location (Canon & Jeannot, 2010). In contrast, a traditional client-server architecture uses a client process that sends requests to servers (typically located on other computers) for processing. In some cases, thin clients may run their operating system or provide their graphical user interface.
Bossche R., Vanmechelen K., & Broeckhove J. (2011). Cost-Efficient Scheduling Heuristics for Deadline Constrained Workloads on Hybrid Clouds. In Proceedings of IEEE 3 rd International Conference on Cloud Computing Technology and Science, Athens, 320-327
Canon L. & Jeannot E. (2010). Evaluation and Optimization of the Robustness of DAG Schedules in Heterogeneous Environments. IEEE Transactions on Parallel and Distributed Systems, 21(4), 532-546

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