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Interoperability of Manufacturing Control and Web Based Facility Management Systems: Trends, Technologies, & Case Studies
Published in Barney L. Capehart, Timothy Middelkoop, Paul J. Allen, David C. Green, Handbook of Web Based Energy Information and Control Systems, 2020
Cloud computing is the most current trend that has arrived in the manufacturing automation business and is available to any facilities automation application today. Cloud computing is based on the idea that computing resources are becoming like electric and water utilities. The concept depends on universal access to the internet, as reasonable speeds. The idea is that rather than running applications on your own computer hardware, and having to maintain, secure, support, and manage the hardware yourself, you run your applications on a remote system, only paying for resources as needed and elastically being able to get more resources on demand in exchange for more money. Private Cloud Computing uses Virtual Private Servers (VPS) which are simply fully dedicated instances of virtual servers running on someone else’s hardware, that you access over the internet or “in the cloud,” providing all the same benefits of a dedicate computer without the headaches.
Elasticity management for capacity planning in software as a service cloud computing
Published in IISE Transactions, 2021
Jon M. Stauffer, Aly Megahed, Chelliah Sriskandarajah
Cloud computing research on resource utilization focuses on the reassignment of queries to better balance capacity requirements across instances (Van et al., 2009; Meng et al., 2010; Wang et al., 2016) or how to reduce the energy consumption of instances within a data center (Gandhi et al., 2010; Lefèvre and Orgerie, 2010; Al-Daoud et al., 2012; Kramer et al., 2012; Aydin et al., 2020). For example, Shen and Wang, (2014) used a stochastic optimization model with backlogging and extensive computational results to show that large environmental savings can be achieved by selectively switching servers (and the corresponding instances) on and off. Gullhav and Nygreen, (2016) and Gullhav et al., (2017) investigated the SaaS instance deployment question when considering instances deployed on a cloud provider’s private servers or leasing servers from a public IaaS provider with the potential for server failures. Recently, Arbabian et al. (2020) optimized the timing of pre-configured server package purchases over the long-term (not daily/hourly capacity requirements) to meet increasing demand. Unlike our research, which places incoming queries on available instances in three capacity dimensions, most of these cloud computing research papers focus on instances simply being occupied and do not consider the reality of multiple capacity dimensions.