Abstract
This paper presents the Forecast-as-a-Service (FaaS) framework, a cloud-based framework that provides on-demand customer-defined forecasting services. Based on the principles of service-oriented architecture (SOA), the FaaS enables the use of different types of data from different sources to generate different kinds of forecasts at different levels of detail for different prices. The FaaS framework has been developed to provide on-demand forecasts of solar or wind power. Forecasts can be long-term forecasts useful for prospecting or planning by potential investors, or short-term forecasts suitable for operational decision making by operators of existing facilities. FaaS provides a more flexible and affordable alternative to the subscription model provided by current forecast service vendors. By improving the flexibility and economics of renewable energy forecasting services with SOA and cloud computing, FaaS achieves the goal of Services Computing.
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References
Makridakis, S., Wheelwright, S., Hyndman, R.: Forecasting Methods and Applications, 3rd edn. John Wiley & Sons (1998)
Montgomery, D., Johnson, L., Gardiner, J.: Forecasting & Time Series Analysis, 2nd edn. McGraw-Hill (1990)
Box, G., Jenkins, G., Reinsel, G.: Time Series Analysis Forecasting and Control, 4th edn. John Wiley & Sons (2008)
Erl, T.: SOA Principles of Service Design. Prentice Hall (2008)
Erl, T.: SOA Design Patterns. Prentice Hall (2009)
Lowy, J.: Programming WCF Services, 3rd edn. O’Reilly (2010)
Chou, D., deVadoss, J., Erl, T., Gandhi, N., Kommapalati, H., Loesgen, B., Shittko, C., Wilhelmsen, H., Williams, M.: SOA with .NET & Windows Azure. Prentice Hall (2010)
Yusuf, L., Olusegun, F., Akinwale, A., Adejumobi, A.: A Framework for Costing Service-Oriented Architecture (SOA) Projects Using Work Breakdown Structure (WBS) Approach. Global Journal of Computer Science and Technology 11(15) (2011)
Li, Z., Keung, J.: Software Cost Estimation Framework for Service-Oriented Architecture Systems using Divide-and-Conquer Approach. In: Proc. Fifth IEEE International Symposium on Service Oriented System Engineering, pp. 47–54 (2010)
Snyder, H., Davenport, E.: Costing and Pricing in the Digital Age. Library Association Publishing (1997)
Kang, B., Tam, K.-S.: A New Characterization and Classification Method for Daily Sky Conditions Based on Ground-Based Solar Irradiance Measurement Data. Solar Energy 94, 102–118 (2013)
Marco, D., Jennings, M.: Universal Meta Data Models. Wiley Publishing Inc. (2004)
Krishnappa, D., Irwin, D., Lyons, E., Zink, M.: CloudCast: Cloud Computing for Short-Term Weather Forecasts. Computing in Science & Engineering, 30–37 (2013)
Wei, Y., Sukumar, K., Vecchiola, C., Karunamoorthy, D., Buyya, R.: Aneka Cloud Application Platform and its Integration with Windows Azure. In: Cloud Computing: Methodology, Systems, and Applications, ch. 27. CRC Press (2011)
Tsai, W., Sun, X., Balasooriya, J.: Service-Oriented Cloud Computing Architecture. In: Seventh International Conference on Information Technology (2010)
Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns Elements of Reusable Object-Oriented Software. Addison-Wesley (1995)
Zhao, J., Tanniru, M., Zhang, L.: Services computing as the foundation of enterprise agility: Overview of recent advances and introduction to the special issue. Inf. Syst. Front. 9, 1–8 (2007)
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Tam, KS., Sehgal, R. (2014). A Cloud Computing Framework for On-Demand Forecasting Services. In: Hsu, R.CH., Wang, S. (eds) Internet of Vehicles – Technologies and Services. IOV 2014. Lecture Notes in Computer Science, vol 8662. Springer, Cham. https://doi.org/10.1007/978-3-319-11167-4_35
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DOI: https://doi.org/10.1007/978-3-319-11167-4_35
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