Pre-Design Stage Cost Estimation for Cloud Services

被引：0

作者：

Aoshima T. ^{[1
]}

Yoshida K. ^{[2
]}

机构：

[1] Department of Risk Engineering, University of Tsukuba, 1-1-1, Tennodai, Ibaraki, Tsukuba

[2] Graduate School of Business Sciences, University of Tsukuba, 3-29-1, Otsuka, Bunkyo-ku, Tokyo

来源：

IEEJ Transactions on Electronics, Information and Systems | 2022年 / 142卷 / 06期

基金：

日本学术振兴会;

关键词：

application topology; cloud computing; cost estimation;

D O I：

10.1541/ieejeiss.142.679

中图分类号：

学科分类号：

摘要：

Cloud computing is being increasingly employed in the development of systems. For such systems, rapid cost estimation is required to start new business. This paper proposes a “Pay-Per-Use” billing model, and providers offer various strategic pricing options. There are many cost structures, and hence, users need to consider many pricing options when estimating system costs. Although companies often want to estimate the cost of their systems, it is difficult to obtain a comprehensive estimate that considers all components. Previously, researchers have implemented simulation-based and analytical approaches to solve this problem. In this study, we develop a cost-estimation method that employs directed acyclic graph (DAG)-based representation and matrix operations. Our method emphasizes simplicity through the use of a systematic procedure that can estimate the costs of new services in the pre-design stage. ©2022 The Institute of Electrical Engineers of Japan.

引用

页码：679 / 688

页数：9

共 18 条

[1]

Armbrust M., Fox A., Griffith R., Joseph A.D., Katz R., Konwinski A., Lee G., Patterson D., Rabkin A., Stoica I., Zaharia M., A View of Cloud Computing, Commun. ACM, 53, 4, pp. 50-58, (2010)

[2]

Mell P.M., Grance T., SP 800-145. The NIST Definition of Cloud Computing, (2011)

[3]

Li X., Li Y., Liu T., Qiu J., Wang F., The Method and Tool of Cost Analysis for Cloud Computing, 2009 IEEE International Conference on Cloud Computing, pp. 93-100, (2009)

[4]

Martens B., Walterbusch M., Teuteberg F., Costing of Cloud Computing Services: A Total Cost of Ownership Approach, 2012 45th Hawaii International Conference on System Sciences, pp. 1563-1572, (2012)

[5]

Simonet A., Lebre A., Orgerie A.-C., Deploying Distributed Cloud Infrastructures: Who and at What Cost?, 2016 IEEE International Conference on Cloud Engineering Workshop (IC2EW), pp. 178-183, (2016)

[6]

Calheiros R.N., Ranjan R., Beloglazov A., De Rose C.A.F., Buyya R., CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms, Software: Practice and Experience, 41, 1, pp. 23-50, (2011)

[7]

Zhao W., Peng Y., Xie F., Dai Z., Modeling and simulation of cloud computing: A review, 2012 IEEE Asia Pacific cloud computing congress (APCloudCC), pp. 20-24, (2012)

[8]

Vondra T., Sedivy J., Cloud autoscaling simulation based on queueing network model, Simulation Modelling Practice and Theory, 70, pp. 83-100, (2017)

[9]

Sotiriadis S., Bessis N., Antonopoulos N., Towards Inter-cloud Simulation Performance Analysis: Exploring Service-Oriented Benchmarks of Clouds in SimIC, 2013 27th International Conference on Advanced Information Networking and Applications Workshops, pp. 765-771, (2013)

[10]

Fittkau F., Frey S., Hasselbring W., CDOSim: Simulating cloud deployment options for software migration support, 2012 IEEE 6th International Workshop on the Maintenance and Evolution of Service-Oriented and Cloud-Based Systems (MESOCA), pp. 37-46, (2012)

← 1 2 →