Title :
Applications of neural-based spot market prediction for cloud computing
Author :
Wallace, Robert M. ; Turchenko, Volodymyr ; Sheikhalishahi, Mehdi ; Turchenko, Iryna ; Shults, Vladyslav ; Vazquez-Poletti, Jose Luis ; Grandinetti, Lucio
Author_Institution :
Dept. of Comput. Arch. & Autom., Complutense Univ., Madrid, Spain
Abstract :
Advances in service-oriented architectures (SOA), virtualization, high-speed networks, and cloud computing has resulted in attractive pay-as-you-go services. Job scheduling on these systems results in commodity bidding for computing time. This bidding is institutionalized by Amazon for its Elastic Cloud Computing (EC2) environment and bidding methods exist for other cloud-computing vendors as well as multi-cloud and cluster computing brokers such as SpotCloud. Commodity bidding for computing has resulted in complex spot price models that have ad-hoc strategies to provide demand for excess capacity. In this paper we will discuss vendors who provide spot pricing and bidding and present a predictive model for future spot prices based on neural networking giving users a high confidence on future prices aiding bidding on commodity computing.
Keywords :
cloud computing; neural nets; power engineering computing; power markets; service-oriented architecture; Amazon; SOA; SpotCloud; bidding methods; cluster computing brokers; commodity bidding; commodity computing; elastic cloud computing environment; high-speed networks; job scheduling; multicloud brokers; neural networking; neural-based spot market prediction; pay-as-you-go services; service-oriented architectures; virtualization; Biological system modeling; Cloud computing; Computational modeling; Data models; Electricity; Neural networks; Predictive models; Algorithms; Cloud Computing; Neural-Networking; Resource Management; Scheduling; Spot Market;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013 IEEE 7th International Conference on
Conference_Location :
Berlin
Print_ISBN :
978-1-4799-1426-5
DOI :
10.1109/IDAACS.2013.6663017