Open AccessSPOT PRICE PREDICTION FOR CLOUD COMPUTINGUSING NEURAL NETWORKS
Author(s) -
Volodymyr Turchenko,
Vladyslav Shults,
Iryna Turchenko,
Richard M. Wallace,
Mehdi Sheikhalishahi,
José Luis Vázquez-Poletti,
Lucio Grandinetti
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.12.4.615
Subject(s) - bidding , cloud computing , computer science , spot contract , commodity , spot market , scheduling (production processes) , virtualization , microeconomics , business , operating system , finance , economics , electricity , operations management , electrical engineering , engineering , futures contract
Advances in service-oriented architectures, virtualization, high-speed networks, and cloud computing has resulted in attractive pay-as-you-go services. Job scheduling on such systems results in commodity bidding for computing time. Amazon institutionalizes this bidding for its Elastic Cloud Computing (EC2) environment. Similar 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 the predictive models for future short-term and middle-term spot price prediction based on neural networks giving users a high confidence on future prices aiding bidding on commodity computing.