Forecasting Price of Amazon Spot Instances Using Machine Learning

Forecasting Price of Amazon Spot Instances Using Machine Learning

Manas Malik, Nirbhay Bagmar
DOI: 10.4018/IJAIML.20210701.oa5
Article PDF Download
Open access articles are freely available for download

Abstract

An auction-based cloud model is followed in the spot pricing mechanism, where the spot instances charge changes with time. The user is bound to pay for the time that is initially initiated. If the user terminates before the sessional hourly completion, then the customer will be billed on the entire hourly session. In case Amazon terminates the instance then the customer would not be billed for the partial hour. When the current spot price reduces to bid price without any notification the cloud provider terminates the spot instance, it is a big disadvantage to the time of the availability factor, which is highly important. Therefore, it is crucial for the bidder to forecast before engaging the bids for spot prices. This paper represents a technique to analyze and predict the spot prices for instances using machine learning. It also discusses implementation, explored factors in detail, and outcomes on numerous instances of Amazon Elastic Compute Cloud (EC2). This technique reduces efforts and errors for forecasting prices.
Article Preview
Top

1. Introduction

Computation of cloud offers shared resources reachable over the Internet connectivity. Software and Hardware are both comprised of cloud computing resources. The different models of cloud services are- Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Network as a Service (NaaS). The cloud platform has various deployment models, they are-public cloud, private cloud, community cloud and hybrid cloud. Resources are enabled by the cloud on the basis of pay as you go model. The major provider for the computation of cloud-related resources is Amazon.

Amazon offers three instances: Spot Instances, On-demand Instances and Reserved Instances, around 16 regions across the globe.

Spot Instances has dynamic pricing, which makes it exclusive and distinguishable. Dynamic variation of the process of spot instances is built on request and delivery of cloud-related services in the data centers. Using an online auction platform, clients request a bid to attain spot instances. The auction platform offers an analysis to determine the market clearance price or spot price if the consumer bids above the aforesaid price, spot instance is obtained. Cloud providers deliver up-to-date and recent spot price data to aid clients in the bidding process. It provides customers with access to the web-based API for bidding spot instances. There are certain parameters to spot instance bid request, they are as follows:

  • 1.

    Number of Instances

  • 2.

    Availability Zone

  • 3.

    Instance Type

  • 4.

    Bidding Amount based on price/instance/per hour

  • 5.

    Graphics Processing Unit (GPU) mode machines

Top

2. Technique For Pricing Spot Instance

Due to the fluctuations in prices and sudden termination possibility of instances, Amazon EC2 spot instance pricing becomes very complicated. Termination may be triggered by either the customer or the cloud organization.

The phases in the spot price billing system followed are:

  • 1.

    User bids for one spot instance (in a specified availability zone) for a particular machine type.

  • 2.

    Only when the bid price is greater than the current price, a spot instance is obtained.

  • 3.

    A spot price is set as the cost of getting an instance on setup.

  • 4.

    Pricing algorithm for spot instances works on an hourly basis in spite of the continuous variations, both user and cloud provider can interrupt computation.

  • 5.

    The user is supposed to pay the entire hour for the estimate, even if the user interrupts the instance without the completion of the hour.

  • 6.

    User doesn’t have to pay if the interruption is performed by the cloud provider. The user’s partial utilization will not be charged.

  • 7.

    After an hour has been finished, the user has to pay for the computation and at the start of the new hour, a new price is set.

  • 8.

    Bid prices remain the same once the instances are created.

Two important conclusions can be drawn from the above steps. Firstly, in case the cloud provider performs the termination of instance, the user gets free of cost of computational services. Furthermore, Cloud service termination of each instance results in a later start of a new instance. New instance boot time isn't included in the simulation's successful execution time.

Complete Article List

Search this Journal:
Reset
Volume 13: 1 Issue (2024)
Volume 12: 2 Issues (2022)
Volume 11: 2 Issues (2021)
Volume 10: 2 Issues (2020)
Volume 9: 2 Issues (2019)
View Complete Journal Contents Listing