OptiSpot: Minimizing Application Deployment Cost using Spot Cloud Resources
Description
1. Attached files: This archive contains 1800 MATLAB files, each one containing the results of a single experiment. The name of each file follows the following format: A_B_C_D_E_F_G.mat Where the fields A, B, C, D, E, F, and G are described as follows. A: number of users. Considered values are: 1000, 2000, 5000, 10000. B: maximum response time in milliseconds. Considered values are: 60, 80, 100, 200. C: overbid time cap in hours. Considered values are: 5, 20, 80, 0 (note: 0 is a code used to express infinite hours). D: Amazon region. Considered values are: us-east, eu-west. E: Operating system. Considerede values are: Windows, Linux. F: Optimization algorithm. Considered values are: heuristic (which is OptiSpot), fmincon. G: Experiment seed. Considered values are from 1 to 30 2. Data format: MATLAB data format, can be loaded from MATLAB using the following command: results = load(filename); results is defined as a structure with the following fields: results.cost Type: scalar, positive real number. Desc: hourly cost in US dollars. results.time Type: scalar, positive real number. Desc: total time (in seconds) needed by the algorithm to compute the solution. results.evaluations Type: scalar, positive integer number. Desc: number of constraints evaluations needed by the algorithm to compute the solution. results.d Type: matrix, non negative positive real number. Desc: association matrix between rented resources (columns) and application components (rows). The sum of all the elements of this matrix is equal to the ECUs used by the application.
Resources
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Description |
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0 |
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http://data.europa.eu/88u/dataset/oai-zenodo-org-49068 |
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http://data.europa.eu/88u/dataset/oai-zenodo-org-49068 |
Tags
- spot-cloud
- application-deployment
- fluid-approximated-queueing-networks
- cloud-provisioning
- bidding-strategy
- random-environment