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doi: 10.5281/zenodo.49068
handle: 10044/1/78096
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.
cloud provisioning, spot cloud, random environment, fluid-approximated queueing networks, bidding strategy, 650, application deployment
cloud provisioning, spot cloud, random environment, fluid-approximated queueing networks, bidding strategy, 650, application deployment
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