1. Attached files: 500_100_fmincon_0.95_1.mat Experiment with 500 users, 100ms max response time, 95% availability, exact algorithm. 500_100_heuristic_0.95_1.mat Experiment with 500 users, 100ms max response time, 95% availability, our algorithm. 2000_70_fmincon_0.95_1.mat Experiment with 2000 users, 70ms max response time, 95% availability, exact algorithm. 2000_70_heuristic_0.95_1.mat Experiment with 2000 users, 70ms max response time, 95% availability, our algorithm. 2000_100_fmincon_0.9_1.mat Experiment with 2000 users, 100ms max response time, 90% availability, exact algorithm. 2000_100_heuristic_0.9_1.mat Experiment with 2000 users, 100ms max response time, 90% availability, our algorithm. 2000_100_fmincon_0.95_1.mat Experiment with 2000 users, 100ms max response time, 95% availability, exact algorithm. 2000_100_heuristic_0.95_1.mat Experiment with 2000 users, 100ms max response time, 95% availability, our algorithm. 2000_100_fmincon_0.999_1.mat Experiment with 2000 users, 100ms max response time, 99.9% availability, exact algorithm. 2000_100_heuristic_0.999_1.mat Experiment with 2000 users, 100ms max response time, 99.9% availability, our algorithm. 2000_300_fmincon_0.95_1.mat Experiment with 2000 users, 300ms max response time, 95% availability, exact algorithm. 2000_300_heuristic_0.95_1.mat Experiment with 2000 users, 300ms max response time, 95% availability, our algorithm. 10000_100_fmincon_0.95_1.mat Experiment with 10000 users, 100ms max response time, 95% availability, exact algorithm. 10000_100_heuristic_0.95_1.mat Experiment with 10000 users, 100ms max response time, 95% availability, our algorithm. 2. Data format: MATLAB data format, can be load 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.