Pregled bibliografske jedinice broj: 911506
Distributing the computation in combinatorial optimization experiments over the cloud
Distributing the computation in combinatorial optimization experiments over the cloud // Advances in Science, Technology and Engineering Systems Journal (ASTESJ), 2 (2017), 6; 136-144 doi:10.25046/aj020617 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 911506 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Distributing the computation in combinatorial optimization experiments over the cloud
Autori
Brčić, Mario ; Hlupić, Nikica ; Katanić, Nenad
Izvornik
Advances in Science, Technology and Engineering Systems Journal (ASTESJ) (2415-6698) 2
(2017), 6;
136-144
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Combinatorial optimization ; Computational experiments ; Cloud computing
Sažetak
Combinatorial optimization is an area of great importance since many of the real-world problems have discrete parameters which are part of the objective function to be optimized. Development of combinatorial optimization algorithms is guided by the empirical study of the candidate ideas and their performance over a wide range of settings or scenarios to infer general conclusions. Number of scenarios can be overwhelming, especially when modeling uncertainty in some of the problem’s parameters. Since the process is also iterative and many ideas and hypotheses may be tested, execution time of each experiment has an important role in the efficiency and successfulness. Structure of such experiments allows for significant execution time improvement by distributing the computation. We focus on the cloud computing as a cost- efficient solution in these circumstances. In this paper we present a system for validating and comparing stochastic combinatorial optimization algorithms. The system also deals with selection of the optimal settings for computational nodes and number of nodes in terms of performance-cost tradeoff. We present applications of the system on a new class of project scheduling problem. We show that we can optimize the selection over cloud service providers as one of the settings and, according to the model, it resulted in a substantial cost-savings while meeting the deadline.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb