International Conference on Computational Intelligence: Modeling Techniques and Applications (CIMTA) 2013 A Genetic Algorithm (GA) based Load Balancing Strategy for Cloud Computing

By K. Dasgupta, B. Mandal, Paramartha Dutta, J. K. Mondal, Santanu Dam. 2013

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Task scheduling techniques in cloud computing: A literature survey (2019, unknown): “Makespan [1] [14–16,23,29,26] [35,38,39,56,47,49] [62] Profit [43,55,33] Completion time [1,5–7] [9,10,13,15,5,17,20–22,25,29] [33,45,50,54,56,53,48,40,51,52] [65] Cost [3,5] [8,17,20,22,23,27] [46,36,51,52] [61,62] Waiting time [4] [12,18] [64] Other [2,31] [19,27,30] [32,41,57,11,60] [59,63]”
A review of metaheuristic scheduling techniques in cloud computing (2015, methodology): “Dasgupta et al. [28] focused on load balancing of resources while scheduling tasks in cloud using genetic algorithm.”
Load balancing in cloud computing: A big picture (2018, background): “[46] have proposed a GA-based load balancing approach that minimizes the makespan.”