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16      CHAPTER 1 BIO-INSPIRED ALGORITHMS FOR BIG DATA ANALYTICS






             REFERENCES
              [1] S. Khan, X. Liu, K.A. Shakil, M. Alam, A survey on scholarly data: from big data perspective, Inf. Process.
                 Manag. 53 (4) (2017) 923–944.
              [2] A. Gandomi, M. Haider, Beyond the hype: big data concepts, methods, and analytics, Int. J. Inf. Manag. 35 (2)
                 (2015) 137–144.
              [3] S. Singh, I. Chana, A survey on resource scheduling in cloud computing: issues and challenges, J. Grid Com-
                 put. 14 (2) (2016) 217–264.
              [4] S.S. Gill, R. Buyya, A taxonomy and future directions for sustainable cloud computing: 360 degree view,
                 ACM Comput. Surv. 51 (6) (2019) 1–37.
              [5] C.P. Chen, C.Y. Zhang, Data-intensive applications, challenges, techniques and technologies: a survey on big
                 data, Inf. Sci. 275 (2014) 314–347.
              [6] J. Wang, Y. Wu, N. Yen, S. Guo, Z. Cheng, Big data analytics for emergency communication networks: a
                 survey, IEEE Commun. Surv. Tutorials 18 (3) (2016) 1758–1778.
              [7] S.S. Gill, I. Chana, M. Singh, R. Buyya, RADAR: self-configuring and self-healing in resource management
                 for enhancing quality of cloud services, in: Concurrency and Computation: Practice and Experience (CCPE),
                 vol. 31, No. 1, Wiley Press, New York, 2019, pp. 1–29, ISSN: 1532-0626.
              [8] I. Singh, K.V. Singh, S. Singh, Big data analytics based recommender system for value added services (VAS),
                 in: Proceedings of Sixth International Conference on Soft Computing for Problem Solving, Springer,
                 Singapore, 2017, pp. 142–150.
              [9] S.S. Ilango, S. Vimal, M. Kaliappan, P. Subbulakshmi, Optimization using artificial bee colony based clus-
                 tering approach for big data, Clust. Comput. (2018) 1–9, https://doi.org/10.1007/s10586-017-1571-3.
             [10] R. Kune, P.K. Konugurthi, A. Agarwal, R.R. Chillarige, R. Buyya, Genetic algorithm based data-aware group
                 scheduling for big data clouds, in: Big Data Computing (BDC), 2014 IEEE/ACM International Symposium,
                 IEEE, 2014, pp. 96–104.
             [11] A.H. Gandomi, S. Sajedi, B. Kiani, Q. Huang, Genetic programming for experimental big data mining: a case
                 study on concrete creep formulation, Autom. Constr. 70 (2016) 89–97.
             [12] S. Elsayed, R. Sarker, Differential evolution framework for big data optimization, Memetic Comput. 8 (1)
                 (2016) 17–33.
             [13] A.H. Kashan, M. Keshmiry, J.H. Dahooie, A. Abbasi-Pooya, A simple yet effective grouping evolutionary
                 strategy (GES) algorithm for scheduling parallel machines, Neural Comput. & Applic. 30 (6) (2018)
                 1925–1938.
             [14] M.M. Mafarja, S. Mirjalili, Hybrid whale optimization algorithm with simulated annealing for feature selec-
                 tion, Neurocomputing 260 (2017) 302–312.
             [15] A. Barbu, Y. She, L. Ding, G. Gramajo, Feature selection with annealing for computer vision and big data
                 learning, IEEE Trans. Pattern Anal. Mach. Intell. 39 (2) (2017) 272–286.
             [16] A. Tayal, S.P. Singh, Integrating big data analytic and hybrid firefly-chaotic simulated annealing approach
                 for facility layout problem, Ann. Oper. Res. 270 (1–2) (2018) 489–514.
             [17] I.B. Saida, K. Nadjet, B. Omar, A new algorithm for data clustering based on cuckoo search optimization,
                 in: Genetic and Evolutionary Computing, Springer, Cham, 2014, pp. 55–64.
             [18] E.D. Raj, L.D. Babu, A firefly swarm approach for establishing new connections in social networks based on
                 big data analytics, Int. J. Commun. Netw. Distrib. Syst. 15 (2-3) (2015) 130–148.
             [19] H. Wang, W. Wang, L. Cui, H. Sun, J. Zhao, Y. Wang, Y. Xue, A hybrid multi-objective firefly algorithm for
                 big data optimization, Appl. Soft Comput. 69 (2018) 806–815.
             [20] L. Wang, H. Geng, P. Liu, K. Lu, J. Kolodziej, R. Ranjan, A.Y. Zomaya, Particle swarm optimization based
                 dictionary learning for remote sensing big data, Knowl.-Based Syst. 79 (2015) 43–50.
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