참고문헌
- Jianbing Ni, Kuan Zhang, Xiaodong Lin, XueminShen, Securing fog computing for internet of things applications: challenges and solutions, IEEE Commun. Surv. Tutor. 20 (1) (2017) 601-628.
- Ke Zhang, SupengLeng, Yejun He, SabitaMaharjan, Yan Zhang, Mobile edge computing and networking for green and low-latency internet of things, IEEE Commun. Mag. 56 (5) (2018) 39-45. https://doi.org/10.1109/MCOM.2018.1700882
- Huang, W.W., Peng, Y.L., Wen, J., Yu, M., 2009. Energy-efficient multi-hop hierarchical routing protocol for wireless sensor networks. In: Proceedings of International Conference on Networks Security, Wireless Communications and Trusted Computing, pp. 469-472.
- A. Boukerche, A. Mostefaoui, M. Melkemi, Efficient and robust serial query processing approach for large-scale wireless sensor network applications, Ad Hoc Netw. 47 (2016) 82-98. https://doi.org/10.1016/j.adhoc.2016.04.012
- Chunsheng Zhu, T. Yang, Lei Shu, ShojiroNishio, Insights of top-k query in duty-cycled wireless sensor networks, IEEE Trans. Ind. Electron. 62 (2) (2015) 1317-1328. https://doi.org/10.1109/TIE.2014.2334653
- Mohan, R., Ananthula, V.R., 2019. Reputation-based secure routing protocol in mobile ad-hoc network using Jaya Cuckoo optimization. Int. J. Modeling, Simul., Sci. Comput. 10 (3).
- RoneIlidio da Silva, Daniel FernandesMacedo, Jose Marcos S. Nogueir, Duty Cycle Aware Spatial Query Processing in Wireless Sensor Networks, Vol. 41, 2015, pp. 240-255.
- MihaelaMiticia, MartijnOnderwater, Maurits de Graafa, Optimal query assignment for wireless sensor networks, Int. J. Electron. Commun. 69 (8) (2015) 1102-1112. https://doi.org/10.1016/j.aeue.2015.04.009
- Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm
- Zhan, G., Shi, W., Deng, J., 2012. Design and implementation of TARF: a trust-aware routing framework for WSNs. IEEE Trans. Dependable Secure Comput. 9 (2), 184-197. https://doi.org/10.1109/TDSC.2011.58
- Zahariadis, T., Leligou, H., Karkazis, P., Trakadas, P., Papaefstathiou, I., Vangelatos, C., Besson, L., 2011. Design and implementation of a trust-aware routing protocol for Largewsns. Int. J. Network Security Appl. 2 (3).
- Cengiz, K., Dag, T., 2018. Energy aware multi-hop routing protocol for WSNs. IEEE Access 6, 2622-2633. https://doi.org/10.1109/access.2017.2784542
- Purkait, R., Tripathi, S., 2017. Energy aware fuzzy based multi-hop routing protocol using unequal clustering. Wireless Pers. Commun. 94 (3), 809-833. https://doi.org/10.1007/s11277-016-3652-7
- Selvi, M., Velvizhy, P., Ganapathy, S., Nehemiah, H.K., Kannan, A., 2017. A rule based delay constrained energy efficient routing technique for wireless sensor networks. Cluster Comput., 1-10
- MOFPL: Multi-objective fractional particle lion algorithm for the energy aware routing in the WSN
- R. Mohanasundaram, P.S. Periasamy, Clustering based optimal data storage strategy using hybrid swarm intelligence in WSN, Wirel. Pers. Commun. 85 (3) (2015) 1381-1397. https://doi.org/10.1007/s11277-015-2846-8
- R. Kumar, D. Kumar, Multi-objective fractional artificial bee colony algorithm to energy aware routing protocol in wireless sensor network, Wirel. Netw. (2015) 1-14. https://doi.org/10.1007/s11276-017-1537-7
- M. Faheem, R.A. Butt, B. Raza, M.W. Ashraf, Seema Begum, Md.A. Ngadi, V.C. Gungor, Bio-inspired routing protocol for WSN-based smart grid applications in the context of industry 40, Trans. Emerg. Telecommun. Technol. (2018).
- Upendran, V., and R. Dhanapal. "Secure and Distributed On-Demand Randomized Routing in WSN." International Journal of Computers & Technology 15, no. 6 (2016): 6850-6856. https://doi.org/10.24297/ijct.v15i6.3976
- Solving the load balanced clustering and routing problems in WSNs with an fpt-approximation algorithm and a grid structure
- C.P. Low, C. Fang, J.M. Ng, Y.H. Ang, Efficient load-balanced clustering algorithms for wireless sensor networks, Comput. Commun. 31 (4) (2008) 750-759. https://doi.org/10.1016/j.comcom.2007.10.020
- P. Kuila, P.K. Jana, Approximation schemes for load balanced clustering in wireless sensor networks, J. Supercomput. 68 (1) (2014) 87-105. https://doi.org/10.1007/s11227-013-1024-6
- P. Kuila, S.K. Gupta, P.K. Jana, A novel evolutionary approach for load balanced clustering problem for wireless sensor networks, Swarm Evol. Comput. 12 (2013) 48-56. https://doi.org/10.1016/j.swevo.2013.04.002
- S.K. Gupta, P.K. Jana, Energy efficient clustering and routing algorithms for wireless sensor networks: GA based approach, Wirel. Pers. Commun.83 (3) (2015) 2403-2423. https://doi.org/10.1007/s11277-015-2535-7
- P. Kuila, P.K. Jana, Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach, Eng. Appl. Artif. Intell. 33 (2014) 127-140. https://doi.org/10.1016/j.engappai.2014.04.009
- M. Azharuddin, P.K. Jana, PSO-based approach for energy-efficient and energy-balanced routing and clustering in wireless sensor networks, Soft Comput. 21 (22) (2017) 6825-6839. https://doi.org/10.1007/s00500-016-2234-7
- P.S. Mann, S. Singh, Energy efficient clustering protocol based on improved metaheuristic in wireless sensor networks, J. Netw. Comput. Appl. 83 (2017) 40-52. https://doi.org/10.1016/j.jnca.2017.01.031
- Stutzle, T. and Dorigo, M., 1999. ACO algorithms for the traveling salesman problem. Evolutionary algorithms in engineering and computer science, 4, pp.163-183.
- Prakasam, Anandkumar, and Nickolas Savarimuthu. "Metaheuristic algorithms and probabilistic behaviour: a comprehensive analysis of Ant Colony Optimization and its variants." Artificial Intelligence Review 45, no. 1 (2016): 97-130. https://doi.org/10.1007/s10462-015-9441-y
- Van Laarhoven, P.J. and Aarts, E.H., 1987. Simulated annealing. In Simulated annealing: Theory and applications (pp. 7-15). Springer, Dordrecht.