A Stable and Energy-Efficient Routing Algorithm Based on Learning Automata Theory for MANET

L. Blazevic, L. Buttyan, S. Capkun, et al. Self-organization in mobile ad-hoc networks: the approach of terminodes [J]. IEEE Communications Magazine, 2001, 39(6): 166–174

R. Bruno, M. Conti, E. Gregori. Mesh networks: commodity multihop Ad Hoc networks [J]. IEEE Press, 2005, 43(3): 123–131

Z. Yang, Y. Liu. Understanding node localizability of wireless Ad Hoc and sensor networks [J]. IEEE Transactions on Mobile Computing, 2012, 11(8): 1249–1260

M. A. Rahman, M. S. Hossain. A location-based mobile crowdsensing framework supporting a massive Ad Hoc social network environment [J]. IEEE Communications Magazine, 2017, 55(3): 76–85

N. T. Dinh, Y. Kim. Information-centric dissemination protocol for safety information in vehicular ad-hoc networks [J]. Wireless Networks, 2017, 23(5): 1359–1371

S. J. Lee, W. Su, M. Gerla. Wireless Ad Hoc multicast routing with mobility prediction [J]. Mobile Networks and Applications, 2001, 6(4): 351–360

B. An, S. Papavassiliou. MHMR: Mobility-based hybrid multicast routing protocol in mobile Ad Hoc wireless networks [J]. Wireless Communications and Mobile Computing, 2003, 3(2): 255–270

A. Bentaleb, S. Harous, A. Boubetra. A weight based clustering scheme for mobile Ad Hoc networks [C]//The 11th International Conference on Advances in Mobile Computing and Multimedia, Vienna, 2013: 161–166

S. Guo, O. Yang. Maximizing multicast communication lifetime in wireless mobile Ad Hoc networks [J]. IEEE Transactions on Vehicular Technology, 2008, 57(4): 2414–2425

H. B. Thriveni, G. M. Kumar, R. Sharma. Performance evaluation of routing protocols in mobile ad-hoc networks with varying node density and node mobility [C]//International Conference on Communication Systems and Network Technologies, Gwalior, 2013: 252–256

R. Suraj, S. Tapaswi, S. Yousef, et al. Mobility prediction in mobile Ad Hoc networks using a lightweight genetic algorithm [J]. Wireless Networks, 2016, 22(6): 1797–1806

T. Manimegalai, C. Jayakumar, G. Gunasekaran. Using animal communication strategy (ACS) for MANET routing [J]. Journal of the National Science Foundation of Sri Lanka, 2015, 43(3): 199–208

G. Singal, V. Laxmi, M. S. Gaur, et al. Moralism: mobility prediction with link stability based multicast routing protocol in MANETs [J]. Wireless Networks, 2017, 23(3): 663–679

Selvi, F. A. Pitchaimuthu. Ant based multipath backbone routing for load balancing in MANET [J]. IET Communications, 2017, 11(1): 136–141

A. Kout, S. Labed, S. Chikhi, et al. AODVCS, a new bio-inspired routing protocol based on cuckoo search algorithm for mobile Ad Hoc networks [J]. Wireless Networks, 2017(9): 1–11

J. Liu, Y. Xu, X. Jiang. End-to-end delay in two hop relay MANETs with limited buffer [C]//Second International Symposium on Computing and Networking, Shizuoka, 2015: 151–156

S. Chettibi, S. Chikhi. Adaptive maximum-lifetime routing in mobile ad-hoc networks using temporal difference reinforcement learning [J]. Evolving Systems, 2014, 5(2): 89–108

A. Petrowski, F. Aissanou, I. Benyahia, et al. Multicriteria reinforcement learning based on a Russian doll method for network routing [C]//IEEE International Conference Intelligent Systems, London, 2010: 321–326

P. Vijayalakshmi, S. A. J. Francis, J. A. Dinakaran. A robust energy efficient ant colony optimization routing algorithm for multi-hop Ad Hoc networks in MANETs [J]. Wireless Networks, 2016, 22(6): 2081–2100

S. Chettibi, S. Chikhi. Dynamic fuzzy logic and reinforcement learning for adaptive energy efficient routing in mobile ad-hoc networks [J]. Applied Soft Computing, 2016,38: 321–328

P. Srivastava, R. Kumar. A new QoS-aware routing protocol for MANET using artificial neural network [J]. Journal of Computing and Information Technology, 2016, 24(3): 221–235

S. K. Das, S. Tripathi. Intelligent energy-aware efficient routing for MANET [J]. Wireless Networks, 2016(7): 1–21

K. S. Narendra, M. A. L. Thathachar. Learning automata: An introduction [M]. USA: DBLP, 2012

M. A. L. Thathachar, P. S. Sastry. A hierarchical system of learning automata that can learn the globally optimal path [J]. Information Sciences, 1987, 42(2): 143–166

H. Beigy, M. R. Meybodi. Utilizing distributed learning automata to solve stochastic shortest path problems [J]. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2006, 14(05): 591–615

M. L. Thathachar, P. S. Sastry. Varieties of learning automata: an overview [J]. IEEE Transactions on Systems Man & Cybernetics Part B Cybernetics A Publication of the IEEE Systems Man & Cybernetics Society, 2002, 32(6): 711–722

A. A. Anasane, R. A. Satao. A survey on various multipath routing protocols in wireless sensor networks [J]. Procedia Computer Science, 2016, 79: 610–615

D. B. West. Introduction to graph theory [M]. 2nd ed. USA: McGraw-Hill Higher Education, 2005: 260

I. Das, D. K. Lobiyal, C. P. Katti. Multipath routing in mobile Ad Hoc network with probabilistic splitting of traffic [J]. Wireless Networks, 2016, 22(7): 2287–2298

H. J. Kushner. Approximation and weak convergence methods for random processes, with applications to stochastic systems theory [M]. USA: MIT Press, 1984

G. Wahba. Erratum: spline interpolation and smoothing on the sphere [J]. Siam Journal on Scientific & Statistical Computing, 2012, 2(2): 5–16

J. Chen, W. Li. Convergence behaviour of inexact Newton methods under weak Lipschitz condition [J]. Journal of Computational & Applied Mathematics, 2006, 191(1):143–164

G. A. Anastassiou, S. G. Gal. Approximation theory: Moduli of continuity and global smoothness preservation [M]. USA: DBLP, 2000

G. F. Riley, T. R. Henderson. The ns-3 network simulator [J]. Modeling and Tools for Network Simulation, 2010: 15–34

M. S. Khan, Q. K. Jadoon, M. I. Khan. Mobile and wireless technology 2015: A comparative performance analysis of MANET routing protocols under security attacks [M]. Germany: Springer Berlin Heidelberg, 2015, 310: 137–145