Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance = Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance

다국어 초록 (Multilingual Abstract)

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm’s performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

참고문헌 (Reference)

1 T. Yigit, "Using the metaheuristic methods for real-time optimisation of dynamic school bus routing problem and an application" 11 (11): 123-133, 2018

2 A. Harter, "The Anatomy of a Context-Aware Application" 8 : 187-197, 2002

3 G. Zhou, "Solving large-scale 0-1 knapsack problem by the social-spider optimisation algorithm" 9 (9): 433-441, 2018

4 J. C. Fan, "RoughPSO : rough set-based particle swarm optimisation" 12 (12): 245-253, 2018

5 H. Y. Gao, "Quantum-inspired glowworm swarm optimisation and its application" 8 (8): 91-100, 2017

6 J. J. Zhang, "Privacy protection based on many-objective optimization algorithm" 31 (31): 2019

7 C. Li, "Overview of Wireless Sensor Networks" 36 (36): 1-22, 2005

8 S. Phoemphon, "Optimized Hop Angle Relativity for DV-Hop Localization in Wireless Sensor Networks" 6 : 78149-78172, 2018

9 R. C. He, "Optimisation of dangerous goods transport based on the improved ant colony algorithm" 8 (8): 210-217, 2017

10 Z. H. Cui, "Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things" 132 : 217-229, 2017

11 Xingjuan Cai, "Optimal LEACH Protocol with Improved Bat Algorithm in Wireless Sensor Networks" 한국인터넷정보학회 13 (13): 2469-2490, 2019

12 Z. B. Wang, "Node localization of wireless sensor networks based on bat algorithm" 50 (50): 90-94, 2014

13 B. P. Zhao, "Multi-objective classification based on NSGA-II" 9 (9): 539-546, 2018

14 K. E. Heraguemi, "Multi-objective bat algorithm for mining numerical association rules" 11 (11): 239-248, 2018

15 C. H. Wu, "Mobile Sensor Networks Self Localization based on Multi-dimensional Scaling" 4038-4043, 2007

16 Z. H. Cui, "Malicious code detection based on CNNs and multi-objective algorithm" 129 : 50-58, 2019

17 L. Girod, "Locating tiny sensors in time and space: a case study" 214-219, 2002

18 L. Gui, "Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks" 24 : 55-73, 2015

19 X. J. Cai, "Improved bat algorithm with optimal forage strategy and random disturbance strategy" 8 (8): 205-214, 2016

20 Z. H. Cui, "Improved NSGA-III with selection-and-elimination operator" 49 : 22-23, 2019

21 Z. Wei, "Improved DV-Hop Algorithm Using Locally Weighted Linear Regression in Anisotropic Wireless Sensor Networks" 98 (98): 3335-3353, 2018

22 M. Bougherara, "IP assignment for efficient NoC-based system design using multi-objective particle swarm optimization" 12 (12): 203-213, 2018

23 G. Saranya, "Hybrid particle swarm optimisation with mutation for code smell detection" 12 (12): 186-195, 2018

24 M. Q. Zhang, "Hybrid multi-objective cuckoo search with dynamical local search" 10 (10): 199-208, 2018

25 Zhenzhou Tang, "How Network Coding Benefits Converge-Cast in Wireless Sensor Networks" 한국인터넷정보학회 7 (7): 1180-1197, 2013

26 Gaige Wang, "High Performance Computing for Cyber Physical Social Systems by Using Evolutionary Multi-Objective Optimization Algorithm" 1-1, 2017

27 G. Anastasi, "Energy Conservation in Wireless Sensor Networks : A Survey" 7 (7): 537-568, 2009

28 Z. H. Cui, "Detection of Malicious Code Variants Based on Deep Learning" 14 (14): 3187-3196, 2018

29 D. Niculescu, "DV based positioning in ad hoc networks" 22 : 267-280, 2003

30 L. Doherty, "Convex position estimation in wireless sensor networks" 1655-1663, 2001

31 X. J. Cai, "Bat algorithm with triangle-flipping strategy for numerical optimization" 9 (9): 199-215, 2018

32 Z. H. Cui, "Bat algorithm with principal component analysis" 10 (10): 603-622, 2019

33 R. Mohammadi, "An intelligent traffic engineering method for video surveillance systems over software defined networks using ant colony optimization" 12 (12): 173-185, 2018

34 Y. Cao, "An improved twin support vector machine based on multi-objective cuckoo search for software defect prediction" 11 (11): 282-291, 2018

35 M. Abdel-Baset, "An improved cuckoo search algorithm for integer programming problems" 9 (9): 66-81, 2018

36 M. Abdel-Baset, "An improved cuckoo search algorithm for integer programming problems" 9 (9): 66-81, 2018

37 D. Niculescu, "Ad hoc positioning system (APS) using AoA" 1734-1743, 2003

38 P. Guo, "A variable threshold-value authentication architecture for wireless mesh networks" 15 (15): 929-935, 2014

39 I. F. Akyildiz, "A survey on sensor networks" 40 (40): 102-114, 2002

40 K. Akkaya, "A survey on routing protocols for wireless sensor networks" 3 (3): 325-349, 2005

41 A. M. Hegland, "A survey of key management in ad hoc networks" 8 (8): 48-66, 2006

42 C. Chow, "A privacy-preserving location monitoring system for wireless sensor networks" 10 (10): 94-107, 2011

43 Z. H. Cui, "A pigeon-inspired optimization algorithm for many-objective optimization problems" 62 (62): 70212-, 2019

44 Z. H. Cui, "A pigeon-inspired optimization algorithm for many-objective optimization problems" 62 (62): 70212-, 2019

45 Z. H. Cui, "A novel oriented cuckoo search algorithm to improve DV-Hop performance for cyber–physical systems" 103 : 42-52, 2017

46 W. X. Yu, "A new method to solve optimisation problems via fixed point of firefly algorithm" 11 (11): 249-256, 2018

47 X. S. Yang, "A new metaheuristic bat-inspired algorithm" 284 : 65-74, 2010

48 Y. Shi, "A modified particle swarm optimizer" 69-73, 1998

49 L. Kezhong, "A modified DV-Hop localization algorithm for wireless sensor networks" 511-514, 2009

50 Z. H. Cui, "A hybrid many-objective cuckoo search algorithm" 23 : 10681-10697, 2019

51 E. Raj, "A firefly inspired game dissemination and QoS-based priority pricing strategy for online social network games" 11 (11): 202-217, 2018