Abstract
The mobile sink is usually applied to improving the performance of wireless sensor networks (WSNs). This improvement is subject to the itinerary plan, through which the sojourn times and settlement locations are determined. This paper simultaneously considers multiple criteria like data merit, latency, deadline, used memory, and travel time, then presents a multi-objective Integer Quadratically Constrained Quadratic Programming (IQCQP) for planning itinerary of mobile sink in WSNs. In practice, this programming should be solved in a centralized node and it is computationally NP-hard, but the mathematical formulation can help estimate the problem characteristic and figure out the optimal path for the mobile sink. In addition, this paper proposes a multi-attribute algorithm where the sink gathers attributes of possible sites and compares them by applying fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Therefore, the neighboring adjacent sites are ranked by TOPSIS, then the best site is selected and the mobile sink moves there. The proposed algorithm has lower complexity and utilizes local information to make a decision, therefore it is can handle dynamic features of WSNs. The proposed methods are assessed through rigorous simulations, the results reveal that the proposed distributed algorithm outperforms counterparts in terms of performance metrics (total merit, latency, gathered, expired, and lost data) in a heterogeneous WSN.
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Agarwal V, Tapaswi S, Chanak P (2021) A survey on path planning techniques for mobile sink in IoT-enabled wireless sensor networks. Wirel Pers Commun 119(1):211–238. https://doi.org/10.1007/s11277-021-08204-w
Akkaya K, Younis M, Bangad M (2005) Sink repositioning for enhanced performance in wireless sensor networks. Comput Netw 49(4):512–534. https://doi.org/10.1016/j.comnet.2005.01.014
Alhasanat A, Alhasanat K, Ahmed M (2015) Range-based data gathering algorithm with a mobile sink in wireless sensor networks. Int J Wirel Mob Netw 7(6):1–13. https://doi.org/10.5121/ijwmn.2015.7601
Alsaafin A, Khedr AM, Al Aghbari Z (2018) Distributed trajectory design for data gathering using mobile sink in wireless sensor networks. AEU-Int J Electron C 96:1–12. https://doi.org/10.1016/j.aeue.2018.09.005
Anwit R, Jana PK (2018) A variable length genetic algorithm approach to optimize data collection using mobile sink in wireless sensor networks. In: 5th International Conference on signal processing and integrated networks, SPIN, pp 73–77, https://doi.org/10.1109/SPIN.2018.8474259
Anwit R, Tomar A, Jana PK (2020) Tour planning for multiple mobile sinks in wireless sensor networks: a shark smell optimization approach. Appl Soft Comput J 97(106):802. https://doi.org/10.1016/j.asoc.2020.106802
Bencan G, Panpan D, Peng C et al (2020) Evolutionary game-based trajectory design algorithm for mobile sink in wireless sensor networks. Int J Distrib Sens Netw 16(3):1–10. https://doi.org/10.1177/1550147720911000
Chakrabarti A, Sabharwal A, Aazhang B (2003) Using predictable observer mobility for power efficient design of sensor networks. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer, pp 129–145, https://doi.org/10.1007/3-540-36978-3_9
Chansombat S, Pongcharoen P, Hicks C (2019) A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry. Int J Prod Res 57(1):61–82. https://doi.org/10.1080/00207543.2018.1459923
CPLEX II (2009) V12. 1: User’s manual for CPLEX
Din MSU, Rehman MAU, Ullah R et al (2020) Towards network lifetime enhancement of resource constrained iot devices in heterogeneous wireless sensor networks. Sensors (Switzerland) 20(15):1–23. https://doi.org/10.3390/s20154156
Dong M, Ota K, Yang LT et al (2014) Mobile agent-based energy-aware and user-centric data collection in wireless sensor networks. Comput Netw 74:58–70. https://doi.org/10.1016/j.comnet.2014.06.019
Gjanci P, Petrioli C, Basagni S et al (2018) Path finding for maximum value of information in multi-modal underwater wireless sensor networks. IEEE Trans Mob Comput 17(2):404–418. https://doi.org/10.1109/TMC.2017.2706689
Gupta N, Gupta V (2016) A review on sink mobility aware fast and efficient data gathering in wireless sensor networks. In: International Conference on advances in computing, communication and automation, ICACCA, IEEE, pp 1–4, https://doi.org/10.1109/ICACCA.2016.7578877
Gupta GP, Saha B (2020) Load balanced clustering scheme using hybrid metaheuristic technique for mobile sink based wireless sensor networks. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-01909-z
Hart WE, Laird CD, Watson JP et al (2017) Pyomo-optimization modeling in python, vol 67. Springer. https://doi.org/10.1007/978-3-319-58821-6
He X, Fu X, Yang Y (2019) Energy-efficient trajectory planning algorithm based on multi-objective pso for the mobile sink in wireless sensor networks. IEEE Access 7:176,204-176,217. https://doi.org/10.1109/ACCESS.2019.2957834
Ji S (2019) Path planning for mobile sink based on enhanced ant colony optimization algorithm in wireless sensor networks. Xitong Fangzhen Xuebao /J Syst Simul 31(11):2543–2552. https://doi.org/10.16182/j.issn1004731x.joss.19-0298
Kaswan A, Nitesh K, Jana PK (2017) Energy efficient path selection for mobile sink and data gathering in wireless sensor networks. AEU-Int J Electron C 73:110–118. https://doi.org/10.1016/j.aeue.2016.12.005
Kaswan A, Singh V, Jana PK (2018) A multi-objective and PSO based energy efficient path design for mobile sink in wireless sensor networks. Pervasive Mob Comput 46:122–136. https://doi.org/10.1016/j.pmcj.2018.02.003
Kaur N, Sood SK (2015) An energy-efficient architecture for the Internet of Things (IoT). IEEE Syst J 11(2):796–805. https://doi.org/10.1109/jsyst.2015.2469676
Keskin ME, Yiğit V (2020) Maximizing the lifetime in wireless sensor networks with multiple mobile sinks having nonzero travel times. Comput Ind Eng 148(106):719. https://doi.org/10.1016/j.cie.2020.106719
Khalily-Dermany M (2021) A decentralized algorithm to combine topology control with network coding. J Parallel Distrib Comput 149:174–185. https://doi.org/10.1016/j.jpdc.2020.12.001, https://www.sciencedirect.com/science/article/pii/S0743731520304172
Khalily-Dermany M, Nadjafi-Arani MJ (2017) Itinerary planning for mobile sinks in network-coding-based wireless sensor networks. Comput Commun 111:1–13. https://doi.org/10.1016/j.comcom.2017.07.001
Khalily-Dermany M, Nadjafi-Arani MJ (2019) Mathematical aspects in combining network coding with transmission range adjustment. IEEE Commun Lett 23(9):1568–1571. https://doi.org/10.1109/LCOMM.2019.2924625
Khan MI, Gansterer WN, Haring G (2013) Static vs. mobile sink: The influence of basic parameters on energy efficiency in wireless sensor networks. Comput Commun 36(9):965–978. https://doi.org/10.1016/j.comcom.2012.10.010
Mehto A, Tapaswi S, Pattanaik KK (2020a) PSO-based rendezvous point selection for delay efficient trajectory formation for mobile sink in wireless sensor networks. In: 2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020, IEEE, pp 252–258. https://doi.org/10.1109/COMSNETS48256.2020.9027330
Mehto A, Tapaswi S, Pattanaik KK (2020b) A review on rendezvous based data acquisition methods in wireless sensor networks with mobile sink. Wirel Netw 26(4):2639–2663. https://doi.org/10.1007/s11276-019-02022-6
Nitesh K, Jana PK (2019) Convex hull based trajectory design for mobile sink in wireless sensor networks. Int J Ad Hoc Ubiquitous Comput 30(1):26–36. https://doi.org/10.1504/IJAHUC.2019.097092
Nitesh K, Kaswan A, Jana PK (2019) Energy density based mobile sink trajectory in wireless sensor networks. Microsyst Technol 25(5):1771–1781. https://doi.org/10.1007/s00542-017-3569-4
Park J, Kim S, Youn J et al (2020) (2020) Iterative sensor clustering and mobile sink trajectory optimization for wireless sensor network with nonuniform density. Wirel Commun Mob Comput. https://doi.org/10.1155/2020/8853662
Preeth SKL, Dhanalakshmi R, Shakeel PM (2020) An intelligent approach for energy efficient trajectory design for mobile sink based IoT supported wireless sensor networks. Peer-to-Peer Netw Appl 13(6):2011–2022. https://doi.org/10.1007/s12083-019-00798-0
Raj PV, Khedr AM, Aghbari ZA (2020) Data gathering via mobile sink in wsns using game theory and enhanced ant colony optimization. Wirel Netw 26(4):2983–2998. https://doi.org/10.1007/s11276-020-02254-x
Roy S, Mazumdar N, Pamula R (2021) An optimal mobile sink sojourn location discovery approach for the energy-constrained and delay-sensitive wireless sensor network. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-020-02886-z
Salarian H, Chin KW, Naghdy F (2014) An energy-efficient mobile-sink path selection strategy for wireless sensor networks. IEEE Trans Veh Technol 63(5):2407–2419. https://doi.org/10.1109/TVT.2013.2291811
Salih MM, Zaidan BB, Zaidan AA et al (2019) Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017. Comput Oper Res 104:207–227. https://doi.org/10.1016/j.cor.2018.12.019
Sapre S, Mini S (2021) A differential moth flame optimization algorithm for mobile sink trajectory. Peer-to-Peer Netw Appl 14(1):44–57. https://doi.org/10.1007/s12083-020-00947-w
Tan CG, Xu K, Wang JX et al (2009) A sink moving scheme based on local residual energy of nodes in wireless sensor networks. J Cent South Univ Technol (English Edition) 16(2):265–268. https://doi.org/10.1007/s11771-009-0045-z
Tao L, Zhang XM, Liang W (2019) Efficient algorithms for mobile sink aided data collection from dedicated and virtual aggregation nodes in energy harvesting wireless sensor networks. IEEE Trans Green Commun Netw 3(4):1058–1071. https://doi.org/10.1109/TGCN.2019.2927619
Tashtarian F, Yaghmaee Moghaddam MH, Sohraby K et al (2015) ODT: Optimal Deadline-based Trajectory for mobile sinks in wsn: a decision tree and dynamic programming approach. Comput Netw 77:128–143. https://doi.org/10.1016/j.comnet.2014.12.003
uz Zaman SK, Jehangiri AI, Maqsood T et al (2021) Mobility-aware computational offloading in mobile edge networks: a survey. Cluster Comput. https://doi.org/10.1007/s10586-021-03268-6
Vajdi A, Zhang G, Zhou J et al (2018) A new path-constrained rendezvous planning approach for large-scale event-driven wireless sensor networks. Sensors (Switzerland) 18(5):1434. https://doi.org/10.3390/s18051434
Varga A, Hornig R (2008) An overview of the OMNeT++ simulation environment. In: SIMUTools 2008—1st International ICST Conference on simulation tools and techniques for communications, networks and systems. ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, Belgium, pp 60:1—-60:10, https://doi.org/10.4108/ICST.SIMUTOOLS2008.3027
Wang J, Cao J, Sherratt RS et al (2018) An improved ant colony optimization-based approach with mobile sink for wireless sensor networks. J Supercomput 74(12):6633–6645. https://doi.org/10.1007/s11227-017-2115-6
Wang J, Gao Y, Zhou C et al (2020) Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs. Comput Mater Contin 62(2):695–711. https://doi.org/10.32604/cmc.2020.08674
Yu F, Lee E, Park S et al (2010) A simple location propagation scheme for mobile sink in wireless sensor networks. IEEE Commun Lett 14(4):321–323. https://doi.org/10.1109/LCOMM.2010.04.092330
Yun Y, Xia Y (2010) Maximizing the lifetime of wireless sensor networks with mobile sink in delay-tolerant applications. IEEE Trans Mob Comput 9(9):1308–1318. https://doi.org/10.1109/TMC.2010.76
Yun Y, Xia Y, Behdani B et al (2013) Distributed algorithm for lifetime maximization in a delay-tolerant wireless sensor network with a mobile sink. IEEE Trans Mob Comput 12(10):1920–1930. https://doi.org/10.1109/TMC.2012.152
Zareei M, Islam AK, Vargas-Rosales C et al (2018) Mobility-aware medium access control protocols for wireless sensor networks: a survey. J Netw Comput Appl 104:21–37. https://doi.org/10.1016/j.jnca.2017.12.009
Zhan C, Zeng Y, Zhang R (2018) Energy-efficient data collection in UAV enabled wireless sensor network. IEEE Wirel Commun Lett 7(3):328–331. https://doi.org/10.1109/LWC.2017.2776922, arXiv:1708.00221
Zhu C, Zhang S, Han G et al (2016) A greedy scanning data collection strategy for large-scale wireless sensor networks with a mobile sink. Sensors (Switzerland). https://doi.org/10.3390/s16091432
Zhu C, Quan K, Han G et al (2018) A high-available and location predictive data gathering scheme with mobile sinks for wireless sensor networks. Comput Netw 145:156–164. https://doi.org/10.1016/j.comnet.2018.08.022
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Khalily-Dermany, M. Multi-criteria itinerary planning for the mobile sink in heterogeneous wireless sensor networks. J Ambient Intell Human Comput 14, 8531–8550 (2023). https://doi.org/10.1007/s12652-021-03616-9
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DOI: https://doi.org/10.1007/s12652-021-03616-9