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Connectivity preserving obstacle avoidance localized motion planning algorithms for mobile wireless sensor networks

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Abstract

Mobile wireless sensor networks (MWSN) are better in terms of coverage and it plays an important role in ubiquitous wireless networks. We design Cellular Automaton (CA) based localized motion planning algorithms for mobile wireless sensors. We propose cellular automaton based algorithms for both dispersion and gathering problems. The dispersion algorithm is intended for self-deployment purpose with the goal of increasing the sensing coverage of the network. We apply a probabilistic approach that maximizes the network coverage as well as maintains the connectivity of the network. In addition, after finishing the dispersion, a gathering algorithm guides the sensors to round up to a single place for collection. It is noteworthy that both algorithms are synchronous which means that all sensors run algorithms in parallel at the same time. Moreover, our algorithms allow the sensors to avert obstacles in their path of movement. As cellular automaton functions depend on the local information about the network strictly, they are suitable for MWSN in practice. We evaluate the performance of our algorithm based on some defined metrics i.e., coverage, strongly connected coverage. We find that our dispersion algorithm maintains better coverage than state-of-the-art algorithm. Furthermore, in case of synchronous gathering, sensors get disconnected for some cases to form multiple clusters while using state-of-the-art algorithm, but our proposed gathering algorithm is always able to provide the connectivity.

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References

  1. Martínez J-F, Garcí A-B, Corredor I, López L, Hernández V, Dasilva A (2007) Qos in wireless sensor networks: survey and approach. In: Proceedings of the 2007 Euro American conference on Telematics and information systems. ACM, New York, p 20

  2. Aldeer MMN A summary survey on recent applications of wireless sensor networks. In 2013 IEEE Student Conference on Research and Developement, Putrajaya, Malaysia, pp 485–490, vol 2013

  3. Fernández-Lozano J, Gomez-Ruiz J, Martín-Guzmán M, Martín-Ávila J, Carlos SB, García-Cerezo A (2017) Wireless sensor networks for urban information systems: Preliminary results of integration of an electric vehicle as a mobile node. In: Iberian Robotics conference. Sevilla. Springer, Spain, pp 190–199

  4. Kar K, Banerjee S (2003) Node placement for connected coverage in sensor networks. In: WiOpt’03: Modeling and Optimization in Mobile. Ad Hoc and Wireless Networks, Sophia Antipolis, p 2

  5. Ateṡ E, Kalayci TE, Uġur A (2017) Area-priority-based sensor deployment optimisation with priority estimation using k-means. IET Commun 11(7):1082–1090

    Article  Google Scholar 

  6. Cheng W, Li M, Liu K, Liu Y, Li X, Liao X (2008) Sweep coverage with mobile sensors. In: 2008 IEEE international symposium on parallel and distributed processing, Miami, FL, USA, pp 1–9

  7. Gupta V, Jeffcoat DE, Murray RM (2006) On sensor coverage by mobile sensors. In: 45th IEEE conference on decision and control. IEEE, San Diego, pp 5912–5917

  8. Yazıcıoġlu AY, Egerstedt M, Shamma JS (2013) A game theoretic approach to distributed coverage of graphs by heterogeneous mobile agents. IFAC Proceedings Volumes 46(27):309–315

    Article  Google Scholar 

  9. Yu X, Huang W, Lan J, Qian X (2012) A novel virtual force approach for node deployment in wireless sensor network. In: 2012 IEEE 8th international conference on distributed computing in sensor systems, Hangzhou, China, pp 359–363

  10. Rout M, Roy R (2016) Dynamic deployment of randomly deployed mobile sensor nodes in the presence of obstacles. Ad Hoc Netw 46:12–22

    Article  Google Scholar 

  11. Choudhury S, Akl SG, Salomaa K (2012) Energy efficient cellular automaton based algorithms for mobile wireless sensor networks. IEEE, Paris, pp 2341–2346

  12. Choudhury S, Salomaa K, Akl SG (2015) Cellular automaton based localized algorithms for mobile sensor networks. Int J Unconv Comput 11:417–447

    MATH  Google Scholar 

  13. Munir A, Uzzaman S, Hossen MS, Choudhury S, Alam M (2016) Localized motion planning algorithm for mobile wireless sensor networks. Int J Unconv Comput 12:363–391

    Google Scholar 

  14. Degener B, Kempkes B, Langner T, Meyer auf der Heide F, Pietrzyk P, Wattenhofer R (2011) A tight runtime bound for synchronous gathering of autonomous robots with limited visibility. In: Proceedings of the 23rd annual ACM symposium on Parallelism in algorithms and architectures. ACM, New York, pp 139–148

  15. Ando H, Suzuki I, Yamashita M (1995) Formation and agreement problems for synchronous mobile robots with limited visibility. In: Proceedings of the 1995 IEEE international symposium on intelligent control. IEEE, Monterey, pp 453–460

  16. Bhagat S, Chaudhuri SG, Mukhopadhyaya K (2016) Fault-tolerant gathering of asynchronous oblivious mobile robots under one-axis agreement. J Discrete Algoritms 36:50–62

    Article  MathSciNet  MATH  Google Scholar 

  17. Baryshnikov YM, Coffman E, Kwak KJ (2008) High performance sleep-wake sensor systems based on cyclic cellular automata. In: International conference on information processing in sensor networks, 2008 IPSN’08. IEEE, St. Louis, pp 517–526

  18. Choudhury S, Salomaa K, Akl SG (2012) A cellular automaton model for wireless sensor networks. J Cell Autom 7(3):223–241

    MATH  Google Scholar 

  19. Cunha RO, Silva AP, Loureiro AA, Ruiz LB (2005) Simulating large wireless sensor networks using cellular automata. In: Proceedings of the 38th annual symposium on simulation. IEEE Computer Society, San Diego, pp 323–330

  20. Choudhury S, Salomaa K, Akl SG (2014) Cellular automaton-based algorithms for the dispersion of mobile wireless sensor networks. Int J Parallel Emergent Distrib Syst 29(2):147–177

    Article  Google Scholar 

  21. Choudhury S (2017) Cellular automata and wireless sensor networks. Springer International Publishing, Cham, pp 321–335

    MATH  Google Scholar 

  22. Li W, Zomaya AY, Al-Jumaily A (2009) Cellular automata based models of wireless sensor networks. In: Proceedings of the 7th ACM international symposium on Mobility management and wireless access. ACM, New York, pp 1–6

  23. Kumar KJ, Reddy KCK, Salivahanan S (2011) Novel and efficient cellular automata based symmetric key encryption algorithm for wireless sensor networks. Int J Comput Appl 13(4):30–37

    Google Scholar 

  24. Teymorian AY, Ma L, Cheng X (2007) Cab: A cellular automata-based key management scheme for wireless sensor networks. In: IEEE Military Communications Conference, 2007. MILCOM 2007. IEEE, Orlando, pp 1–7

  25. Torbey S, Akl SG (2012) Reliable node placement in wireless sensor networks using cellular automata. In: International conference on unconventional computing and natural computation. Springer, Berlin, pp 210–221

  26. Rashid N, Choudhury S, Salomaa K (2018) Localized algorithms for redundant readers elimination in rfid networks, International Journal of Parallel. Emergent and Distrib Syst 0(0):1–12

    Google Scholar 

  27. Chen J, Li J, He S, He T, Gu Y, Sun Y (2013) On energy-efficient trap coverage in wireless sensor networks. ACM Trans Sensor Netw 10(1):2

    Article  Google Scholar 

  28. Du YL, Wu L (2017) Connected sensor cover and related problems. Peer-to-Peer Netw Appl 10(6):1299–1303

    Article  Google Scholar 

  29. He S, Gong X, Zhang J, Chen J, Sun Y (2014) Curve-based deployment for barrier coverage in wireless sensor networks. IEEE Trans Wirel Commun 13(2):724–735

    Article  Google Scholar 

  30. He S, Shin DH, Zhang J, Chen J, Sun Y (2016) Full-view area coverage in camera sensor networks: dimension reduction and near-optimal solutions. IEEE Trans Veh Technol 65(9):7448– 7461

    Article  Google Scholar 

  31. He S, Shu Y, Cui X, Wei C, Chen J, Shi Z (2017) A trust management based framework for fault-tolerant barrier coverage in sensor networks. In: 2017 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, San Francisco, pp 1–6

  32. Choudhury S, Salomaa K, Akl SG (2015) Cellular automata and object monitoring in mobile wireless sensor networks. In: 2015 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, New Orleans, pp 1344–1349

  33. Poudel P, Sharma G (2017) Universally optimal gathering under limited visibility. In: International Symposium on Stabilization, Safety, and Security of Distributed Systems. Springer, Boston, pp 323–340

  34. Flocchini P, Prencipe G, Santoro N, Widmayer P (2005) Gathering of asynchronous robots with limited visibility. Theor Comput Sci 337(1-3):147–168

    Article  MathSciNet  MATH  Google Scholar 

  35. Saadatmand S, Moazzami D, Moeini A (2016) A cellular automaton based algorithm for mobile sensor gathering. J Algorithms and Comput 47(1):93–99

    Google Scholar 

  36. Yu Q, Jiang W, Leng S, Mao Y (2015) Modeling wireless sensor network based on non-volatile cellular automata. IEICE Trans Commun 98(7):1294–1301

    Article  Google Scholar 

  37. Ko SK, Kim H, Han YS (2013) A ca model for target tracking in distributed mobile wireless sensor network. In: 2013 13th international conference on control, automation and systems (ICCAS 2013), Busan, Korea, pp 1356–1361

  38. Garzon MH (2012) Models of massive parallelism: analysis of cellular automata and neural networks. Springer Science & Business Media, Berlin

    MATH  Google Scholar 

  39. Munir A, Hossen MS, Choudhury S Localized load balancing in RFID systems. In 2016 International Conference on Theory and Practice of Natural Computing, Japan, pp 34–45

  40. Munir A, Hossen MS, Choudhury S CARRE: cellular automaton based redundant readers elimination in RFID networks. In: 2016 International Conference on Communications (ICC), Malaysia, pp 1–6

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Acknowledgment

Authors of this paper are grateful to the anonymous reviewers for their constructive comments and meticulous review about this work which led the authors to an improvement of the work.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Green University of Bangladesh, Dhaka, Bangladesh

    Md. Yeakub Hassan

  2. Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Bangladesh

    Faisal Hussain

  3. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

    Salimur Choudhury

Authors
  1. Md. Yeakub Hassan
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  2. Faisal Hussain
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  3. Salimur Choudhury
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Corresponding author

Correspondence to Salimur Choudhury.

Additional information

This article is part of the Topical Collection: Special Issue on Network Coverage

Guest Editors: Shibo He, Dong-Hoon Shin, and Yuanchao Shu

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Hassan, M.Y., Hussain, F. & Choudhury, S. Connectivity preserving obstacle avoidance localized motion planning algorithms for mobile wireless sensor networks. Peer-to-Peer Netw. Appl. 12, 647–659 (2019). https://doi.org/10.1007/s12083-018-0656-y

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