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Position Unmanned Aerial Vehicles in the Mobile Ad Hoc Network

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Abstract

This paper considers the problem of employing multiple unmanned aerial vehicles (UAVs) to the mobile ad hoc network (MANET) as relay backbone nodes to construct the backbone network, to improve the network connectivity, and to address many issues in the MANET such as linkage, capacity, load balance, and reliability. With considering the dynamic nature of the problem, this study provides several linear location problem models and their extensions to accommodate these issues. Due to the size of linear location models associated with a large number of constraints, the problem becomes computational challenging even with modest size of nodes. To overcome the computational barrier, we recast these location problem models using a quadratic unconstrained binary optimization (QUBO) framework and solve these QUBO models with a Tabu search heuristic with preprocessing. The analysis of the solutions that are produced by QUBO together with the comparisons made with the linear model highlight both the attractiveness and robustness of the proposed approach. The results of this study provide support to future advanced routing protocol development.

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References

  1. Ma, Y., Richards, M., Ghanem, M., Guo, Y., Hassard, J.: Air pollution monitoring and mining based on sensor grid in London. Sensors 8(6), 3601–3623 (2008)

    Article  Google Scholar 

  2. Delot, T., Cenerario, N., Ilarri, S.: Vehicular event sharing with a mobile peer-to-peer architecture. Transport Res. C-Emer. 18(4), 584–598 (2010). doi:10.1016/j.trc.2009.12.003

    Article  Google Scholar 

  3. Gerla, M.: From battlefields to urban grids: New research challenges in ad hoc wireless networks. Pervasive Mob. Comput. 1(1), 77–93 (2005). doi:10.1016/j.pmcj.2005.01.002

    Article  Google Scholar 

  4. Gerla, M., Kleinrock, L.: Vehicular networks and the future of the mobile internet. Comput. Netw. 55(2), 457–469 (2011). doi:10.1016/j.comnet.2010.10.015

    Article  Google Scholar 

  5. Şahin, C., Gundry, S., Uyar, M.Ü.: Markov chain analysis of self-organizing mobile nodes. J. Intell. Robot. Syst. 67(2), 133–153 (2012). doi:10.1007/s10846-011-9649-2

    Article  MATH  Google Scholar 

  6. Luis, M., Fernando, C., Dios, J.R.M.-d., Joaquín, F., Aníbal, O.: A cooperative perception system for multiple UAVs: application to automatic detection of forest fires. J. Field Robot. 23(4), 165–184 (2006)

    Google Scholar 

  7. Bekmezci, İ., Sahingoz, O.K., Temel, Ş.: Flying Ad-Hoc Networks (FANETs): Survey. Ad Hoc Netw. 11(3), 1254–1270 (2013). doi:10.1016/j.adhoc.2012.12.004

    Article  Google Scholar 

  8. Enright, J.J., Savla, K., Frazzoli, E., Francesco Bulloch, S.: Stochastic and dynamic routing problems for multiple uninhabited aerial vehicles. J. Guid. Control Dyn. 32(4), 1152–1166 (2009). doi:10.2514/1.41616

    Article  Google Scholar 

  9. Mehdi, A., Jonathan, P.H.: A robust approach to the UAV task assignment problem. Int. J. Robust. Nonlin. 18(2), 118–134 (2008)

    Article  MATH  Google Scholar 

  10. Alidaee, B., Wang, H., Landram, F.: On the flexible demand assignment problems: case of unmanned aerial vehicles. IEEE Trans. Autom. Sci. Eng. 8(4), 865–868 (2011). doi:10.1109/TASE.2011.2159709

    Article  Google Scholar 

  11. Alidaee, B., Wang, H., Landram, F.: A note on integer programming formulations of the real-time optimal scheduling and flight path selection of UAVs. IEEE Trans. Control Syst. Technol. 17(4), 839–843 (2009)

    Article  Google Scholar 

  12. Sahjendra, N.S., Rong, Z., Phil, C., Siva, B.: Decentralized nonlinear robust control of UAVs in close formation. Int. J. Robust. Nonlin. 13(11), 1057–1078 (2003)

    Article  MATH  Google Scholar 

  13. Roberts, J.: Editorial for journal of field robotics—special issue on UAVs. J. Field Robot. 23(3–4), 163–164 (2006). doi:10.1002/rob.20124

    Article  Google Scholar 

  14. Parr, G., Hailes, S., How, J.P., McGeehan, J., Guo, Y.J.: Guest editorial: communications challenges and dynamics for unmanned autonomous vehicles. IEEE J. Sel. Areas Commun. 30(5), 849–851 (2012). doi:10.1109/JSAC.2012.120601

    Article  Google Scholar 

  15. Zhou, G., Ambrosia, V., Gasiewski, A.J., Bland, G.: Foreword to the special issue on Unmanned Airborne Vehicle (UAV) Sensing systems for earth observations. IEEE Trans. Geosci. Remote Sens. 47(3), 687–689 (2009). doi:10.1109/TGRS.2009.2013059

    Article  Google Scholar 

  16. Shima, T., Pagilla, P.R.: Special issue on analysis and control of multi-agent dynamic systems. J. Dyn. Syst. Meas. Control. 129(5), 569–570 (2007). doi:10.1115/1.2772562

    Article  Google Scholar 

  17. Michael, N., Scaramuzza, D., Kumar, V.: Special issue on micro-UAV perception and control. Auton. Robot. 33(1–2), 1–3 (2012). doi:10.1007/s10514-012-9295-y

    Article  Google Scholar 

  18. Rohde, S., Putzke, M., Wietfeld, C.: Ad hoc self-healing of OFDMA networks using UAV-based relays. Ad Hoc Netw. 11(7), 1893–1906 (2013). doi:10.1016/j.adhoc.2012.06.014

    Article  Google Scholar 

  19. Grøtli, E., Johansen, T.: Path planning for UAVs under communication constraints using SPLAT! and MILP. J. Intell. Robot. Syst. 65(1–4), 265–282 (2012). doi:10.1007/s10846-011-9619-8

    Article  Google Scholar 

  20. Jiang, S., Xue, Y., Schmidt, D.C.: Minimum disruption service composition and recovery in mobile ad hoc networks. Comput. Netw. 53(10), 1649–1665 (2009). doi:10.1016/j.comnet.2008.10.017

    Article  MATH  Google Scholar 

  21. Vazifehdan, J., Venkatesha Prasad, R., Niemegeers, I.: On the lifetime of node-to-node communication in wireless ad hoc networks. Comput. Netw. 56(6), 1685–1709 (2012). doi:10.1016/j.comnet.2011.12.014

    Article  Google Scholar 

  22. Zussman, G., Segall, A.: Energy efficient routing in ad hoc disaster recovery networks. Ad Hoc Netw. 1(4), 405–421 (2003). doi:10.1016/S1570-8705(03)00041-6

    Article  Google Scholar 

  23. Dai, F., Wu, J.: On constructing k-connected k-dominating set in wireless ad hoc and sensor networks. J. Parallel Distr. Com. 66(7), 947–958 (2006). doi:10.1016/j.jpdc.2005.12.010

    Article  MATH  Google Scholar 

  24. Li, X., Zhao, Z., Zhu, X., Wyatt, T.: Covering models and optimization techniques for emergency response facility location and planning: a review. Math. Meth. Oper. Res. 74(3), 281–310 (2011). doi:10.1007/s00186-011-0363-4

    Article  MATH  MathSciNet  Google Scholar 

  25. Fellows, M.R., Fernau, H.: Facility location problems: a parameterized view. Discret. Appl. Math. 159(11), 1118–1130 (2011). doi:10.1016/j.dam.2011.03.021

    Article  MATH  MathSciNet  Google Scholar 

  26. Farahani, R.Z., SteadieSeifi, M., Asgari, N.: Multiple criteria facility location problems: a survey. Appl. Math. Model. 34(7), 1689–1709 (2010). doi:10.1016/j.apm.2009.10.005

    Article  MATH  MathSciNet  Google Scholar 

  27. Mladenović, N., Brimberg, J., Hansen, P., Moreno-Pérez, J.A.: The p-median problem: a survey of metaheuristic approaches. Eur. J. Oper. Res. 179(3), 927–939 (2007). doi:10.1016/j.ejor.2005.05.034

    Article  MATH  Google Scholar 

  28. Klose, A.: A branch and bound algorithm for an uncapacitated facility location problem with a side constraint. Int. Trans. Oper. Res. 5(2), 155–168 (1998)

    Article  Google Scholar 

  29. Döyen, A., Aras, N., Barbarosoğlu, G.: A two-echelon stochastic facility location model for humanitarian relief logistics. Optim. Lett. 6(6), 1123–1145 (2012). doi:10.1007/s11590-011-0421-0

    Article  MATH  MathSciNet  Google Scholar 

  30. Senne, E.L.F., Lorena, L.A.N., Pereira, M.A.: A branch-and-price approach to p-median location problems. Comput. Oper. Res. 32(6), 1655–1664 (2005)

    Article  MathSciNet  Google Scholar 

  31. Canós, M.J., Ivorra, C., Liern, V.: An exact algorithm for the fuzzy p-median problem. Eur. J. Oper. Res. 116(1), 80–86 (1999). doi:10.1016/S0377-2217(98)00330-0

    Article  MATH  Google Scholar 

  32. Kochenberger, G., Glover, F., Wang, H.: The binary unconstrained quadratic optimization problem: a unified framework for combinatorial optimization. In: Pardalos, P., Du, D.-Z., Graham, R. (eds.) Handbook on Combinatorial Optimization. Springer (2013)

  33. Wang, H., Alidaee, B., Glover, F., Kochenberger, G.: Solving group technology problems via clique partitioning. Int. J. Flex. Manuf. Syst. 18(2), 77–77 (2006)

    Article  MATH  Google Scholar 

  34. Alidaee, B., Glover, F., Kochenberger, G., Wang, H.: Solving the maximum edge weight clique problem via unconstrained quadratic programming. Eur. J. Oper. Res. 181(2), 592–597 (2007). doi:10.1016/j.ejor.2006.06.035

    Article  MATH  Google Scholar 

  35. Alidaee, B., Kochenberger, G., Lewis, K., Lewis, M., Wang, H.: A new approach for modeling and solving set packing problems. Eur. J. Oper. Res. 186(2), 504–512 (2008). doi:10.1016/j.ejor.2006.12.068

    Article  MATH  MathSciNet  Google Scholar 

  36. IBM Technical Note: Comparison of CPLEX Performance on Dual Core Machines with True Multiple Processor Machines (2012)

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Authors and Affiliations

  1. Sanchez School of Business, Texas A&M International University, Laredo, TX, 78041, USA

    Haibo Wang

  2. School of International Trade and Economics, Central University of Finance and Economics, South College Road, Haidian District, Beijing, 100081, China

    Da Huo

  3. School of Business Administration, The University of Mississippi, University, MS, 38677, USA

    Bahram Alidaee

Authors
  1. Haibo Wang
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  2. Da Huo
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  3. Bahram Alidaee
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Correspondence to Haibo Wang.

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Wang, H., Huo, D. & Alidaee, B. Position Unmanned Aerial Vehicles in the Mobile Ad Hoc Network. J Intell Robot Syst 74, 455–464 (2014). https://doi.org/10.1007/s10846-013-9939-y

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  • DOI: https://doi.org/10.1007/s10846-013-9939-y

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