Journal of Computer Science and Technology

, Volume 31, Issue 2, pp 326–349 | Cite as

Survey on Simulation for Mobile Ad-Hoc Communication for Disaster Scenarios

  • Erika RosasEmail author
  • Nicolás Hidalgo
  • Veronica Gil-Costa
  • Carolina Bonacic
  • Mauricio Marin
  • Hermes Senger
  • Luciana Arantes
  • Cesar Marcondes
  • Olivier Marin


Mobile ad-hoc communication is a demonstrated solution to mitigate the impact of infrastructure failures during large-scale disasters. A very complex issue in this domain is the design validation of software applications that support decision-making and communication during natural disasters. Such disasters are irreproducible, highly unpredictable, and impossible to scale down, and thus extensive assessments cannot be led in situ. In this context, simulation constitutes the best approach towards the testing of software solutions for natural disaster responses. The present survey reviews mobility models, ad-hoc network architectures, routing protocols and network simulators. Our aim is to provide guidelines for software developers with regards to the performance evaluation of their applications by means of simulation.


mobile ad-hoc communication simulation disaster scenario mobility model 


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  1. [1]
    Guha-Sapir D, Hoyois P, Below R. Annual disaster statistical review 2013: The numbers and trends. Technical Report, Center for Research on Epidemiology of Disasters (CRED), Institute of Health and Society, Universitè Catholique de Louvain, 2014., Jan. 2016.
  2. [2]
    ITU-T Focus Group on Disaster Relief Systems, Network Resilience and Recovery. Technical report on telecommunication and disaster mitigation. Technical Report, International Telecommunication Union (UTI), United Nations, 2014., Jan. 2016.
  3. [3]
    Conti M, Giordano S. Mobile ad hoc networking: Milestones, challenges, and new research directions. IEEE Communications Magazine, 2014, 52(1): 85–96.CrossRefGoogle Scholar
  4. [4]
    Chlamtac I, Conti M, Liu J J N. Mobile ad hoc networking: Imperatives and challenges. Ad Hoc Networks, 2003, 1(1): 13–64.CrossRefGoogle Scholar
  5. [5]
    Bruno R, Conti M, Gregori E. Mesh networks: Commodity multihop ad hoc networks. IEEE Communications Magazine, 2005, 43(3): 123–131.CrossRefGoogle Scholar
  6. [6]
    Lin Y, Chen Y, Lee S. Routing protocols in vehicular ad hoc networks: A survey and future perspectives. Journal of Information Science and Engineering, 2010, 26(3): 913–932.Google Scholar
  7. [7]
    Fall K R. A delay-tolerant network architecture for challenged internets. In Proc. the Conf. Applications, Technologies, Architectures, and Protocols for Computer Communication, August 2003, pp.27-34.Google Scholar
  8. [8]
    Yick J, Mukherjee B, Ghosal D. Wireless sensor network survey. Computer Networks, 2008, 52(12): 2292–2330.CrossRefGoogle Scholar
  9. [9]
    Nieuwenhuis K. Information systems for crisis response and management. In Lecture Notes in Computer Science 4458, Löffler J, Klann M (eds.), Springer, 2007, pp.1-8.Google Scholar
  10. [10]
    Hossmann T, Carta P, Schatzmann D, Legendre F, Gunningberg P, Rohner C. Twitter in disaster mode: Security architecture. In Proc. the Special Workshop on Internet and Disasters, December 2011, pp.7:1–7:8.Google Scholar
  11. [11]
    Zheng C, Chen L, Sicker D, Zeng X. Hybrid cellular-MANETs in practice: A microblogging system for smart devices in disaster areas. In Proc. the Int. Wireless Communications and Mobile Computing Conf., August 2014, pp.648-653.Google Scholar
  12. [12]
    Goncalves A, Silva C, Morreale P. Design of a mobile ad hoc network communication app for disaster recovery. In Proc. the 28th Int. Conf. Advanced Information Networking and Applications Workshops, May 2014, pp.121-126.Google Scholar
  13. [13]
    Bahrepour M, Meratnia N, Poel M, Taghikhaki Z, Havinga P. Distributed event detection in wireless sensor networks for disaster management. In Proc. the 2nd Int. Conf. Intelligent Networking and Collaborative Systems, November 2010, pp.507-512.Google Scholar
  14. [14]
    Ulucinar A R, Korpeoglu I, Cetin A E. A Wi-Fi cluster based wireless sensor network application and deployment for wildfire detection. International Journal of Distributed Sensor Networks, 2014, 2014: Article ID 651957.Google Scholar
  15. [15]
    Wang W, Guo L. The application of wireless sensor network technology in earthquake disaster. In Proc. the Int. Conf. Industrial Control and Electronics Engineering, August 2012, pp.52-55.Google Scholar
  16. [16]
    Fujihara A, Miwa H. Real-time disaster evacuation guidance using opportunistic communications. In Proc. the 12th IEEE/IPSJ Int. Symp. Applications and the Internet, July 2012, pp.326-331.Google Scholar
  17. [17]
    Chuang M C, Chen M C. DEEP: Density-aware emergency message extension protocol for VANETs. IEEE Trans. Wireless Communications, 2013, 12(10): 4983–4993.CrossRefGoogle Scholar
  18. [18]
    Fan C W, Su K C, Wu H M, Chang W L, Chou Y H. An effective multi-hop broadcast control mechanism for emergency alert message in VANET. In Proc. the 12th Int. Conf. ITS Telecommunications, November 2012, pp.791-795.Google Scholar
  19. [19]
    Umedu T, Urabe H, Tsukamoto J, Sato K, Higashinoz T. A MANET protocol for information gathering from disaster victims. In Proc. the 4th IEEE Int. Conf. Pervasive Computing and Communications Workshops, March 2006, p.446.Google Scholar
  20. [20]
    Wang J, Cheng Z, Nishiyama I, Zhou Y. Design of a safety confirmation system integrating wireless sensor network and smart phones for disaster. In Proc. the 6th IEEE Int. Symp. Embedded Multicore SoCs, September 2012, pp.139-143.Google Scholar
  21. [21]
    Fajardo J T B, Yasumoto K, Shibata N, Sun W, Ito M. Disaster information collection with opportunistic communication and message aggregation. Journal of Information Processing, 2014, 22(2): 106–117.CrossRefGoogle Scholar
  22. [22]
    Fajardo J, Yasumoto K, Ito M. Content-based data prioritization for fast disaster images collection in delay tolerant network. In Proc. the 7th Int. Conf. Mobile Computing and Ubiquitous Networking, January 2014, pp.147-152.Google Scholar
  23. [23]
    George S M, Zhou W, Chenji H, Won M, Lee Y O, Pazarloglou A, Stoleru R, Barooah P. DistressNet: A wireless ad hoc and sensor network architecture for situation management in disaster response. IEEE Communications Magazine, 2010, 48(3): 128–136.CrossRefGoogle Scholar
  24. [24]
    Cayirci E, Coplu T. SENDROM: Sensor networks for disaster relief operations management. Wireless Network, 2007, 13(3): 409–423.CrossRefGoogle Scholar
  25. [25]
    Radianti J, Gonzalez J, Granmo O C. Publish-subscribe smartphone sensing platform for the acute phase of a disaster: A framework for emergency management support. In Proc. the IEEE Int. Conf. Pervasive Computing and Communications Workshops, March 2014, pp.285-290.Google Scholar
  26. [26]
    Miyazaki T, Kawano R, Endo Y, Shitara D. A sensor network for surveillance of disaster-hit region. In Proc. the 4th Int. Symp. Wireless Pervasive Computing, February 2009.Google Scholar
  27. [27]
    Sardouk A, Mansouri M, Merghem-Boulahia L, Gaiti D, Rahim-Amoud R. Crisis management using MAS-based wireless sensor networks. Computer Networks, 2013, 57(1): 29–45.CrossRefGoogle Scholar
  28. [28]
    Lorincz K, Malan D J, Fulford-Jones T R, Nawoj A, Clavel A, Shnayder V, Mainland G, Welsh M, Moulton S. Sensor networks for emergency response: Challenges and opportunities. IEEE Pervasive Computing, 2004, 3(4): 16–23.CrossRefGoogle Scholar
  29. [29]
    Curtis D, Pino E J, Bailey J, Shih E,Waterman J, Vinterbo S A, Stair T O, Guttag J V, Greenes R A, Ohno-Machado L. Application of information technology: SMART — An integrated wireless system for monitoring unattended patients. Journal American Medical Informatics Association, 2008, 15(1): 44–53.CrossRefGoogle Scholar
  30. [30]
    Mart´ın-Campillo A, Mart´ı R, Yoneki E, Crowcroft J. Electronic triage tag and opportunistic networks in disasters. In Proc. the Special Workshop on Internet and Disasters, December 2011, pp.6:1–6:10.Google Scholar
  31. [31]
    Majid S, Ahmed K. Cluster-based communications system for immediate postdisaster scenario. Journal of Clinical Medicine, 2009, 4(5): 307–319.Google Scholar
  32. [32]
    Jalihal D, Koilpillai R D, Khawas P, Sampoornam S, Nagarajan S H, Takeda K, Kataoka K. A rapidly deployable disaster communications system for developing countries. In Proc. the IEEE Int. Conf. Communications, June 2012, pp.6339-6343.Google Scholar
  33. [33]
    Toral S L, Barrero F, Cort´es F, Reina D G, Marsal E, Hinojo J M, Soto M. A wireless in-door system for assisting victims and rescue equipments in a disaster management. In Proc. the 2nd Int. Conf. Intelligent Networking and Collaborative Systems, November 2010, pp.502-506.Google Scholar
  34. [34]
    Mase K, Gao J. Electric vehicle-based ad-hoc networking for large-scale disasters design principles and prototype development. In Proc. the 11th IEEE Int. Symp. Autonomous Decentralized Systems, March 2013.Google Scholar
  35. [35]
    Lien Y N, Jang H C, Tsai T C. A MANET based emergency communication and information system for catastrophic natural disasters. In Proc. the 29th IEEE Int. Conf. Distributed Computing Systems Workshops, June 2009, pp.412-417.Google Scholar
  36. [36]
    Gardner-Stephen P, Challans R, Lakeman J, Bettison A, Gardner-Stephen D, Lloyd M. The serval mesh: A platform for resilient communications in disaster & crisis. In Proc. the IEEE Global Humanitarian Technology Conference, October 2013, pp.162-166.Google Scholar
  37. [37]
    Mecella M, Angelaccio M, Krek A, Catarci T, Buttarazzi B, Dustdar S. WORKPAD: An adaptive peer-to-peer software infrastructure for supporting collaborative work of human operators in emergency/disaster scenarios. In Proc. the Int. Symp. Collaborative Technologies and Systems, May 2006, pp.173-180.Google Scholar
  38. [38]
    Lu W, Seah W K G, Peh E W C, Ge Y. Communications support for disaster recovery operations using hybrid mobile ad-hoc networks. In Proc. the 32nd IEEE Conf. Local Computer Networks, October 2007, pp.763-770.Google Scholar
  39. [39]
    Lakshmi Narayanan R G, Ibe O C. A joint network for disaster recovery and search and rescue operations. Computer Networks, 2012, 56(14): 3347–3373.CrossRefGoogle Scholar
  40. [40]
    Sun J, Zhu X, Zhang C, Fang Y. RescueMe: Location-based secure and dependable VANETs for disaster rescue. IEEE Journal on Selected Areas in Communications, 2011, 29(3): 659–669.CrossRefGoogle Scholar
  41. [41]
    Suzuki H, Kaneko Y, Mase K, Yamazaki S, Makino H. An ad hoc network in the sky, SKYMESH, for large-scale disaster recovery. In Proc. the 64th IEEE Vehicular Technology Conference, September 2006.Google Scholar
  42. [42]
    Shibata Y, Sato Y, Ogasawara N, Chiba G, Takahata K. A new ballooned wireless mesh network system for disaster use. In Proc. the 23rd IEEE Int. Conf. Advanced Information Networking and Applications, May 2009, pp.816-821.Google Scholar
  43. [43]
    Aziz N, Aziz K. Managing disaster with wireless sensor networks. In Proc. the 13th Int. Conf. Advanced Communication Technology, February 2011, pp.202-207.Google Scholar
  44. [44]
    Vieweg S, Hughes A L, Starbird K, Palen L. Microblogging during two natural hazards events: What twitter may contribute to situational awareness. In Proc. the SIGCHI Conference on Human Factors in Computing Systems, April 2010, pp.1079-1088.Google Scholar
  45. [45]
    Camp T, Boleng J, Davies V. A survey of mobility models for ad hoc network research. Wireless Communication and Mobile Computing, 2002, 2(5): 483–502.CrossRefGoogle Scholar
  46. [46]
    Aschenbruck N, Gerhards-Padilla E, Martini P. Modeling mobility in disaster area scenarios. Performance Evaluation, 2009, 66(12): 773–790.CrossRefGoogle Scholar
  47. [47]
    Nelson S C, Harris A F, Kravets R. Event-driven, role-based mobility in disaster recovery networks. In Proc. the 2nd ACM Workshop Challenged Networks, September 2007, pp.27-34.Google Scholar
  48. [48]
    Huang Y, He W, Nahrstedt K, Lee W. CORPS: Eventdriven mobility model for first responders in incident scene. In Proc. the IEEE Military Communications Conf., November 2008.Google Scholar
  49. [49]
    Uddin M, Nicol D, Abdelzaher T, Kravets R. A postdisaster mobility model for delay tolerant networking. In Proc. the Winter Simulation Conference, December 2009, pp.2785-2796.Google Scholar
  50. [50]
    Pomportes S, Tomasik J, Vèque V. Ad hoc network in a disaster area: A composite mobility model and its evaluation. In Proc. the Int. Conf. Advanced Technologies for Communications, October 2010, pp.17-22.Google Scholar
  51. [51]
    Saha S, Sushovan, Sheldekar A, Joseph C R, Mukherjee A, Nandi S. Post disaster management using delay tolerant network. In Communications in Computer and Information Science 162, ¨Ozcan A, Zizka J, Nagamalai D (eds.), Springer, 2011, pp.170-184.Google Scholar
  52. [52]
    Costantini D, Munch M, Leonardi A, Rocha V, Mogre P S, Steinmetz R. Rolebased urban post-disaster mobility model for search and rescue operations. In Proc. the 37th IEEE Conf. Local Computer Networks Workshops, October 2012, pp.900-907.Google Scholar
  53. [53]
    Conceição L, Curado M. Modelling mobility based on human behaviour in disaster areas. In Lecture Notes in Computer Science 7889, Tsaoussidis V, Kassler A, Koucheryavy Y, Mellouk A (eds.), Springer, 2013, pp.56-69.Google Scholar
  54. [54]
    Keränen A, Ott J, Kärkkäinen T. The ONE simulator for DTN protocol evaluation. In Proc. the 2nd Int. Conf. Simulation Tools and Techniques, March 2009, pp.55:1–55:10.Google Scholar
  55. [55]
    Rhee I, Shin M, Hong S, Lee K, Kim S J, Chong S. On the levy-walk nature of human mobility. IEEE/ACM Trans. Networking, 2011, 19(3): 630–643.CrossRefGoogle Scholar
  56. [56]
    Johansson P, Larsson T, Hedman N, Mielczarek B, Degermark M. Scenario-based performance analysis of routing protocols for mobile ad-hoc networks. In Proc. the 5th Annu. ACM/IEEE Int. Conf. Mobile Computing and Networking, August 1999, pp.195-206.Google Scholar
  57. [57]
    Reina D G, Toral S, Barrero F, Bessis N, Asimakopoulou E. Evaluation of ad hoc networks in disaster scenarios. In Proc. the 3rd Int. Conf. Intelligent Networking and Collaborative Systems, November 2011, pp.759-764.Google Scholar
  58. [58]
    Wister M A, Pancardo P, Acosta F D, Arias-Torres D. Performance evaluation of AODV and DYMO as a platform for rescue task applications in MANETs. In Proc. the IEEE Workshops Int. Conf. Advanced Information Networking and Applications, March 2011, pp.670-675.Google Scholar
  59. [59]
    Raffelsberger C, Hellwagner H. Evaluation of MANET routing protocols in a realistic emergency response scenario. In Proc. the 10th Workshop Intelligent Solutions in Embedded Systems, July 2012, pp.88-92.Google Scholar
  60. [60]
    Macone D, Oddi G, Pietrabissa A. MQ-Routing: Mobility-,GPS- and energy-aware routing protocol in MANETs for disaster relief scenarios. Ad Hoc Networks, 2013, 11(3): 861–878.CrossRefGoogle Scholar
  61. [61]
    MartìN-Campillo A, Crowcroft J, Yoneki E, Martì R. Evaluating opportunistic networks in disaster scenarios. Journal of Network and Computer Applications, 2013, 36(2): 870–880.CrossRefGoogle Scholar
  62. [62]
    Uddin M, Ahmadi H, Abdelzaher T, Kravets R. A lowenergy, multi-copy inter-contact routing protocol for disaster response networks. In Proc. the 6th Annu. IEEE Conf. Sensor, Mesh and Ad Hoc Communications and Networks, June 2009, pp.637-645.Google Scholar
  63. [63]
    MartìN-Campillo A, Martì R. Energy-efficient forwarding mechanism for wireless opportunistic networks in emergency scenarios. Computer Communications, 2012, 35(14): 1715–1724.CrossRefGoogle Scholar
  64. [64]
    Takahashi A, Nishiyama H, Kato N. Fairness issue in message delivery in delay- and disruption-tolerant networks for disaster areas. In Proc. the Int. Conf. Computing, Networking and Communications, January 2013, pp.890-894.Google Scholar
  65. [65]
    Bhattacharjee S, Roy S, Bandyopadhyay S. Exploring an energy-efficient DTN framework supporting disaster management services in post disaster relief operation. Wireless Networks, 2015, 21(3): 1033–1046.CrossRefGoogle Scholar
  66. [66]
    Perkins C E, Bhagwat P. Highly dynamic destinationsequenced distance vector routing (DSDV) for mobile computers. ACM SIGCOMM Computer Communication Review, 1994, 24(4): 234–244.CrossRefGoogle Scholar
  67. [67]
    Perkins C E, Royer E M. Ad-hoc ondemand distance vector routing. In Proc. the 2nd IEEE Workshop Mobile Computing Systems and Applications, February 1999, pp.90-100.Google Scholar
  68. [68]
    Johnson D, Maltz D. Dynamic source routing in ad hoc wireless networks. In The Kluwer International Series in Engineering and Computer Science 353, Imielinski T, Korth H (eds.), Springer, 1996, pp.153-181.Google Scholar
  69. [69]
    Issariyakul T, Hossain E. Introduction to Network Simulator NS2 (1st edition). Springer, 2008.Google Scholar
  70. [70]
    Billington J, Yuan C. On modelling and analysing the dynamic MANET on-demand (DYMO) routing protocol. In Lecture Notes in Computer Science 5800, Jensen K, Billington J, Koutny M (eds.), Springer, 2009, pp.98-126.Google Scholar
  71. [71]
    Marina M K, Das S R. Ad hoc on-demand multipath distance vector routing. ACM SIGMOBILE Mobile Computing and Communications Review, 2002, 6(3): 92–93.CrossRefGoogle Scholar
  72. [72]
    Aschenbruck N, Ernst R, Gerhards-Padilla E, Schwamborn M. BonnMotion: A mobility scenario generation and analysis tool. In Proc. the 3rd Int. Conf. Simulation Tools and Techniques, March 2010, pp.51:1–51:10.Google Scholar
  73. [73]
    Jacquet P, Muhlethaler P, Clausen T, Laouiti A, Qayyum A, Viennot L. Optimized link state routing protocol for ad hoc networks. In Proc. the IEEE Int. Conf. Technology for the 21st Century, December 2001, pp.62-68.Google Scholar
  74. [74]
    Klein A, Braun L, Oehlmann F. Performance study of the better approach to mobile adhoc networking (B.A.T.M.A.N.) protocol in the context of asymmetric links. In Proc. the IEEE Int. Symp. a World of Wireless, Mobile and Multimedia Networks, June 2012.Google Scholar
  75. [75]
    Vahdat A, Becker D. Epidemic routing for partially connected ad hoc networks. Technical Report, Duke University, July 2000.Google Scholar
  76. [76]
    Lindgren A, Doria A, Schelén O. Probabilistic routing in intermittently connected networks. ACM SIGMOBILE Mobile Computing and Communication Review, 2003, 7(3): 19–20.CrossRefGoogle Scholar
  77. [77]
    Spyropoulos T, Psounis K, Raghavendra C S. Spray and Wait: An efficient routing scheme for intermittently connected mobile networks. In Proc. the ACM SIGCOMM Workshop on Delay-Tolerant Networking, August 2005, pp.252-259.Google Scholar
  78. [78]
    Burgess J, Gallagher B, Jensen D, Levine B. MaxProp: Routing for vehicle-based disruption-tolerant networks. In Proc. the 25th IEEE Int. Conf. Computer Communications, April 2006.Google Scholar
  79. [79]
    Spyropoulos T, Psounis K, Raghavendra C. Spray and Focus: Efficient mobility-assisted routing for heterogeneous and correlated mobility. In Proc. the 5th Annu. IEEE Int. Conf. Pervasive Computing and Communications Workshops, March 2007, pp.79-85.Google Scholar
  80. [80]
    Martì R, Robles S, Martìn-Campillo A, Cucurull J. Providing early resource allocation during emergencies: The mobile triage tag. Journal of Network and Computer Applicactions, 2009, 32(6): 1167–1182.CrossRefGoogle Scholar
  81. [81]
    Raffelsberger C, Hellwagner H. Overview of hybrid MANET-DTN networking and its potential for emergency response operations. Electronic Communications of the EASST, 2013, 56.Google Scholar
  82. [82]
    Kawamoto Y, Nishiyama H, Kato N. Toward terminal-toterminal communication networks: A hybrid MANET and DTN approach. In Proc. the 8th Int. Workshop Computer Aided Modeling and Design of Communication Links and Networks, September 2013, pp.228-232.Google Scholar
  83. [83]
    Nishiyama H, Ito M, Kato N. Relay-by-smartphone: Realizing multihop device-to-device communications. IEEE Communications Magazine, 2014, 52(4): 56–65.CrossRefGoogle Scholar
  84. [84]
    Mangharam R, Weller D S, Stancil D D, Rajkumar R, Parikh J S. GrooveSim: A topography-accurate simulator for geographic routing in vehicular networks. In Proc. the 2nd ACM Int. Workshop on Vehicular Ad Hoc Networks, Sept. 2005, pp.59-68.Google Scholar
  85. [85]
    Fasolo E, Zanella A, Zorzi M. An effective broadcast scheme for alert message propagation in vehicular ad hoc networks. In Proc. the IEEE Int. Conf. Communications, June 2006, pp.3960-3965.Google Scholar
  86. [86]
    Korkmaz G, Ekici E, Özgüner F, ÖzgünerÜ. Urban multihop broadcast protocol for inter-vehicle communication systems. In Proc. the 1st ACM Int. Workshop on Vehicular Ad Hoc Networks, 2004, pp.76-85.Google Scholar
  87. [87]
    Zorzi M, Rao R R. Geographic random forwarding (GeRaF) for ad hoc and sensor networks: Multihop performance. IEEE Trans. Mobile Computing, 2003, 2(4): 337–348.CrossRefGoogle Scholar
  88. [88]
    Peng J, Cheng L. A distributed MAC scheme for emergency message dissemination in vehicular ad hoc networks. IEEE Trans. Vehicular Technology, 2007, 56(6): 3300–3308.CrossRefGoogle Scholar
  89. [89]
    Bi Y, Zhao H, Shen X. A directional broadcast protocol for emergency message exchange in inter-vehicle communications. In Proc. the IEEE Int. Conf. Communications, June 2009.Google Scholar
  90. [90]
    Suriyapaiboonwattana K, Pornavalai C, Chakraborty G. An adaptive alert message dissemination protocol for VANET to improve road safety. In Proc. the IEEE Int. Conf. Fuzzy Systems, August 2009, pp.1639-1644.Google Scholar
  91. [91]
    Lee D, Bai S, Kim T, Jung J. Enhanced selective forwarding scheme for alert message propagation in VANETs. In Proc. the Int. Conf. Information Science and Applications, April 2010.Google Scholar
  92. [92]
    Li M, Zeng K, Lou W. Opportunistic broadcast of eventdriven warning messages in vehicular ad hoc networks with lossy links. Computer Networks, 2011, 55(10): 2443–2464.CrossRefGoogle Scholar
  93. [93]
    Lee J F, Wang C S, Chuang M C. Fast and reliable emergency message dissemination mechanism in vehicular ad hoc networks. In Proc. the IEEE Wireless Communications and Networking Conf., April 2010.Google Scholar
  94. [94]
    Javed M A, Ngo D T, Khan J Y. A multihop broadcast protocol design for emergency warning notification in highway VANETs. EURASIP Journal on Wireless Communications and Networking, 2014, 2014: 179.CrossRefGoogle Scholar
  95. [95]
    Saha S, Matsumoto M. A framework for data collection and wireless sensor network protocol for disaster management. In Proc. the 2nd Int. Conf. Communication Systems Software and Middleware, January 2007.Google Scholar
  96. [96]
    Gu S, Yue Y, Maple C, Wu C, Liu B. Challenges in mobile localisation in wireless sensor networks for disaster scenarios. In Proc. the 19th Int. Conf. Automation and Computing, September 2013.Google Scholar
  97. [97]
    Chen D, Liu Z, Wang L, Dou M, Chen J, Li H. Natural disaster monitoring with wireless sensor networks: A case study of data-intensive applications upon lowcost scalable systems. Mobile Networks and Applications, 2013, 18(5): 651–663.CrossRefGoogle Scholar
  98. [98]
    Yu L, Wang N, Meng X. Real-time forest fire detection with wireless sensor networks. In Proc. the Int. Conf. Wireless Communications, Networking and Mobile Computing, September 2005, pp.1214-1217.Google Scholar
  99. [99]
    Fujiwara T, Makie H, Watanabe T. A framework for data collection system with sensor networks in disaster circumstances. In Proc. the Int. Workshop on Wireless Ad-Hoc Networks, May 31-June 3, 2004, pp.94-98.Google Scholar
  100. [100]
    Fantacci R, Marabissi D, Tarchi D. A novel communication infrastructure for emergency management: The In.Sy.Eme. vision. Wireless Communications and Mobile Computing, 2010, 10(12): 1672–1681.CrossRefGoogle Scholar
  101. [101]
    Dilmaghani R B, Rao R R. Hybrid wireless mesh network with application to emergency scenarios. Journal of Software, 2008, 3(2): 52–60.CrossRefGoogle Scholar
  102. [102]
    Suzuki T, Shibata Y. Autonomous power supplied wireless mesh network for disaster information system. In Proc. the Int. Conf. Broadband, Wireless Computing, Communication and Applications, November 2010, pp.88-93.Google Scholar
  103. [103]
    Ngo T, Nishiyama H, Kato N, Shimizu Y, Mizuno K, Kumagai T. On the throughput evaluation of wireless mesh network deployed in disaster areas. In Proc. the Int. Conf. Computing, Networking and Communications, January 2013, pp.413-417.Google Scholar
  104. [104]
    Li M, Nishiyama H, Owada Y, Hamaguchi K. On energy efficient scheduling and load distribution based on renewable energy for wireless mesh network in disaster area. In Proc. the 13th IEEE Int. Conf. Trust, Security and Privacy in Computing and Communications, September 2014, pp.465-472.Google Scholar
  105. [105]
    Fouda M, Nishiyama H, Miura R, Kato N. On efficient traffic distribution for disaster area communication using wireless mesh networks. Wireless Personal Communications, 2014, 74(4): 1311–1327.CrossRefGoogle Scholar
  106. [106]
    Sommer C, German R, Dressler F. Bidirectionally coupled network and road traffic simulation for improved IVC analysis. IEEE Trans. Mobile Computing, 2011, 10(1): 3–15.CrossRefGoogle Scholar
  107. [107]
    Spyropoulos T, Rais R, Turletti T, Obraczka K, Vasilakos A. Routing for disruption tolerant networks: Taxonomy and design. Wireless Networks, 2010, 16(8): 2349–2370.CrossRefGoogle Scholar
  108. [108]
    Gil-Costa V, Marín M, Inostrosa-Psijas A, Lobos J, Bonacic C. Modelling search engines performance using coloured Petri nets. Fundamenta Informaticae, 2014, 131(1): 139–166.Google Scholar
  109. [109]
    Casanova H, Legrand A, Quinson M. SimGrid: A generic framework for large-scale distributed experiments. In Proc. the 10th Int. Conf. Computer Modeling and Simulation, April 2008, pp.126-131.Google Scholar
  110. [110]
    Grasic S, Lindgren A. An analysis of evaluation practices for DTN routing protocols. In Proc. the 7th ACM Int. Workshop Challenged Networks, August 2012, pp.57-64.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Erika Rosas
    • 1
    Email author
  • Nicolás Hidalgo
    • 1
  • Veronica Gil-Costa
    • 2
  • Carolina Bonacic
    • 1
  • Mauricio Marin
    • 1
  • Hermes Senger
    • 3
  • Luciana Arantes
    • 4
  • Cesar Marcondes
    • 3
  • Olivier Marin
    • 5
  1. 1.Department of Informatics EngineeringUniversity of SantiagoSantiagoChile
  2. 2.National Council of Scientific and Technical ResearchNational University of San LuisSan LuisArgentina
  3. 3.Department of Computer ScienceFederal University of São CarlosSão CarlosBrazil
  4. 4.Laboratoire d’Informaique de Paris 6University of Pierre and Marie Currie, Sorbonne Universités, CNRS, INRIAParisFrance
  5. 5.Engineering and Computer ScienceNew York University ShanghaiShanghaiChina

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