Abstract

Communication network plays a big part for us in our lives. It is needed to perform daily tasks, access information and communicate each other anytime, anywhere and from any device. Nowadays, the communication network is a priority when it comes to a disaster scenario such as earthquakes, typhoons, tsunamis etc. The fixed communication network may be partially or fully destroyed or may be overloaded due to the aftermath of the disaster. It is crucial for rescue teams to establish a disaster recovery network for them to communicate with each other during their Search and Rescue (SAR) operations and mission critical. The disaster recovery network must be established within a short period to ensure the smooth operation of the rescue teams. Mobile Ad-Hoc Network (MANET) is a favourable approach for recovering the communication network as it can be deployed rapidly after the disaster rather than fixed communication network. MANET is an infrastructure-less network that can be deployed instantly and maintained easily. MANET can be used to address the issue of increasing communication requests, especially for data, speech, and video stream transmission. Due to limitations on scalability, repeatability, speed and cost, software simulations are often chosen instead of field-test experiments to verify the characteristics of designated topology control and protocols used in MANET for the disaster area scenario. The behaviour of the protocols used in MANET is highly affected by nodes’ mobility model. The mobility model shows the nodes’ movement and should be able to resemble the real-life situation for the designated scenario. Most of existing mobility models, such as random-based movements show unrealistic movement in concerns with the rescue teams’ movement as they will not move randomly during their SAR operations. Instead, their movements are influenced by existing obstacles such as walls, trees and others. This paper reviews the existing mobility models used for investigating the movement of the rescue entities in the disaster area scenario. Some of other resilient disaster communication networks aside from MANET and MANET simulation tools were also reviewed. The main aim of this paper is to find the ideal mobility model that can realistically describe the movement of the rescue entities in the disaster area scenario. A comparative analysis, which includes the approaches and limitations on the related works was presented. By the end of this paper, a conclusion is drawn and suggestions aspects for future researches were stated.

Keyword

Disaster area network, MANET, Mobility model, Post-disaster, Node mobility, Network performance.

Cite this article

Mahiddin NA, Affandi FF, Mohamad Z

Refference

[1][1]Aschenbruck N, Gerhards-padilla E, Martini P. Modeling mobility in disaster area scenarios. Performance Evaluation. 2009; 66(12):773-90.

[2][2]Mahiddin NA, Sarkar NI, Cusack B. An internet access solution: MANET routing and a gateway selection approach for disaster scenarios. The Review of Socionetwork Strategies. 2017; 11:47-64.

[3][3]Hoebeke J, Moerman I, Dhoedt B, Demeester P. An overview of mobile ad hoc networks: applications and challenges. Journal-Communications Network. 2004; 3(3):60-6.

[4][4]Mahiddin NA, Sarkar NI. An efficient gateway routing scheme for disaster recovery scenario. In international conference on information networking 2019 (pp. 204-9). IEEE.

[5][5]Aschenbruck N, Gerhards-Padilla E, Martini P. A survey on mobility models for performance analysis in tactical mobile networks. Journal of Telecommunications and Information Technology. 2008:54-61.

[6][6]Aschenbruck N, Ernst R, Gerhards-padilla E, Schwamborn M. Bonnmotion: a mobility scenario generation and analysis tool. In proceedings of the international ICST conference on simulation tools and techniques 2010 (pp. 1-10).

[7][7]Boldrini C, Conti M, Passarella A. Users mobility models for opportunistic networks: the role of physical locations. Proceddings of IEEE WRECOM. 2007.

[8][8]Nelson SC, Harris III AF, Kravets R. Event-driven, role-based mobility in disaster recovery networks. In proceedings of the second ACM workshop on challenged networks 2007 (pp. 27-34).

[9][9]Rollo M, Komenda A. Mobility model for tactical networks. In international conference on industrial applications of holonic and multi-agent systems 2009 (pp. 254-65). Springer, Berlin, Heidelberg.

[10][10]Papageorgiou C, Birkos K, Dagiuklas T, Kotsopoulos S. Simulating mission critical mobile ad hoc networks. In proceedings of the 4th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks 2009 (pp. 143-50).

[11][11]Pomportes S, Tomasik J, Vèque V. Ad hoc network in a disaster area: a composite mobility model and its evaluation. In the international conference on advanced technologies for communications 2010 (pp. 17-22). IEEE.

[12][12]Reina DG, Toral SL, Barrero F, Bessis N, Asimakopoulou E. Evaluation of ad hoc networks in disaster scenarios. In third international conference on intelligent networking and collaborative systems 2011 (pp. 759-64). IEEE.

[13][13]Raffelsberger C, Hellwagner H. Evaluation of MANET routing protocols in a realistic emergency response scenario. In proceedings of the 10th international workshop on intelligent solutions in embedded systems 2012 (pp. 88-92). IEEE.

[14][14]Conceição L, Curado M. Modelling mobility based on human behaviour in disaster areas. In international conference on wired/wireless internet communication 2013 (pp. 56-69). Springer, Berlin, Heidelberg.

[15][15]Martín-campillo A, Crowcroft J, Yoneki E, Martí R. Evaluating opportunistic networks in disaster scenarios. Journal of Network and Computer Applications. 2013; 36(2):870-80.

[16][16]Reina DG, Toral SL, Leon-Coca JM, Barrero F, Bessis N, Asimakopoulou E. An evolutionary computational approach for optimizing broadcasting in disaster response scenarios. In international conference on innovative mobile and internet services in ubiquitous computing 2013 (pp. 94-100). IEEE.

[17][17]Reina DG, Toral SL, Barrero F, Bessis N, Asimakopoulou E. Modelling and assessing ad hoc networks in disaster scenarios. Journal of Ambient Intelligence and Humanized Computing. 2013; 4:571-9.

[18][18]Ebenezer J. A mobility model for MANET in large scale disaster scenarios. In 17th international conference on computer and information technology 2014 (pp. 59-64). IEEE.

[19][19]Reina DG, León-coca JM, Toral SL, Asimakopoulou E, Barrero F, et al. Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios. Soft Computing. 2014; 18:1745-56.

[20][20]Arbia DB, Alam MM, Attia R, Hamida EB. Behavior of wireless body-to-body networks routing strategies for public protection and disaster relief. In international conference on wireless and mobile computing, networking and communications 2015 (pp. 117-24). IEEE.

[21][21]Wang X, Li D, Zhang X, Tang H, Zhang G. A catastrophic intensity-based rescue mobility model for earthquake emergency rescue scenario. International Journal of Simulation--Systems, Science & Technology. 2016; 17(38):1-6.

[22][22]Gondaliya N , Atiquzzaman M. RTTMM: role based 3-tier mobility model for evaluation of delay tolerant routing protocols in post disaster situation. In international conference on internet of things and big data 2016 (pp. 11-20). SCITEPRESS.

[23][23]Stute M, Maass M, Schons T, Hollick M. Reverse engineering human mobility in large-scale natural disasters. In proceedings of the ACM international conference on modelling, analysis and simulation of wireless and mobile systems 2017 (pp. 219-26).

[24][24]Sani AM, Newaz SS, Wani SM, Wan AT, Jahan S. TCP performance evaluation under manet routing protocols in disaster recovery scenario. In international conference on advances in electrical engineering 2017 (pp. 389-94). IEEE.

[25][25]Al-shehri SM, Loskot P, Numanoğlu T, Mert M. Comparing tactical and commercial MANETs design strategies and performance evaluations. In military communications conference 2017 (pp. 599-604). IEEE.

[26][26]Kim BS, Kim KI, Roh B, Choi H. A new routing protocol for UAV relayed tactical mobile ad hoc networks. In wireless telecommunications symposium 2018 (pp. 1-4). IEEE.

[27][27]Kim N, Na W, Cho S. Dual-channel-based mobile ad hoc network routing technique for indoor disaster environment. IEEE Access. 2020; 8:126713-24.

[28][28]Younes OS, Albalawi UA. Analysis of route stability in mobile multihop networks under random waypoint mobility. IEEE Access. 2020; 8:168121-36.

[29][29]Sakano T, Fadlullah ZM, Ngo T, Nishiyama H, Nakazawa M, Adachi F, et al. Disaster-resilient networking: a new vision based on movable and deployable resource units. IEEE Network. 2013; 27(4):40-6.

[30][30]Sakano T, Kotabe S, Komukai T. Overview of movable and deployable ICT resource unit architecture. NTT Technical Review. 2015; 13(5):1-6.

[31][31]Sakano T, Kotabe S, Komukai T, Kumagai T, Shimizu Y, Takahara A, et al. Bringing movable and deployable networks to disaster areas: development and field test of MDRU. IEEE Network. 2016; 30(1):86-91.

[32][32]Pervez F, Qadir J, Khalil M, Yaqoob T, Ashraf U, Younis S. Wireless technologies for emergency response: a comprehensive review and some guidelines. IEEE Access. 2018; 6:71814-38.

[33][33]Höchst J, Baumgärtner L, Kuntke F, Penning A, Sterz A, Freisleben B. Lora-based device-to-device smartphone communication for crisis scenarios. In proceedings of the international conference on information systems for crisis response and management 2020.

[34][34]Nik WN, Mohamad Z, Zakaria AH, Azlan AA. i-BeeHOME: an intelligent stingless honey beehives monitoring tool based on TOPSIS method by implementing LoRaWan–a preliminary study. In computational science and technology 2020 (pp. 669-76). Springer, Singapore.

[35][35]Sciullo L, Trotta A, Di FM. Design and performance evaluation of a LoRa-based mobile emergency management system. Ad Hoc Networks. 2020.

[36][36]Khan MA, Safi A, Qureshi IM, Khan IU. Flying ad-hoc networks (FANETs): A review of communication architectures, and routing protocols. In first international conference on latest trends in electrical engineering and computing technologies 2017 (pp. 1-9). IEEE.

[37][37]Bongsu RHR., Mohammed A., and Mohamed MA. Recent trends in channel assignment algorithms for multi-radio multi-channel in wireless mesh network. International Journal of Recent Technology and Engineering. 2019; 7(5S4):656-9. IJRTE.

[38][38]Molla DM, Badis H, Desta AA, George L, Berbineau M. SDR-based reliable and resilient wireless network for disaster rescue operations. In international conference on information and communication technologies for disaster management 2019 (pp. 1-7). IEEE.

[39][39]Solpico D, Tan MI, Manalansan EJ, Zagala FA, Leceta JA, Lanuza DF, et al. Application of the V-HUB standard using LoRa beacons, mobile cloud, uavs, and dtn for disaster-resilient communications. In IEEE global humanitarian technology conference 2019 (pp. 1-8). IEEE.

[40][40]Qiu J, Grace D, Ding G, Zakaria MD, Wu Q. Air-ground heterogeneous networks for 5G and beyond via integrating high and low altitude platforms. IEEE Wireless Communications. 2019; 26(6):140-8.

[41][41]Manaseer S and Alawneh A. A new mobility model for Ad Hoc networks in disaster recovery areas. International Journal of Online Engineering. 2017; 13(6):113-20.

[42][42]Camp T, Boleng J, Davies V. A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing. 2002; 2(5):483-502.

[43][43]Rhee I, Shin M, Hong S, Lee K, Kim SJ, Chong S. On the levy-walk nature of human mobility. IEEE/ACM Transactions on Networking. 2011; 19(3):630-43.

[44][44]Kumar S, Sharma SC, Suman B. Mobility metrics based classification & analysis of mobility model for tactical network. International Journal of Next-Generation Networks. 2010; 2(3):39-51.

[45][45]Patle VK, Kumar S. Evaluation of mobility model with MANET routing protocols. International Journal of Computer Applications. 2016; 152(8):8-12.

[46][46]https://www.isi.edu/nsnam/ns/. Accessed 10 April 2021.

[47][47]https://www.nsnam.org/. Accessed 10 April 2021.

[48][48]Dorathy I, Chandrasekaran M. Simulation tools for mobile ad hoc networks: a survey. Journal of Applied Research and Technology. 2018; 16(5):437-45.

[49][49]https://www.scalable-networks.com/products/qualnet-network-simulation-software-tool/. Accessed 10 April 2021.

[50][50]https://omnetpp.org/intro/. Accessed 10 April 2021.

[51][51]Keränen A, Ott J, Kärkkäinen T. The ONE simulator for DTN protocol evaluation. In proceedings of the international conference on simulation tools and techniques 2009 (pp. 1-10).

[52][52]https://www.tetcos.com/. Accessed 20 February 2021.

[53][53]http://jist.ece.cornell.edu/. Accessed 20 February 2021.

[54][54]https://www.physiome.org/jsim/. Accessed 20 February 2021.