Abstract

Communication and coordination amongst rescue teams in post-disaster areas (DAs) are essential during search and rescue (SAR) operations. The physical infrastructure network may be partially or fully damaged due to the disaster's nature, hindering communication between rescue teams and delaying the broadcast of information. This paper aims to enhance the quality of services in post-DA by addressing the difficulties of network communication caused by the obstacles and tactical zones, and unrealistic node movement due to the mobility speed of the disaster rescue teams (DRT). Hence, a DRT mobility model is proposed and implemented to simulate DRTs’ movement realistically in post-DA. This study modifies the previous DA model by separating the incident location (IL) into four risk-based zones based on catastrophic intensity (CI) values using network simulator 2 (NS2). The network performance of the DRT model outperformed the DA model, achieving a 2.5% improvement in throughput, a 5.4% improvement in PDR, an 83% reduction in overhead, a 5.4% improvement in packet loss rate, and a 0.3% improvement in E2E delay. As a result of improved routing protocol efficiency shown by the higher value of packet delivery ratio (PDR), there is less packet congestion and communication overhead between the rescue teams. This result shows that the proposed method is better in the effectiveness of the communication for the rescue teams to be applied in mobile ad hoc network (MANET). Recommendations for future work are outlined for this study to be extended by considering the movement of the victims in a post-DA.

Keyword

Mobile Ad-hoc network, Mobility model, Post-DA, Nodes mobility, Performance evaluation.

Cite this article

Affandi FF, Mahiddin NA, Mohamad Z.DRT mobility model for search and rescue operations based on catastrophic intensity to improve the quality of services. International Journal of Advanced Technology and Engineering Exploration. 2024;11(112):332-353. DOI:10.19101/IJATEE.2023.10102419

Refference

[1]Zakaria A, Saman M, Nor A, Hassan H. Finding shortest routing solution in mobile ad hoc networks using firefly algorithm and queuing network analysis. Jurnal Teknologi. 2015; 77(18):17-22.

[2]Kniess J, Petri M, Parpinelli RS. An energy-efficient bio-scheduling model for emergency networks. In wireless communications and networking conference 2021 (pp. 1-6). IEEE.

[3]Trono EM, Fujimoto M, Suwa H, Arakawa Y, Yasumoto K. Generating pedestrian maps of disaster areas through ad-hoc deployment of computing resources across a DTN. Computer Communications. 2017; 100:129-42.

[4]Hazra K, Shah VK, Silvestri S, Aggarwal V, Das SK, Nandi S, et al. Designing efficient communication infrastructure in post-disaster situations with limited availability of network resources. Computer Communications. 2020; 164:54-68.

[5]Lavanya P, Ch SM. Routing in mobile ad-hoc networks-a comprehensive research. In first international conference on electrical, electronics, information and communication technologies 2022 (pp. 1-8). IEEE.

[6]Affandi FF, Mahiddin NA, Hashim AD. MANET performance evaluation for DSDV, DSR and ZRP. International Journal of Advanced Technology and Engineering Exploration. 2023; 10(99):244-56.

[7]Mahiddin NA, Sarkar NI, Cusack B. Gateway load balancing and routing selection scheme of MANET in disaster scenario. In 2nd Asia-Pacific world congress on computer science and engineering 2015 (pp. 1-7). IEEE.

[8]Bongsu RH, Hamid NA, Rose AN, Subramaniam S. Enhanced packet scheduling algorithm for multihop wireless LANs. International Journal of Advanced Science and Technology. 2012; 49:63-72.

[9]Soomro AM, Fudzee MF, Hussain M, Saim HM, Zaman G, Atta-ur-rahman, et al. Comparative review of routing protocols in MANET for future research in disaster management. Journal of Communications. 2022; 17(9):734-44.

[10]Mostafa SA, Mustapha A, Ramli AA, Jubair MA, Hassan MH, Abbas AH. Comparative analysis to the performance of three mobile ad-hoc network routing protocols in time-critical events of search and rescue missions. In advances in simulation and digital human modeling: proceedings of the virtual conferences on human factors and simulation, and digital human modeling and applied optimization, USA 2021 (pp. 117-23). Springer International Publishing.

[11]Aschenbruck N, Gerhards-padilla E, Gerharz M, Frank M, Martini P. Modelling mobility in disaster area scenarios. In proceedings of the 10th symposium on modeling, analysis, and simulation of wireless and mobile systems 2007 (pp. 4-12). ACM.

[12]He D, Sun W, Shi L. The realistic 3D group mobility model based on spiral line for aerial backbone network. IEEE Transactions on Vehicular Technology. 2021; 70(4):3817-30.

[13]Wang X, Guo C. A four-quadrant mobility model-based routing protocol for post-earthquake emergency communication network. EURASIP Journal on Wireless Communications and Networking. 2021; 2021(1):1-29.

[14]Azmi IN, Yussoff YM, Thamrin NM, Zaman FH, Tahir NM. Flying ad hoc coverage area mobility model for post-disaster area based on two drones. In international conference on computing, networking and communications 2023 (pp. 672-6). IEEE.

[15]Ganazhapa AF, Palmieri N, Pushug MI. Drones for connectivity support in disaster recovery. In unmanned systems technology XXII 2020 (pp. 150-8). SPIE.

[16]Godbole V. Performance analysis of AntNet-LA protocol for ad-hoc networks based on disaster area mobility model. REV Journal on Electronics and Communications. 2013; 3(1-2):28-39.

[17]Trono EM, Fujimoto M, Suwa H, Arakawa Y, Takai M, Yasumoto K. Disaster area mapping using spatially-distributed computing nodes across a DTN. In international conference on pervasive computing and communication workshops (PerCom Workshops) 2016 (pp. 1-6). IEEE.

[18]Guo W, Huang X. On coverage and capacity for disaster area wireless networks using mobile relays. EURASIP Journal on Wireless Communications and Networking. 2009; 2009:1-7.

[19]Guo W, Huang X. Mobility model and relay management for disaster area wireless networks. In international conference on wireless algorithms, systems, and applications 2008 (pp. 274-85). Springer Berlin Heidelberg.

[20]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.

[21]Shimizu Y, Suzuki Y, Sasazawa R, Kawamoto Y, Nishiyama H, Kato N, et al. Development of movable and deployable ICT resource unit (MDRU) and its overseas activities. Journal of Disaster Research. 2019; 14(2):363-74.

[22]Aschenbruck N, Ernst R, Gerhards-padilla E, Schwamborn M. Bonnmotion: a mobility scenario generation and analysis tool. In 3rd international ICST conference on simulation tools and techniques 2010 (pp. 1-10).

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

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

[25]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.

[26]Conceição L, Curado M. Modelling mobility based on obstacle-aware human behaviour in disaster areas. Wireless Personal Communications. 2015; 82:451-72.

[27]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.

[28]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.

[29]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.

[30]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 seventh international conference on innovative mobile and internet services in ubiquitous computing 2013 (pp. 94-100). IEEE.

[31]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.

[32]Reina DG, León-coca JM, Toral SL, Asimakopoulou E, Barrero F, Norrington P, 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.

[33]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.

[34]Arbia DB, Alam MM, Attia R, Hamida EB. Behavior of wireless body-to-body networks routing strategies for public protection and disaster relief. In 11th international conference on wireless and mobile computing, networking and communications 2015 (pp. 117-24). IEEE.

[35]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.

[36]Stute M, Maass M, Schons T, Hollick M. Reverse engineering human mobility in large-scale natural disasters. In proceedings of the 20th international conference on modelling, analysis and simulation of wireless and mobile systems 2017 (pp. 219-26). ACM.

[37]Sani AM, Newaz SS, Wani SM, Wan AT, Jahan S. TCP performance evaluation under manet routing protocols in disaster recovery scenario. In 4th international conference on advances in electrical engineering 2017 (pp. 389-94). IEEE.

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

[39]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.

[40]Walunjkar G, Rao AK. Simulation and evaluation of different mobility models in disaster scenarios. In 4th international conference on recent trends on electronics, information, communication & technology 2019 (pp. 464-9). IEEE.

[41]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.

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

[43]Mondal R, Biswas A, Bhattacharya I, Mahapatra PR. A framework for post disaster management using device to device communication with controlled mobility and opportunistic routing. In devices for integrated circuit 2021 (pp. 572-6). IEEE.

[44]Pirzadi S, Pourmina MA, Safavi-hemami SM. A novel routing method in hybrid DTN–MANET networks in the critical situations. Computing. 2022; 104(9):2137-56.

[45]Reina DG, Marin ST, Bessis N, Barrero F, Asimakopoulou E. An evolutionary computation approach for optimizing connectivity in disaster response scenarios. Applied Soft Computing. 2013; 13(2):833-45.

[46]Mahiddin NA, Affandi FF, Mohamad Z. A review on mobility models in disaster area scenario. International Journal of Advanced Technology and Engineering Exploration. 2021; 8(80):848-73.

[47]Saini RK. Comparative study of on demand routing protocols in wireless sensor networks. Journal of Information Technology & Software Engineering. 2021; 11(02):255.

[48]Snigdh I, Gosain D. Analysis of scalability for routing protocols in wireless sensor networks. Optik. 2016; 127(5):2535-8.

[49]Nwuku YE, Ajibesin AA, Ishaq AT. A comprehensive analysis of proactive and reactive MANET routing protocols using NS3. Journal of Engineering and Applied Sciences Technology. 2021; 3(1):1-6.

[50]Alameri IA, Komarkova J. A multi-parameter comparative study of MANET routing protocols. In 15th Iberian conference on information systems and technologies 2020 (pp. 1-6). IEEE.

[51]Neeraj K, Yedupati K, Soumya AS, Krishna SS. Performance analysis of different routing protocols in manet using different parameters in different ranges. In 2nd international conference on I-SMAC 2018 (pp. 713-8). IEEE.