International Journal of Computer Networks and Applications

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The Impact of Mobility Models on Geographic Routing in Multi-Hop Wireless Networks and Extensions – A Survey


Affiliations
1 Firstsoft Technologies Private Limited, Chennai, Tamil Nadu, India
2 Department of Information Technology, MLR Institute of Technology, Hyderabad, Telangana, India
 

Multi-hop Wireless Networks (MWNs) emerge as an enabling communication technology, evolving rapidly due to the accelerating advancements and creating potential network applications that significantly improve the quality of life. Pure general-purpose MANET laid the theoretical foundation for MWNs, and many extensions are successfully deployed in commercial networks. This article surveys geographical routing protocols and mobility models applicable to MWNs and their recently proposed extensions. Mobility is a significant factor that profoundly impacts the performance of multi-hop geographical routing. This study analyzes various mobility models that significantly influence the performance of geographical routing protocols based on the characteristics and behavior of various network extensions. This survey investigates the primary challenges in designing geographical routing for various mobility models that notably impact the routing performance for a particular network extension. It also explores the enormous potential of geographical routing protocols under each extension and adequately addressing the routing and mobility-related issues. The essential factors that impact geographical routing, the freshness of location information, and the adaptive location update are examined extensively for various network extensions. Finally, the survey concludes with future research challenges and directions.

Keywords

Multihop Wireless Networks, Geographical Routing, Mobility Models, MANET, FANET, WSN, VANET, DTN.
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  • Macro Conti, Silvia Giordano, “Multi-hop Ad-hoc networking: The Reality”, IEEE Communications Magazine, Vol. 45, No.4, pp. 88-95, 2007

  • Ruhrup, Stephan, “Theory and practice of Geographic routing”, Ad Hoc and Sensor Wireless Networks: Architectures, Algorithms and Protocols, pp. 1-37, 2009

  • Chlamtac Imrich, Marco Conti, and Jennifer J-N. Liu, “Mobile ad hoc networking: imperatives and challenges”, Ad hoc networks, Vol.1, No.1, pp 13-64, 2003.

  • Bekmezci, Ilker, Ozgur Koray Sahingoz, and Şamil Temel, “Flying ad-hoc networks (FANETs): A survey”, Ad Hoc Networks, Vol.11, No. 3, pp.1254-1270, 2013.

  • Priyanka Rawat, Kamal Deep Singh, Hakima Chaouchi, Jean Marie Bonnin, “Wireless sensor networks: a survey on recent developments and potential synergies”, The Journal of Super computing, Vol. 68, No. 1, pp 1–48, 2014.

  • Tong Wang, Yue Cao, Yougzhe Zhou, Pengcheng Li, "A Survey on Geographic Routing Protocols in Delay/Disruption Tolerant Networks", International Journal of Distributed Sensor Networks, 2016, http://dx.doi.org/10.1155/2016/3174670

  • Souaad Boussoufa-Lahlaha, FouziSemchedinea, LouizaBouallouche-Medjkounea, “Geographic routing protocols for Vehicular Ad hoc NETworks (VANETs): A survey”, Vehicular Communications, Vol. 11, pp. 20-31, 2018.

  • Tasneem Darwish, Kamalrulnizam Abu Bakar, Ahlam Hashim, “Green geographical routing in vehicular ad hoc networks: Advances and challenges”, Computers & Electrical Engineering, Vol.64, pp. 436-449, 2017.

  • Cadger Fraser, Kevin Curran, Jose Santos, and Sandra Moffett, “A survey of geographical routing in wireless ad-hoc networks", IEEE Communications Surveys & Tutorials, Vol. 15, No. 2, pp. 621-653, 2013

  • Nakano, Keisuke, Masakazu Sengoku, and Shoji Shinoda, “Effect of mobility on connectivity of mobile multihop wireless networks”, IEEE 55th Conference on Vehicular Technology, Vol. 3, pp. 1195-1199, 2002.

  • Son, D., Helmy, A. and Krishnamachari, B, “The effect of mobility-induced location errors on geographic routing in ad hoc networks: analysis and improvement using mobility prediction”, In IEEE Wireless Communications and Networking Conference, Vol.1, pp.189-194, Atlanta, GA, USA, 2004.

  • T. Camp, J. Bowling, and V. Davies, “A survey of mobility models for ad hoc network research”, Wireless Communication and Mobile Computing, Vol.2, No. 5, pp.483–502, 2002.

  • Pan, Jianli, and Raj Jain, “A survey of network simulation tools: Current status and future developments”, Vol.7, No. 6, pp. 1-13, 2008.

  • Treurniet, J, “A taxonomy and survey of microscopic mobility models from the mobile networking domain”, ACM Computing Surveys (CSUR), Vol.47, No.1, pp. 1-32, 2014.

  • Gorawski Michal, and Krzysztof Grochla, “Review of mobility for performance evaluation of wireless networks”, Advances in Intelligent Systems and Computing, Springer, Vol. 242, pp. 567-577, 2014.

  • Vaity, N. P., & Thombre, D. V, “A survey on vehicular mobility modeling: flow modeling”, International Journal of Communication Network Security, Vol.1, No.4, 21, 2012

  • Batabyal, Suvadip, and Parama Bhaumik, “Mobility models, traces and impact of mobility on opportunistic routing algorithms: A survey”, IEEE Communications Surveys & Tutorials, Vol.17, No. 3, pp. 1679-1707, 2015.

  • B. Karp and H. T. Kung, “GPSR: Greedy Perimeter Stateless Routing for Wireless Networks”, in Proceedings of ACM Mobicom, pp. 243-254, Boston, Massachusetts, USA, 2000.

  • E. Kranakis, S. O. C. Science, H. Singh, and J. Urrutia, “Compass Routing on Geometric Networks,” in Proc. 11 th Canadian Conference on Computational Geometry, pp. 51–54, Ottawa, Canada, 1999.

  • F. Kuhn, R. Wattenhofer, and A. Zollinger, “An algorithmic approach to geographic routing in ad hoc and sensor networks”, IEEE/ACM Transactions On Networking, Vol. 16, No. 1, pp. 51–62, 2008.

  • J. Na and C. Kim, “GLR: A novel geographic routing scheme for large wireless ad hoc networks,” Computer Networks, Vol. 50, No. 17, pp. 3434–3448, 2006.

  • J. Na, D. Soroker, and C.-k. Kim, “Greedy Geographic Routing using Dynamic Potential Field for Wireless Ad Hoc Networks,” IEEE Communication Letters., Vol. 11, No. 3, pp. 243–245, 2007.

  • Y.-J. Kim, R. Govindan, B. Karp, and S. Shenker, “On the pitfalls of geographic face routing,” Proceeding joint workshop on Foundations of mobile computing - DIALM-POMC, pp. 34-43, Cologne, Germany, 2005.

  • F. Kuhn, R. Wattenhofer, and A. Zollinger, “Asymptotically optimal geometric mobile ad-hoc routing,” Proceeding 6th international workshop on Discrete algorithms and methods for mobile computing and communications - DIALM, pp. 24-33, Atlanta, Georgia, USA, 2002.

  • F. Kuhn, R. Wattenhoffer, and A. Zollinger, “Worst-case optimal and average-case efficient geometric ad-hoc routing,” in Proc. 4th ACM international symposium on Mobile ad hoc networking & computing,ser. MobiHoc, ACM, pp. 267–278, Annapolis, Maryland, USA, 2003

  • F. Kuhn, R.Wattenhofer, Y. Zhang, and A. Zollinger, "Geometric ad-hoc routing: Of theory and practice", In Proceedings of the 22nd ACM International Symposium on the Principles of Distributed Computing(PODC), pages 63–72, Boston, Massachusetts, USA, 2003

  • B. Leong, S. Mitra, and B. Liskov, “Path vector face routing: geographic routing with local face information,” 13th IEEE International Conference on Routing Protocols, pp. 12, Boston, MA, USA, 2005

  • Biswas, S., & Morris, R., “Opportunistic routing in multi-hop wireless networks”, ACM SIGCOMM Computer Communication Review, Vol.34, No.1, pp.69-74, 2004

  • Zhong, Z., Wang, J., Nelakuditi, S., & Lu, G. H., “On selection of candidates for opportunistic any path forwarding”, ACM SIGMOBILE Mobile Computing and Communications Review, Vol.10, No.4, pp.1-2, 2006

  • R. Jain, A. Puri, and R. Sengupta, “Geographical Routing Using Partial Information for Wireless Ad Hoc Networks,” IEEE Personal Communications, Vol. 8, No.1, pp. 48–57, 2001

  • Dazhi chen and Pramod k. Varshney, “A survey of void handling techniques for geographic routing in wireless networks”, IEEE communications Surveys and Tutorials, Vol. 9, No.1, 2007

  • Hugo Barbosa-Filho, et.al, "Human Mobility: Models and Applications", arXiv.org, physics, arXiv:1710.00004, 2017.

  • Fan Bai and Ahmed He, “A Survey of Mobility Models in Wireless Adhoc Networks”, 2004.

  • M. Guenes and J. Siekermann, “CosMos–communication scenario and mobility scenario generator for mobile ad-hoc networks”, in Proc 2nd Int. Worksh, MANETs Interoper, Iss. MANETII, Las Vegas, USA, 2005

  • B. Zhou, Y.-Z. Lee, and M. Gerla, “Direction assisted geographic routing for mobile ad hoc networks,” in Proceedings of MILCOM Military Communications Conference. IEEE, 2008

  • Seungjoon Lee, Bobby Bhattacharjee , Suman Banerjee and Bo Han, “A General Framework for Efficient Geographic Routing in Wireless Networks”, Computer Networks, Vol. 54, No. 5, pp. 844-861, 2010

  • Baban A. Mahmood and D. Manivannan, “GRB: Greedy Routing Protocol with Backtracking for Mobile Ad Hoc Networks”, IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems, Dallas, TX, USA, 2015

  • Dong Yang, Hongxing Xia, Erfei Xu, Dongliang Jing and Hailin Zhang, “An Energy-Balanced Geographic Routing Algorithm for Mobile Ad Hoc Networks” Energies, Vol. 11, No. 9, pp. 1-16, 2018

  • Noureddine, H., Ni, Q., Min, G., & Al-Raweshidy, H, “A New Link Lifetime Prediction Method for Greedy and Contention-based Routing in Mobile Ad Hoc Networks”, 10th IEEE International Conference on Computer and Information Technology, 2010

  • Nallusamy, C., & Sabari, A, “Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET”, Mobile Networks and Applications, 2017

  • Chih‑Lin Hu and Chuluuntulga Sosorburam, “Enhanced Geographic Routing with Two‑Hop Neighborhood Information in Sparse MANETs” Wireless Personal Communications: An International Journal, Vol.107, No. 1, pp. 417-436, 2019

  • Jung, W.-S., Yim, J., & Ko, Y.-B, “QGeo: Q-Learning-Based Geographic Ad Hoc Routing Protocol for Unmanned Robotic Networks”, IEEE Communications Letters, Vol. 21, No. 10, pp. 2258–2261, 2017

  • Haesu Hwang, In HUT, and Hyunseung Choo, “GOAFR Plus-ABC: Geographic Routing Based on Adaptive Boundary Circle in MANETs”, International Conference on Information Networking, Chiang Mai, Thailand, 2009

  • Ben Newton, Jay Aikat, Kevin Jeffay, “Geographic Routing in Large-Scale Highly-Dynamic Mobile Ad hoc Networks”, IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), London, UK, 2015

  • Alshehri, A., Badawy, A.-H. A., & Huang, H, “FQ-AGO: Fuzzy Logic Q-Learning Based Asymmetric Link Aware and Geographic Opportunistic Routing Scheme for MANETs”, Electronics, Vol. 9, No. 4, 2020

  • Daeho Kanga , Hyung-Sin Kimb , Changhee Jooc , Saewoong Bahk, “ORGMA: Reliable opportunistic routing with gradient forwarding for MANETs”, Computer Networks, 2017

  • Li, N., Martinez-Ortega, J.-F., & Diaz, V. H, “Cross-Layer and Reliable Opportunistic Routing Algorithm for Mobile Ad Hoc Networks”, IEEE Sensors Journal, Vol. 18, No. 13, pp. 5595–5609, 2018

  • Wang, Z., Chen, Y., & Li, C. “CORMAN: A novel cooperative opportunistic routing scheme in mobile ad hoc networks. IEEE Journal on Selected Areas in Communications, Vol.30, No.2, pp. 289-296, 2012

  • Armir Bujari, Carlos T Calafate, Juan-Carlos Cano, Pietro Manzoni, Claudio Enrico Palazzi and Daniele Ronzani, "Flying ad-hoc network application scenarios and mobility models", International Journal of Distributed Sensor Networks, Vol 13, No.10, 2017.

  • Samira Hayat, Evşen Yanmaz, Raheeb Muzaffar,"Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint", IEEE Communications Surveys & Tutorials, Vol: 18, No: 4, pp 2624 - 2661, 2016.

  • Oubbati, Omar Sami, Abderrahmane Lakas, Fen Zhou, Mesut Güneş, and Mohamed Bachir Yagoubi, “A survey on position-based routing protocols for Flying Ad hoc Networks (FANETs)”, Vehicular Communications, Vol. 10, pp. 29-56, 2017.

  • Guillen-Perez, A. and Cano, M.D, “Flying ad hoc networks: A new domain for network communications”, Sensors, Vol.18, No.10, p.3571, 2018

  • Omar Sami Oubbatia, , Abderrahmane Lakasb, Fen Zhouc , Mesut G¨une¸sd, Nasreddine Lagraaa, Mohamed Bachir Yagoubia, “Intelligent UAV-Assisted Routing Protocol for Urban VANETs”, Computer Networks, 2017

  • Robert L. Lidowski, Barry E. Mullins, Rusty O. Baldwin, "A novel communications protocol using geographic routing for swarming UAVs performing a Search Mission", In Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications, USA, 2009.

  • Vieira, L. F. M., & Cunha, A. V. dos S, “Performance of Greedy Forwarding in Geographic Routing for the Internet of Drones”, Internet Technology Letters, Vol: 1, No:5, 2018.

  • Qamar Usman, Omer Chughtai, Nadia Nawaz, Zeeshan Kaleem, Kishwer Abdul Khaliq, Long D. Nguyen, "A Reliable Link-adaptive Position-based Routing Protocol for Flying Ad hoc Network", Mobile Networks and Applications, 2021.DOI:https://doi.org/10.1007/s11036-021-01758-w

  • Lin Lin, Qibo Sun, Jinglin Li, Fangchun Yang, "A Novel Geographic Position Mobility Oriented Routing Strategy for UAVs", Journal of Computational Information Systems, Vol:8, No: 2, pp 709-716, 2012.

  • E. Kuiper, S. Nadjm-Tehrani, “Geographical routing with location service in intermittently connected MANETs”, IEEE Transactions on Vehicular Technology, Vol. 60 , No.2, pp. 592–604, 2011.

  • Jabbar, J. P. Sterbenz, “AeroRP: A geolocation assisted aeronautical routing protocol for highly dynamic telemetry environments”, in: Proceedings of the International Telemetering Conference, pp. 1-10, Las Vegas, NV, 2009.

  • D. Ros ́ario, Z. Zhao, T. Braun, E. Cerqueira, A. Santos, I. Alyafawi, “Opportunistic routing for multi-flow video dissemination over flying ad-hoc networks”, in: Proceedings of the 15th International IEEE Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1–6, Sydney, NSW, Australia, 2014

  • Arafat, M. Y., & Moh, S, “Location-Aided Delay Tolerant Routing Protocol in UAV Networks for Post-Disaster Operation”, IEEE Access, 2018

  • Xiong Wang, Luoyi Fu, Yang Zhang, Xiaoying Gan and Xinbing Wang, “VDNet: an infrastructure-less UAV-assisted sparse VANET system with vehicle location prediction”, Wireless Communications and Mobile Computing, 2016

  • Omar Sami Oubbati, Abderrahmane Lakas†, Nasreddine Lagraa, and Mohamed Bachir Yagoubi, “CRUV: Connectivity-based Traffic Density Aware Routing using UAVs for VANets”, International Conference on Connected Vehicles and Expo (ICCVE), 2015

  • Xiaoyan Ma, Simona Chisiu, Rahim Kacimi and Riadh Dhaou, “Opportunistic Communications in WSN Using UAV”, 14th IEEE SURVEY ARTICLE Annual Consumer Communications & Networking Conference (CCNC), USA, 2017

  • He, Y., Tang, X., Zhang, R., Du, X., Zhou, D., & Guizani, M, “A Course-Aware Opportunistic Routing Protocol for FANETs”. IEEE Access, Vol. 7, pp. 144303–144312, 2019

  • Stefano Basagni, Alessio Carosi, and Chiara Petriol, "Mobility in Wireless Sensor Networks", Technical Report, 2012, https://www2.eecs.berkeley.edu/Pubs/TechRpts/2012/EECS-2012-270.pdf

  • Ricardo Silva, JorgeSa Silva, Fernando Boavida, "Mobility in wireless sensor networks–Survey and proposal", Computer Communications, Vol 52, pp 1-20, 2014.

  • R. Shah, S. Roy, S. Jain, and W. Brunette, “Data mules: modeling a three-tier architecture for sparse sensor networks,” in Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, pp. 30–41, Anchorage, AK, USA, 2003

  • P. Juang, H. Oki, Y. Wang, M. Martonosi, L. S. Peh, and D. Rubenstein, “Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet,” ACM SIGOPS Operation System Review, Vol. 36, No. 5, pp. 96–107, 2002.

  • B. Hull, V. Bychkovsky, Y. Zhang, K. Chen, M. Goraczko, A. Miu, E. Shih, H. Balakrishnan, and S. Madden, “Cartel: a distributed mobile sensor computing system,” in Proceedings of ACM the 4th international conference on Embedded networked sensor systems, SenSys, pp. 125–138, Boulder, Colorado, 2006.

  • H. Smeets, C.-Y. Shih, M. Zuniga, T. Hagemeier, and P. Marron, “Trainsense: A novel infrastructure to support mobility in wireless sensor networks,” Lecture Notes in Computer Science, Vol. 7772, pp. 18–33, 2013.

  • T. Zhang, D. Wang, J. Cao, Y. Q. Ni, L.-J. Chen, and D. Chen, “Elevator-assisted sensor data collection for structural health monitoring,” IEEE Transactions on Mobile Computing, Vol. 11, No. 10, pp. 1555–1568, 2012.

  • D. Johnson, T. Stack, R. Fish, D. Flickinger, L. Stoller, R. Ricci, and J. Lepreau, “Mobile emulab: A robotic wireless and sensor network testbed,” in Proceedings of IEEE the 25th IEEE International Conference on Computer Communications (INFOCOM), pp. 1–12, Barcelona, Spain, 2006.

  • P. De, A. Raniwala, R. Krishnan, K. Tatavarthi, J. Modi, N. A. Syed, S. Sharma, and T.-c. Chiueh, “Mint-m: an autonomous mobile wireless experimentation platform,” in Proceedings of the 4th international conference on Mobile systems, applications and services, ser. MobiSys, pp. 124–137, Uppsala, Sweden, 2006.

  • S. Gandham, M. Dawande, R. Prakash, and S. Venkatesan, “Energy efficient schemes for wireless sensor networks with multiple mobile base stations,” in Proc. of IEEE Global Telecommunications Conference, Vol. 1, pp. 377–381, San Francisco, USA, 2003.

  • F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, “A two-tier data dissemination model for large-scale wireless sensor networks,” in Proceedings of ACM the 8th annual international conference on Mobile computing and networking, ser. MobiCom, pp. 148–15, Atlanta, Georgia, USA, 2002.

  • C.-J. Lin, P.-L. Chou, and C.-F. Chou, “Hcdd: hierarchical cluster-based data dissemination in wireless sensor networks with mobile sink,” in Proceedings of the ACM 2006 international conference on Wireless communications and mobile computing, ser. IWCMC, pp. 1189–1194, Vancouver, British Columbia, Canada, 2006.

  • D. Jea, A. Somasundara, and M. Srivastava, “Multiple controlled mobile elements (data mules) for data collection in sensor networks,” Lecture Notes in Computer Science, Vol. 3560, pp. 244–257, 2005.

  • S. Basagni, A. Carosi, E. Melachrinoudis, C. Petrioli, and Z. M. Wang, “Controlled sink mobility for prolonging wireless sensor networks lifetime,” Wireless Networks, Vol. 14, No. 6, pp. 831–858, 2008.

  • Y. Shi and Y. Hou, “Theoretical results on base station movement problem for sensor network,” in INFOCOM 2008. The 27th Conference on Computer Communications. IEEE, pp. 1–5, Phoenix, AZ, USA, 2008.

  • M. Ma and Y. Yang, “Sencar: An energy-efficient data gathering mechanism for large-scale multihop sensor networks,” IEEE Transactions on Parallel and Distributed Systems, Vol. 18, No. 10, pp. 1476–1488, 2007.

  • G. Xing, T. Wang, Z. Xie, and W. Jia, “Rendezvous planning in mobility-assisted wireless sensor networks,” in Proceedings of the 28th IEEE International Real-Time Systems Symposium (RTSS), pp. 311–320, Tucson, Arizona, USA, 2007.

  • M. Zhao and Y. Yang, “Bounded relay hop mobile data gathering in wireless sensor networks,” IEEE Transactions on Computers, Vol. 61, No. 2, pp. 265–277, 2012.

  • Khelifi, M., Bourouais, S., Lounis, O., & Moussaoui, S, “GRCS: A cluster-based geographic routing protocol for WSNs”, Ninth International Conference on Ubiquitous and Future Networks (ICUFN), 2017.

  • Yu, F., Park, S., Lee, E., & Kim, S.-H. “Elastic routing: a novel geographic routing for mobile sinks in wireless sensor networks”, IET Communications, Vol. 4, No. 6, pp. 716–727, 2010

  • Tran Dinh Hieu, Le The Dung, and Byung-Seo Kim, “Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks”, Sensors, 2016

  • Mouna Rekik, Nathalie Mitton, Zied Chtourou, “GRACO: a geographic GReedy routing with an ACO-based void handling technique” International Journal of Sensor Networks, Vol.26, No.3, pp.145–161, 2018.

  • Sun, Y., Guo, J., & Yuhui Yao, “Speed Up-Greedy Perimeter Stateless Routing Protocol for Wireless Sensor Networks (SU-GPSR)”, IEEE 18th International Conference on High Performance Switching and Routing (HPSR), 2017.

  • Basagni, S., Carosi, A., Melachrinoudis, E., Petrioli, C., & Wang, Z, “A New MILP Formulation and Distributed Protocols for Wireless Sensor Networks Lifetime Maximization”, IEEE International Conference on Communications, 2006.

  • Antonio Caruso, Francesco Paparella, Luiz F. M. Vieira, Melike Erol, Mario Gerla, “The Meandering Current Mobility Model and its Impact on Underwater Mobile Sensor Networks”, IEEE INFOCOM The 27th Conference on Computer Communications, pp. 771-779, Phoenix, AZ, USA, 2008.

  • zheng yang and yunhao liu, “Sea Depth Measurement with Restricted Floating Sensors”, 28th IEEE International Real-Time Systems Symposium (RTSS), Tucson, AZ, USA 2013

  • Xie, P., Cui, J. and Lao, L, “VBF: Vector-based forwarding protocol for underwater sensor networks”, IFIP International Federation for Information Processing, pp. 1216–1221, 2006.

  • Nicolaou, N., See, A., Xie, P., Cui, J. H. and Maggiorini, D, “Improving the Robustness of Location-Based Routing for Underwater Sensor Networks,” IEEE Oceans Conference, pp.1-6, Aberdeen, UK, 2007.

  • Jinming, C., Xiaobing, W. and Guihai, C. (2008) “REBAR: a reliable and energy balanced routing algorithm for UWSNs”. In Proceedings of the seventh international conference on grid and cooperative computing, pp. 349-355, Shenzhen, China 2008.

  • Daeyoup, H. and Dongkyun, K., “DFR: Directional flooding-based routing protocol for underwater sensor networks” IEEE OCEANS, pp. 1-7, Quebec City, QC, Canada, 2008

  • Anupama, KR., Sasidharan, A. and Vadlamani, S., “A location-based clustering algorithm for data gathering in 3D underwater wireless sensor networks” In Proceedings of the International Symposium on Telecommunications, IST, pp. 343-348, Tehran, Iran, 2008.

  • Rahman Z, Hashim F, Rasid MFA, Othman M, “Totally opportunistic routing algorithm (TORA) for underwater wireless sensor network”. PLoS ONE, Vol. 13, No. 6, pp. 1-28, 2018

  • Chirdchoo, N., Wee-Seng, S. and Kee Chaing, C, “Sector-based routing with destination location prediction for underwater mobile networks”, In Proceedings of the international conference on advanced information networking and applications workshops, pp. 1148-1153, Bradford, UK, 2009.

  • Coutinho, R. W. L., Vieira, L. F. M., & Loureiro, A. A. F, “DCR: Depth-Controlled Routing protocol for underwater sensor networks”, IEEE Symposium on Computers and Communications (ISCC), 2013.

  • Seyed Mohammad Ghoreyshi , Alireza Shahrabi, and Tuleen Boutaleb, “A Stateless Opportunistic Routing Protocol for Underwater Sensor Networks”, Wireless Communications andMobileComputingVolume, pp. 1-18, 2018.

  • Noh, Y., Lee, U., Wang, P., Choi, B. S. C., & Gerla, M, “VAPR: Void-Aware Pressure Routing for Underwater Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 12, No. 5, pp. 895–908, 2013.

  • Coutinho, R. W. L., Boukerche, A., Vieira, L. F. M., & Loureiro, A. A. F, “GEDAR: Geographic and opportunistic routing protocol with Depth Adjustment for mobile underwater sensor networks”, IEEE International Conference on Communications (ICC), 2014.

  • Choffnes, D., Bustamante, F, “An Integrated Mobility and Traffic Model for Vehicular Wireless Networks”, In: 2nd ACM Workshop on Vehicular Ad Hoc Networks, pp. 69-78, Cologne, Germany 2005.

  • Uchiyama, A, “Mobile Ad-hoc Network Simulator based on Realistic Behavior Model”, Demo Session in MobiHoc, 2005

  • Gainaru, A., Dobre, C., Cristea, V, “A Realistic Mobility Model Based on Social Networks for the Simulation of VANETs”, In: IEEE 69th Vehicular Technology Conference, pp. 1–5, Barcelona, Spain, 2009.

  • Choffnes, David, and Fabin E. Bustamante, “STRAW-An Integrated Mobility and Traffic Model for VANET”, Proc. of the 10th International Command and Control Research and Technology Symposium (CCRTS), pp. 1-7, 2005.

  • Khokhar, Rashid Hafeez, et al, “Fuzzy-assisted social-based routing for urban vehicular environments”, EURASIP Journal on Wireless Communications and Networking, pp. 1-15, 2011

  • Zhao, Jing, and Guohong Cao. "VADD: Vehicle-assisted data delivery in vehicular ad hoc networks." IEEE transactions on vehicular technology, Vol.57, No.3, pp.1910-1922, 2008.

  • Xue, G., Luo, Y., Yu, J., & Li, M. “A novel vehicular location prediction based on mobility patterns for routing in urban VANET”, EURASIP Journal on Wireless Communications and Networking, Vol. 1, pp.1-14, 2012.

  • Lochert, C., Hartenstein, H., Tian, J., Fussler, H., Hermann, D., & Mauve, M. “A routing strategy for vehicular ad hoc networks in city environments”, IEEE Intelligent vehicles symposium, pp. 156–161, Columbus, OH, USA, 2003.

  • Seet, Boon-Chong, Genping Liu, Bu-Sung Lee, Chuan-Heng Foh, Kai-Juan Wong, and Keok-Kee Lee, “A-STAR: A mobile ad hoc routing strategy for metropolis vehicular communications”, In International Conference on Research in Networking, pp. 989-999, 2004.

  • Jerbi, M., Meraihi, R., Senouci, S. M., & Ghamri-Doudane, Y, “Gytar: Improved greedy traffic aware routing protocol for vehicular ad hoc networks in city environments”, ACM Proceedings of the 3rd international workshop on vehicular ad hoc networks, pp. 88–89, Los Angeles, CA, USA, 2006.

  • V. Naumov and T.R. Gross. “Connectivity-aware routing (car) in vehicular ad-hoc networks”, In Proceedings of the IEEE International Conference on Computer Communications, pp.1919–1927, Barcelona, Spain, 2007.

  • Schnaufer, S., & Effelsberg, W, “Position-based unicast routing for city scenarios”, International Symposium on a World of Wireless, Mobile and Multimedia Networks, 2008

  • B. Kirsch, W. Effelsberg, “Implementation of a Distance-Vector-Based Recovery Strategy for Position-Based-Routing”, Department of Mathematics and Computer Science, University of Mannheim, 2007.

  • Tsiachris, S., Koltsidas, G., & Pavlidou, F.-N, “Junction-Based Geographic Routing Algorithm for Vehicular Ad hoc Networks”, Wireless Personal Communications, Vol. 71, No. 2, pp., 955–973, 2012

  • Wang, L., Chen, Z., & Wu, J, “An Opportunistic Routing for Data Forwarding Based on Vehicle Mobility Association in Vehicular Ad Hoc Networks”, Information, Vol. 8, No. 4, 2017

  • I. Leontiadis and C. Mascolo, “GeOpps: geographical opportunistic routing for vehicular networks,” in Proceedings of the IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WOWMOM), pp. 1–6, Espoo, Finland, 2007.

  • Ghaffari, A, “Hybrid opportunistic and position-based routing protocol in vehicular ad hoc networks”, Journal of Ambient Intelligence and Humanized Computing, 2019

  • Lee, K. C., Le, M., Harri, J., & Gerla, M. “Louvre: Landmark overlays for urban vehicular routing environments”, IEEE Conference on Vehicular Technology, Calgary, BC, Canada, 2008.

  • Baischolar_mainkar M, Ghaffarpour Rahbar. A, & Sabaei, M, “LDAOR Location and Direction Aware Opportunistic Routing in Vehicular Ad hoc Networks”, Journal of Telecommunications and Information Technology, Vol. 1, No. 1, pp 68–83, 2016.

  • Sadatpour, V., Zargari, F., & Ghanbari, M, “A Collision Aware Opportunistic Routing Protocol for VANETs in Highways”, Wireless Personal Communications, 2019

  • Li, N., Martinez-Ortega, J.-F., Diaz, V. H., & Fernandez, J. A. S, “Probability Prediction-Based Reliable and Efficient Opportunistic Routing Algorithm for VANETs”, IEEE/ACM Transactions on Networking, Vol. 26, No. 4, pp. 1933–1947, 2018.

  • Naderi, M., Zargari, F., Sadatpour, V., & Ghanbari, M, “A 3-Parameter Routing Cost Function for Improving Opportunistic Routing Performance in VANETs”, Wireless Personal Communications, Vol. 97, No. 1, pp. 109–123, 2017.

  • Uddin, Md Yusuf S., David M. Nicol, Tarek F. Abdelzaher, and Robin H. Kravets, “A post-disaster mobility model for delay tolerant networking”, In Winter Simulation Conference, pp. 2785-2796, Austin, TX, USA, 2009.

  • Walker, Brenton D., T. Charles Clancy, and Joel K. Glenn, “Using localized random walks to model delay-tolerant networks”, In Military Communications Conference, MILCOM IEEE, pp. 1-7, San Diego, CA, USA, 2008.

  • M Shahzamal, M F Pervez, M A U Zaman, and M D Hossain, "Mobility Models for Delay Tolerant Network: A Survey", International Journal of Wireless & Mobile Networks, Vol. 6, No. 4, 2014.

  • F. Ekman, A. Ker¨anen, J. Karvo, and J. Ott, “Working day movement model”, in Proceedings of the In Proceedings of the 1st ACMSIGMOBILE workshop on Mobility models, (MobilityModels), pp. 33–40, Hong Kong, China, 2008.

  • Q. Zheng, X. Hong, J. Liu, D. Cordes, and W. Huang, “Agenda driven mobility modelling”, International Journal of Ad Hoc and Ubiquitous Computing, Vol. 5, No. 1, pp. 22–36, 2009.

  • X. Zhu, Y. Bai, W. Yang, Y. Peng, and C. Bi, “SAME: A students’ daily activity mobility model for campus delay-tolerant networks,” in Proceedings of the 8th Asia-Pacific Conference on Communications (APCC), pp. 528–533, Jeju Island, South Korea, 2012.

  • J. Ghosh, S. J. Philip, and C. Qiao, “Sociological orbit aware location approximation and routing (SOLAR) in MANET”, Ad Hoc Networks, Vol. 5, No. 2, pp. 189–209, 2007.

  • W. J. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy, “Modeling time-variant user mobility in wireless mobile networks,” in Proceedings of the 26th IEEE International Conference on Computer Communications, pp. 758–766, Barcelona, Spain, 2007.

  • K. Lee, S. Hong, S. J. Kim, I. Rhee, and S. Chong, “Slaw: A new mobility model for human walks”, in Proceedings of the INFOCOM, IEEE, pp. 855–863, Rio de Janeiro, Brazil, 2009.

  • C. Boldrini and A. Passarella, “HCMM, Modelling spatial and temporal properties of human mobility driven by users social relationships,” Computer Communications, Vol. 33, No. 9, pp. 1056–1074, 2010.

  • N. Vastardis and K. Yang, “An enhanced community-based mobility model for distributed mobile social networks,” Journal of Ambient Intelligence and Humanized Computing, Vol. 5, No. 1, pp. 65–75, 2014.

  • V. Borrel, F. Legendre, M. D. de Amorim, and S. Fdida, “Simps, Using sociology for personal mobility,” IEEE/ACMTransactions on Networking, Vol. 17, No. 3, pp. 831–842, 2009.

  • D. Fischer, K.Herrmann, andK. Rothermel, “GeSoMo-A general social mobility model for delay tolerant networks,” in Proceedings of the 7th International Conference on Mobile Adhoc and Sensor Systems (MASS), IEEE, pp. 99–108, San Francisco, CA, USA, 2010.

  • Dávid HrabIák, Martin Matis, L’ubomír Doboš, and Ján Papaj, “Students Social Based Mobility Model for MANET-DTN Networks”, Mobile Information System, pp. 1-13, 2017

  • H. Kang and D. Kim, “Vector routing for delay tolerant networks,” in Proceedings of the 68th IEEE Vehicular Technology Conference (VTC-Fall), pp. 1–5, Calgary, Canada, 2008.

  • Yue Cao ; Zhili Sun ; Ning Wang ; Haitham Cruickshank ; Naveed Ahmad, “A Reliable and Efficient Geographic Routing Scheme for Delay/Disruption Tolerant Networks”, IEEE Wireless Communications Letters, Vol. 2 , No. 6, pp. 603-606, 2013.

  • H. Kang and D. Kim, “HVR: history-based vector routing for delay tolerant networks,” in Proceedings of the 18th Internatonal Conference on Computer Communications and Networks (ICCCN), pp. 1–6, San Francisco, Calif, USA, 2009.

  • Y. Cao, Z. Sun, N. Wang, M. Riaz, H. Cruickshank, and X. Liu, “Geographic-based spray-and-relay (GSaR): an efficient routing scheme for DTNs,” IEEE Transactions on Vehicular Technology, Vol. 64, No. 4, pp. 1548–1564, 2015.

  • Yue Cao, Kaimin Wei, Geyong Min, Jian Weng, Xin Yang and Zhili Sun, “A Geographic Multi-Copy Routing Scheme for DTNs With Heterogeneous Mobility”, IEEE Systems Journal, Vol. 12 , No.1, pp. 790-801, 2016.

  • O. Turkes, H. Scholten, and P. Havinga, “RoRo-LT: social routing with next-place prediction from self-assessment of spatiotemporal routines,” in Proceedings of the 10th International Conference on Ubiquitous Intelligence and Computing and 10th International Conference on IEEE Autonomic and Trusted Computing (UIC/ATC), pp. 201–208, Vietri sulMare, Italy, 2013.

  • V. N. G. J. Soares, J. J. P. C. Rodrigues, and F. Farahmand, “GeoSpray: a geographic routing protocol for vehicular delay tolerant networks,” Information Fusion, Vol. 15, No. 1, pp. 102–113, 2014.

  • Y. Cao, Z. Sun, H. Cruickshank, and F. Yao, “Approach-and Roam (AaR): a geographic routing scheme for delay/disruption tolerant networks,” IEEE Transactions on Vehicular Technology, Vol. 63, No. 1, pp. 266–281, 2014.

  • Cao, Y., Han, C., Zhang, X., Kaiwartya, O., Zhuang, Y., Aslam, N., Dianati, M, “A Trajectory-Driven Opportunistic Routing Protocol for VCPS”, IEEE Transactions on Aerospace and Electronic Systems, Vol. 54, No. 6, pp. 2628-2642, 2018.

  • Yue Cao ; Zhili Sun ; Ning Wang ; Fang Yao ; Haitham Cruickshank, “Converge-and-Diverge: A Geographic Routing for Delay/Disruption-Tolerant Networks Using a Delegation Replication Approach”, IEEE Transactions on Vehicular Technology, Vol. 62, No. 5, pp. 2339-2343, 2013.

  • H.-Y. Huang, P.-E. Luo, M. Li et al., “Performance evaluation of SUVnet with real-time traffic data”, IEEE Transactions on Vehicular Technology, Vol. 56, No. 6, pp. 3381–3396, 2007

  • X. Li, W. Shu, M. Li, H. Huang, and M.-Y. Wu, “DTN routing in vehicular sensor networks,” in Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM), pp. 752– 756, New Orleans, La, USA, 2008.

  • J. A. B. Link, D. Schmitz, and K. Wehrle, “GeoDTN: geographic routing in disruption tolerant networks,” in Proceedings of the 54th Annual IEEE Global Telecommunications Conference (GLOBECOM), pp. 1–5, Houston, Tex, USA, 2011.

  • Pei-Chun Cheng · Kevin C. Lee · Mario Gerla · Jérôme Härri, “GeoDTN+Nav: Geographic DTN Routing with Navigator Prediction for Urban Vehicular Environments”, Mobile Networks and Applications, Vol.15, No. 1, pp. 61-82, 2010.

  • Jinyang Li, John Jannotti, Douglas S. J. De Couto, David R. Karger, Robert Morris, Robert, "A Scalable Location Service for Geographic Ad Hoc Routing", Proceedings of the Annual International Conference on Mobile Computing and Networking, 2000.

  • S.M. Das, H. Pucha, Y.C. Hu, "Performance comparison of scalable location services for geographic ad hoc routing", Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies, 2005.

  • X. Shi and K. Liu, “A contention-based beaconless geographic routing protocol for mobile ad hoc networks”, Third International Conference on Communications and Networking in China, pp. 840–843, Hangzhou, China, 2008.

  • G. Y. Lee and Y. Lee, “Numerical analysis of optimum timer value for time-based location registration scheme,” IEEE Communication Letters., Vol. 6, No. 10, pp. 431–433, 2002.

  • D. Son, A. Helmy, B. Krishnamachari, "The effect of mobility-induced location errors on geographic routing in mobile ad hoc sensor networks: analysis and improvement using mobility prediction", IEEE Transactions on Mobile Computing, Vol. 3, No 3, pp.233-245, 2004.

  • Quanjun Chen, Salil S. Kanhere, Mahbub Hassan, "Adaptive Position Update for Geographic Routing in Mobile Ad-hoc Networks", IEEE Transactions on Mobile Computing, Vol 12, No 3, pp 489-501, 2013.

  • Marco Fiore, Claudio Casetti, Carla-Fabiana Chiasserini, Panagiotis Papadimitratos, "Discovery and Verification of Neighbor Positions in Mobile Ad Hoc Networks", IEEE Transactions on Mobile Computing, Vol 12, No. 2, pp. 289-303, 2013.

  • S.H. Shah and K. Nahrstedt. “Predictive location-based QoS routing in mobile ad hoc networks”,Proceedings of IEEE International Conference on Communications, 2002.

  • Liu, G. & Maguire Jr., “A Class of Mobile Motion Prediction Algorithms for Wireless Mobile Computing and Communications”, Mobile Networks and Applications Journal, Springer, Vol.1, No.2, pp 113-121, 1996.

  • M. Rieke, T. Foerster, A. Broering, “Unmanned aerial vehicles as mobile multi-platforms”, in: The 14th AGILE International Conference on Geographic Information Science, pp.18–21, 2011.

  • Chellapa-Doss, R., Jennings, A. & Shenoy, N., “User Mobility Prediction in Hybrid and Ad Hoc Wireless Networks”, Proceeding of the Australian Telecommunications Networks and Applications Conference (ATNAC), 2003.

  • Saman, N. & Karmouch, A., “A Mobility Prediction Architecture Based on Contextual Knowledge and Spatial Conceptual Maps” IEEE Transactions on Mobile Computing. Vol.4, No.6, pp. 537-551, 2005.

  • Kulkarni, Vaibhav, and Benoît Garbinato. "20 Years of Mobility Modeling & Prediction: Trends, Shortcomings & Perspectives." In Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 492-495. 2019.

  • Aarti Munjal,Tracy Camp, and Nils Aschenbruck, “Changing Trends in Modeling Mobility”, Journal of Electrical and Computer Engineering, Hindwai, Vol.2012, pp. 16, 2012

  • V. Kulkarni, A. Mahalunkar, B. Garbinato, and J. D. Kelleher. Examining the limits of predictability of human mobility. Entropy, Vol.21, No.4, pp.432, 2019

  • J. Feng, Y. Li, C. Zhang, F. Sun, F. Meng, A. Guo, and D. Jin. Deepmove: Predicting human mobility with attentional recurrent networks. In WWW, 2018

  • Myounggyu Won, Wei Zhang, Chien-An Chen, Radu Stoleru, "GROLL: Geographic Routing for Low Power and Lossy IoT Networks", Internet of Things, Vol 9, 2020.

  • Dmitrii Chemodanov, Flavio Esposito, Andrei Sukhov, Prasad Calyam, Huy Trinh, Zakariya Oraibia, "AGRA: AI-augmented geographic routing approach for IoT-based incident-supporting applications", Future Generation Computer Systems, Vol 92, pp 1051-1065, 2019.


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  • The Impact of Mobility Models on Geographic Routing in Multi-Hop Wireless Networks and Extensions – A Survey

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Authors

T. Sakthivel
Firstsoft Technologies Private Limited, Chennai, Tamil Nadu, India
Allam Balaram
Department of Information Technology, MLR Institute of Technology, Hyderabad, Telangana, India

Abstract


Multi-hop Wireless Networks (MWNs) emerge as an enabling communication technology, evolving rapidly due to the accelerating advancements and creating potential network applications that significantly improve the quality of life. Pure general-purpose MANET laid the theoretical foundation for MWNs, and many extensions are successfully deployed in commercial networks. This article surveys geographical routing protocols and mobility models applicable to MWNs and their recently proposed extensions. Mobility is a significant factor that profoundly impacts the performance of multi-hop geographical routing. This study analyzes various mobility models that significantly influence the performance of geographical routing protocols based on the characteristics and behavior of various network extensions. This survey investigates the primary challenges in designing geographical routing for various mobility models that notably impact the routing performance for a particular network extension. It also explores the enormous potential of geographical routing protocols under each extension and adequately addressing the routing and mobility-related issues. The essential factors that impact geographical routing, the freshness of location information, and the adaptive location update are examined extensively for various network extensions. Finally, the survey concludes with future research challenges and directions.

Keywords


Multihop Wireless Networks, Geographical Routing, Mobility Models, MANET, FANET, WSN, VANET, DTN.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209993