Анализ сетей с нестационарной топологией. Обзор исследований

Анализ сетей с нестационарной топологией. Обзор исследований

Автор: Шахов Владимир Владимирович, Соколова Ольга Дмитриевна

Журнал: Проблемы информатики @problem-info

Рубрика: Теоретическая и системная информатика

Статья в выпуске: 4 (49), 2020 года.

Бесплатный доступ

Статья представляет собой обзор научных публикаций на тему моделирования и анализа беспроводных самоорганизующихся сетей, не имеющих постоянной структуры. Основные задачи функционирования таких сетей связаны со сбором информации, распространением сообщений между движущимися узлами. В статье рассматриваются различные подходы к анализу функционирования сетей, описывается применение соответствующего математического аппарата, сравниваются системы имитационного моделирования.

Нестационарные сети, модели сетей с подвижными узлами, системы массового обслуживания, имитационное моделирование

Короткий адрес: https://sciup.org/143178100

IDR: 143178100   |   DOI: 10.24411/2073-0667-2020-10014

Список литературы Анализ сетей с нестационарной топологией. Обзор исследований

  • Wu X. A Hybrid View of Mobility in MANETs: Analytical Models and Simulation Study // Computer Comm. 2008. Vol. 31. N. 16. P. 3810-3821.
  • Barani, H., Fathv, M. An Algorithm for Localization in Vehicular Ad-Hoc Networks. // Journal of Computer Science. 2010. Vol. 6. N 2. P. 168-172.
  • Liu C., Yang O., Li G, Shu Y. Effective Transmission Coverage Area-Based Link Dynamics Characterization of VANET in Highway Scenario // International Journal of Distributed Sensor Networks. 2015. Vol. 11. N 10.
  • Elhosenv M., Shankar K. Energy Efficient Optimal Routing for Communication in VANETs via Clustering Model. // Emerging Technologies for Connected Internet of Vehicles and Intelligent Transportation System Networks. Studies in Systems, Decision and Control. 2020. Vol. 242.
  • Liu Т., Zhao L., Li В., Zhao C. Research on the Enhancement of VANET Coverage Based on UAV // Liang Q., Wang W., Liu X., Na Z., Jia M., Zhang B. (eds) Communications, Signal Processing, and Systems. CSPS. 2019. Lecture Notes in Electrical Engineering. Vol. 571. Springer, Singapore.
  • Qiu, Z., Wu, L., Zhang, P. An Efficient Localization Method for Mobile Nodes in Wireless Sensor Networks // International Journal of Online Engineering. 2017. Vol. 13. N 3.
  • Sokolova O., Yurgenson A. Using graph, hvpergraph, and hvpernet models for network analysis problems // Proc. 7th International Forum on Strategic Technology (IFOST), 2012.
  • Reddv A. R., Venkatesh D., Ramesh K. Hvpergraph Interference Models in Wireless Ad-Hoc Networks with Low Complexity Distributed Scheduling // International journal of scientific research. 2012. 2. P. 237-240.
  • Webb J., Docemmilli F., Bonin, M. Graph Theory Applications in Network Security // ArXiv.2015. abs/1511.04785.
  • Yang L., Yu Y. Н. A Mobile Frequency Allocation Algorithm Based on the Graph Theory // International Conference on Computer Information Systems and Industrial Applications. 2015.
  • Goldin D., Attia S. A. Unit Disk Graph Based Modelling of a Network of Mobile Agents // Proceedings of the First IFAC Workshop on Estimation and Control of Networked Systems. Venice, Italy. 2009.
  • Сорокин А. А., Дмитриев В. H. Описание систем связи с динамической топологией сети при помощи модели „мерцающего графа" // Вестник АГТУ. Серия: Управление, вычислительная техника и информатика. 2009. № 2. С. 134-139.
  • Eiza М. Н., Ni Q. An Evolving Graph-Based Reliable Routing Scheme for VANETs // IEEE Transactions on Vehicular Technology. 2013. Vol. 62. N. 4. P. 1493-1504.
  • Liu K., Ng J. K. Y., Lee V. C. S., Son S. H., Stojmenovic I. Cooperative Data Scheduling in Hybrid Vehicular Ad Hoc Networks: VANET as a Software Defined Network // IEEE/ACM Transactions on Networking.2016. Vol. 24. N 3. P. 1759-1773.
  • Mokdad, L., Ben-Othman, J., Nguyen, A.T. I). J .WAX: Detecting jamming attacks in Vehicle Ad hoc Networks // Performance Evaluation. 2015. Vol. 87. P. 47-59.
  • Shakhov V., Sokolova O. Towards Air Pollution Detection with Internet of Vehicles // 15th International Asian School-Seminar Optimization Problems of Complex Systems, Novosibirsk, Russia, 2019, P. 183-186.
  • Deng D., Lien S., Lin C., Hung S., Chen W. Latency Control in Software-Defined Mobile-Edge Vehicular Networking // IEEE Communications Magazine. 2017. Vol. 55. N 8, P. 87-93.
  • Zhou S., Sun Y., Jiang Z., Niu Z. Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks // IEEE Communications Magazine. 2019. Vol. 57. N 5. P. 49-55.
  • Zhou Z., Yu H., Xu C., Chang Z., Mumtaz S., Rodriguez J. BEGIN: Big Data Enabled Energy-Efficient Vehicular Edge Computing // IEEE Communications Magazine. 2018. Vol. 56. N 12. P. 82-89.
  • Бертсекас Д., Галлагер P. Сети передачи данных. М.: Мир, 1989.
  • Zhu Н., Fu L., Xue G., Zhu Y., Li M., NiL. M. Recognizing Exponential Inter-Contact Time in VANETs // Proceedings IEEE INFOCOM, San Diego, CA, 2010. P. 1-5.
  • Jiang R., Zhu Y., Yang Y. Improving Throughput and Fairness of Converge cast in Vehicular Networks // IEEE Transactions on Mobile Computing. 2017. Vol. 16. N 11. P. 3070-3083.
  • Li Y., Jin D., Hui P., ChenS. Contact-aware data replication in roadside unit aided vehicular delay tolerant networks // IEEE Transactions on Mobile Computing. 2016. Vol. 15. N 2. P. 306-321.
  • LiuY., Peng M., Shou G., Chen Y., Chen S. Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things // IEEE Internet of Things Journal. 2020. Vol. 7. N 8. P. 6722-6747.
  • Guo H., Liu J., Zhang J. Computation Offloading for Multi-Access Mobile Edge Computing in Ultra-Dense Networks // IEEE Communications Magazine. 2018. Vol. 56. N 8. P. 14-19.
  • Mao Y., You, C. Zhang J., Huang K., Letaief К. B. A Survey on Mobile Edge Computing: The Communication Perspective // IEEE Communications Surveys k, Tutorials. 2017. Vol. 19. N 4. P. 2322-2358.
  • Крылов В. В., Самохвалова С. С. Теория телетрафика и ее приложения // СПб.: БХВ-Петербург, 2005.
  • Hashim М. F., Abdul Razak, N. I. Ultra-Dense Networks: Integration with Device to Device (D2D) Communication // Wireless Personal Communications. 2019. Vol. 106. P. 911-925.
  • Zhang К., Mao, Y. Leng S., He Y., Zhang Y. Mobile-Edge Computing for Vehicular Networks: A Promising Network Paradigm with Predictive Off-Loading // IEEE Vehicular Technology Magazine. 2017. Vol. 12. N 2. P. 36-44.
  • Thai M., Lin Y., Lai Y., Chien H. Workload and Capacity Optimization for Cloud-Edge Computing Systems with Vertical and Horizontal Offloading // IEEE Transactions on Network and Service Management. 2020. Vol. 17. N 1. P. 227-238.
  • 31.Cui L., Xu C., Yang S., Huang J. Z., Li J., Wang X., Ming Z., Lu N. Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things // IEEE Internet of Things Journal. 2019. Vol. 6. P. 4791-4803.
  • Chen Y., Sun Y., Feng T., Li S. A Collaborative Service Deployment and Application Assignment Method for Regional Edge Computing Enabled IoT // IEEE Access. 2020. Vol. 8. P. 112659-112673.
  • Islambouli R., Sharafeddine S. Optimized 3D Deployment of UAV-Mounted Cloudlets to Support Latency-Sensitive Services in IoT Networks // IEEE Access. 2019. Vol. 7. P. 172860-172870.
  • Ebrahimzadeh A., Maier M. Cooperative Computation Offloading in FiWl Enhanced 4G HetNets Using Self-Organizing MEC // IEEE Transactions on Wireless Communications. 2020. Vol. 19. N 7. P. 4480-4493.
  • Wang S., Zhang X., Yan Z., Wenbo W. Cooperative Edge Computing With Sleep Control Under Nonuniform Traffic in Mobile Edge Networks // IEEE Internet of Things Journal. 2019. Vol. 6. N 3. P. 4295-4306.
  • Hajipour J. Stochastic Buffer-Aided Relay-Assisted MEC // IEEE Communications Letters. 2020. Vol. 24. N 4. P. 931-934.
  • Doan T. V., You D., Salah H., Nguyen G. T., Fitzek H. P. F. MEC-assisted Immersive Services: Orchestration Framework and Protocol // IEEE Intern. Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), Jeju, Korea (South), 2019. P. 1-6.
  • Wu S., Xia W., Cui W., Chao Q., Lan Z., Yan F., Shen L. An Efficient Offloading Algorithm Based on Support Vector Machine for Mobile Edge Computing in Vehicular Networks // 10th International Conference on Wireless Communications and Signal Processing (WTCSP), Hangzhou. 2018. P. 1-6.
  • Zhang Q., Chen J., Ji L., Feng Z., Han Z., Chen Z. Response Delay Optimization in Mobile Edge Computing Enabled UAV Swarm // IEEE Transactions on Vehicular Technology. 2020. Vol. 69. N 3. P. 3280-3295.
  • Belogaev A., Elokhin A., Krasilov A., Khorov E., Akvildiz I. F.Cost-Effective V2X Task Offloading in MEC-Assisted Intelligent Transportation Systems // IEEE Access. 2020. Vol. 8. P. 169010-169023.
  • Zhou Z., Yu S., Chen W., Chen X. CE-IoT: Cost-Effective Cloud-Edge Resource Provisioning for Heterogeneous IoT Applications // IEEE Internet of Things Journal. 2020. Vol. 7. N 9. P. 8600-8614.
  • Nguyen M. N. H., Zaw C. W., Kim K., Tran N. H., Hong C. S. Let's Share the Resource WThen We're Co-Located: Co-location Edge Computing // IEEE Transactions on Vehicular Technology. 2020. Vol. 69. N 5. P. 5618-5633.
  • Wang Y., Yang J., Guo X., Qu Z. A Game-Theoretic Approach to Computation Offloading in Satellite Edge Computing // IEEE Access. 2020. Vol. 8. P. 12510-12520.
  • Al-Mavouf Y. R. B., Ismail M., Abdullah N. F., Al-Qaraawi S. M., Mahdi O. A. Survey on VANET technologies and simulation models // ARPN Journal of Engineering and Applied Sciences. 2016. Vol. 11. N 15. P. 9414-9427.
  • Jukic Z., Arshad M. Review of Simulation Based Comparison of VANET Protocols // New Technologies, Development and Application. NT 2018. Lecture Notes in Networks and Systems. Vol. 42. Springer.
  • Sanguesa J. A., Fogue M., Garrido P., Martinez F. J., Cano J.-C., Calafate C. T. A survey and comparative study of broadcast warning message dissemination schemes for VANETs / Mobile Information Systems. 2016, art.ID 8714142, 18 p.
  • Elgazzar M. M. A., Alshareef A. VANET Simulator: Full Design Architecture // International Journal of Engineering and Advanced Technology. 2020. Vol. 9. N 3.
  • Jia D., Lu K., Wang J., Zhang X., Shen X. A Survey on Platoon-Based Vehicular Cyber-Phvsical Systems // IEEE Communications Surveys & Tutorials. 2016. Vol. 18. N 1. P. 263-284."
  • VISSIM. [Electron. Res.]: http://www.ptv-vision.com/en-uk/products/vision-traffic-suite/ptv-vissim/overview/.
  • Harri .J., Fiore M., Bonnet F. Vehicular mobility simulation with Vanet MobiSim /7 Simulation. 2009. Vol. 87. N 4. P. 275 300.
  • Behrisch M., Bicker L., Erdmann .J., Krajzewicz D. SUMO simulation of urban Mobilitv-an overview /7 in Proc. 3rd Int. Conf. Adv. Svst. SIMUL. 2011. P. 63 68.
  • NS-3. [Electron. Res.]: https://www.nsnam.org/.
  • Onmetpp. [Electron. Res.]: www.omnetpp.org.
  • TraNS. [Electron. Res.]: http://lca.epfl.ch/projects/trans/.
  • Рудометов С. В., Соколова О. Д. Моделирование передачи сообщений между движущимися объектами в транспортной среде /7 Пршраммные продукты и системы. 2019. Т. 32. № 1. С. 141 145.
  • Sanguesa .J. A., Fogue M., Garrido P., Martinez F., Cano .J., Calafate C. A Survey and Comparative Study of Broadcast Warning Message Dissemination Schemes for VANETs /7 Mob. Inf. Svst. 2016.
  • Yang F., Wu N., Qiao Y., Zhou M., Su R., Qu T. Modeling and Optimal Cyclic Scheduling of Time-Constrained Single-Robot-Arm Cluster Tools via Petri Nets and Linear Programming /7 IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2020. Vol. 50. N 3. P. 871 883.
  • Alam T., Bobadilla L., Shell D. A. Space-Efficient Filters for Mobile Robot Localization from Discrete Limit Cycles /7 IEEE Robotics and Automation Letters. 2018. Vol. 3. N 1. P. 257 264.
  • Zhang H., Niu M. Modeling and Analysis of Long-Term Average User Throughput in Mobile Ultra Dense Networks /7 IEEE Wireless Communications Letters. 2019. Vol. 8. N 5. P. 1498 1501.
  • Abdel-Aziz M. K., Samarakoon S., Liu C., Bennis M., Saad W. Optimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks /7 IEEE Transactions on Communications. 2020. Vol. 68. К З. P. 1911 1924.
  • Centenaro M., Tomasin S., Benvenuto N., Yang S. Predictive Voice-Over-Internet Protocol Fallback Over Vehicular Channels: Employing Artificial Intelligence at the Edge of 5G Networks /7 IEEE Vehicular Technology Magazine. 2020. Vol. 15. N 2. P. 72 78.
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