Bir doğal afet sonrası mobil iletişim ağının restorasyonu: Kadıköy, İstanbul için bir vaka çalışması

Öz

Doğal bir afetin ardından, mobil iletişim ağları ve diğer altyapılar genellikle zarar görür. Ancak, afet sonrası iyileşme faaliyetlerinde sağlıklı ve güvenilir iletişim hayati bir rol oynar. Özellikle mobil ağ sağlayıcıları, afet sonrası iletişim iyileştirme girişimlerine başlamıştır. Bu çalışmada, kapsama ve kapasite kısıtları altında mobil baz istasyonlarının yerleştirilmesi sorununa yönelik matematiksel bir model önerilmektedir. Model, mevcut mobil baz istasyonu ağı, acil toplanma noktaları, acil toplanma noktalarındaki kişi sayısı ve doğal afetten sonra hizmet vermeye devam edebilen mevcut mobil baz istasyonlarını açıkça dikkate almaktadır. Modelin genel amacı, afet bölgesindeki tüm kazazedeler için minimum maliyetle mobil iletişimi sağlamaktır. Sonuç olarak, afetten etkilenmeyen mevcut baz istasyonları, afet sonrası senaryolarda yeni kurulacak baz istasyonlarının yerini ve kapasitesini belirlemede kritik bir rol oynamaktadır. Bu anlamda, çalışmamız, afet sonrası ortamda yeni mobil baz istasyonlarının yerleştirilmesinde kısmen operasyonel bir mobil iletişim ağını dikkate alan nadir çalışmalardan biridir. Sunulan model, İstanbul, Kadıköy ilçesine odaklanarak, 199 mevcut baz istasyonu ve 150 acil toplanma noktası ile gerçek dünya verileri üzerinde test edilmiştir. Mevcut mobil baz istasyonlarının hala çalışır durumda olanlarının sayısı, doğal afetin şiddetine büyük ölçüde bağlı olduğundan, çeşitli senaryolar geliştirilmiştir. Sonuçlar, önemli yönetsel içgörüler elde etmek için kapsamlı bir şekilde analiz edilmiştir.

Anahtar Kelimeler

• Afet Sonrası İyileşme
• afet yönetimi
• mobil iletişim ağı
• kapasiteli küme kapsama problemi
• ağ restorasyonu

Restoring the Mobile Communication Network After a Natural Disaster: A Case Study for Kadikoy, Istanbul

Öz

Following a natural disaster, mobile communication networks along with the rest of the infrastructure are often damaged. However, in the post-disaster recovery activities, healthy and reliable communication plays a crucial role. Especially mobile network providers started initiatives for post-disaster communication recovery. This study presents a mathematical model for location-allocation problem of mobile base stations under coverage and capacity constraints. The model explicitly considers existing mobile base station network, emergency collection points, number of people in the emergency collection points as well as percentage of existing mobile base stations that survived the natural disaster. The overall objective of the model is to enable mobile communication for all survivors in the disaster area with minimum cost possible. Consequently, existing base stations that are not affected by the disaster plays a crucial role in determining the location and the capacity of the new base stations to be established in post-disaster scenarios. In this sense, our study is one of the very few that takes into account a partially operational mobile communication network in locating new mobile base stations in a post-disaster environment. Presented model is tested on a problem with real world data, focusing on Kadikoy district of Istanbul, Türkiye, with 199 existing base stations and 150 emergency collection points. Since the number of mobile base stations that are still operational highly depends on the severity of the natural disaster, several scenarios are developed. The results are thoroughly analyzed to obtain important managerial insights.

Anahtar Kelimeler

• Post-disaster Recovery
• disaster management
• mobile communication network
• capacitated set covering problem
• network restoration

Kaynakça

1. 1. World Bank: Fixed Telephone Subscriptions. https://data.worldbank.org/indicator/IT.MLT.MAIN Erişim tarihi: 10.05.2024
2. 2. World Bank: Mobile Cellular Subscriptions. https://data.worldbank.org/indicator/IT.CEL.SETS Erişim tarihi: 10.05.2024
3. 3. Berawi, M.A., Leviakangas, P., Siahaan, S.A.O., Hafidza, A., Sari, M., Miraj, P., Harwahyu, R., Saroji, G.: Increasing disaster victim survival rate: Savemylife mobile application development. International Journal of Disaster Risk Reduction 60, 102290, 2021.
4. 4. Han, D.C., Takabatake, T., Esteban, M., Shibayama, T.: Development and implementation of a smartphone application for tsunami evacuation. International Journal of Disaster Risk Reduction 96, 103915, 2023.
5. 5. Salvati, P., Ardizzone, F., Cardinali, M., Fiorucci, F., Fugnoli, F., Guzzetti, F., Marchesini, I., Rinaldi, G., Rossi, M., Santangelo, M., Vujica, I.: Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection. International Journal of Disaster Risk Reduction 55, 102087, 2021.
6. 6. Dai, K., Cheng, C., Shen, S., Su, K., Zheng, X., Zhang, T.: Postearthquake situational awareness based on mobile phone signaling data: An example from the 2017 jiuzhaigou earthquake. International Journal of Disaster Risk Reduction 69, 102736, 2022.
7. 7. Ghafoori, H.R., Sadeghi-Niaraki, A., Alesheikh, A.A., Choi, S.-M.: Ubiquitous GIS based outdoor evacuation assistance: An effective response to earthquake disasters. International Journal of Disaster Risk Reduction 81, 103232, 2022.
8. 8. Parsons, T., Toda, S., Stein, R.S., Barka, A., Dieterich, J.H.: Heightened odds of large earthquakes near istanbul: An interaction-based probability calculation. Science 288 (5466), 661–665, 2000.

9. 9. Selim, S.Z., Almoghathawi, Y.A., Aldajani, M.: Optimal base stations location and configuration for cellular mobile networks. Wireless Networks, 21 (1), 13–19, 2015.
10. 10. Mc Grath, F.: Mobile Network Restoration and Humanitarian Response. GSMA (2014). https://www.gsma.com/mobilefordevelopment/wp-content/uploads/2014/02/Mobile-Network-Restoration-and-Humanitarian-Response.pdf Accessed 10.05.2024
11. 11. Karp, R.M.: In: Miller, R.E., Thatcher, J.W., Bohlinger, J.D. (eds.) Reducibility among Combinatorial Problems, 85–103, Springer, Boston, MA, 1972.
12. 12. Christofides, N., Korman, S.: Note-a computational survey of methods for the set covering problem. Management Science 21 (5), 591–599, 1975.
13. 13. Yu, C., Subramanian, S., Jain, N.: CDMA cell site optimization using a set-covering algorithm. In: Proceedings of the 8th International Telecommunication Network Planning Symposium, Sorrento, Italy, 1998.
14. 14. Mathar, R., Schmeink, M.: Optimal base station positioning and channel assignment for 3g mobile networks by integer programming. Annals of Operations Research, 107 (1), 225–236, 2001.
15. 15. Singh, W., Sengupta, J.: An efficient algorithm for optimizing base station site selection to cover a convex square region in cell planning. Wireless Personal Communications, 72 (2), 823–841, 2013.
16. 16. Özdağ R., 3D location optimization of multiple Unmanned Aerial Vehicle Base Stations in nextgeneration cellular networks and a new meta-heuristic approach, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (3), 1467-1482, 2021.
17. 17. Dogusgen Erbas C., Dual-band and dual-mode annular ring microstrip patch antenna with slots for GSM-1800 and GPS operations, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (1), 547-556, 2022.
18. 18. Rawat, P., Haddad, M., Altman, E.: Towards efficient disaster management: 5G and device to device communication. In: 2015 2nd International Conference on Information and Communication Technologies for Disaster Management (ICTDM), 79–87, 2015. IEEE
19. 19. Deepak, Ladas, A., Sambo, Y.A., Pervaiz, H., Politis, C., Imran, M.A.: An overview of post-disaster emergency communication systems in the future networks. IEEE Wireless Communications 26 (6), 132–139, 2019.
20. 20. Matracia, M., Saeed, N., Kishk, M.A., Alouini, M.-S.: Post-Disaster Communications: Enabling Technologies, Architectures, and Open Challenges. IEEE Open Journal of the Communications Society, 3, 1177-1205, 2022.
21. 21. Wang, Q., Li, W., Yu, Z., Abbasi, Q., Imran, M., Ansari, S., Sambo, Y., Wu, L., Li, Q., Zhu, T.: An overview of emergency communication networks. Remote Sensing 15 (6), 1595, 2023.
22. 22. Yazar, Y., & Eren, T., Afet Sonrası Taşınabilir Baz İstasyonu Yer Seçimi: Bingöl Şehir Merkezi Örneği. Politeknik Dergisi, 28 (1), 1-12, 2025.
23. 23. Çavdur F., Sebatlı Sağlam A., Köse Küçük M., A scenario-based decision support system for allocating temporary-disaster-response facilities, Journal of the Faculty of Engineering and Architecture of Gazi University, 36 (3), 1499-1514, 2021.
24. 24. Avlar E., Limoncu S., Tızman D., Post-earthquake temporary housing unit: CLT E-BOX, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (1), 471-482, 2022.
25. 25. Çiftçi S., Sakallı Ü.S., A mathematical modelling approach for planning health resources after earthquake: Kırıkkale city example, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (2), 1203-1216, 2022.
26. 26. Yoruk E., Baykasoğlu A. Research on employing containers as pre-disaster storage units to enhance the effectiveness of post-disaster operations, Journal of the Faculty of Engineering and Architecture of Gazi University, 40 (2), 815-828, 2025.
27. 27. AA Inman, J. (1821). Navigation and Nautical Astronomy for Seamen. Portsmouth: Royal Naval College.
28. 28. Google: Kadıköy İlçesi GSM Baz İstasyonları Gözlem, Ölçüm ve Çevresel İnceleme Haritası 2023 - Google My Maps (2023). https://www.google.com/maps/d/viewer?mid=1LJLRMZunSljtyTYeBXEOj3y-NH0&hl=en US&ll=40.9823455938499%2C29.037361704505884&z=13 Erişim tarihi: 10.05.2024
29. 29. Li, D., Chen, H., Shen, W., Ye, M.: An analysis of the temporal and spatial gathering and dispersion patterns of crowds at the community level after the 2020 m5.1 tangshan guye earthquake. International Journal of Disaster Risk Reduction 61, 102331, 2021.
30. 30. Appelhans, T., Detsch, F., Reudenbach, C., Woellauer, S.: Mapview: Interactive Viewing of Spatial Data in R. 2023. R package version 2.11.2. https://github.com/r-spatial/mapview Erişim tarihi: 10.05.2024.