Analisis Komprehensif Tantangan Implementasi Network Slicing pada Jaringan 5G Menggunakan Metode Systematic Literature Review
DOI:
https://doi.org/10.61722/jipm.v4i2.2279Keywords:
Network Slicing in 5G, Network slicing architecture, Network slicing security, 5G Network Virtualization, 5G Network Slicing ChallengesAbstract
Perkembangan jaringan 5G menghadirkan konsep network slicing sebagai solusi untuk mendukung beragam layanan dengan kebutuhan yang heterogen dalam satu infrastruktur jaringan terpadu. Namun, implementasinya menghadapi berbagai tantangan yang kompleks dan saling berkaitan. Penelitian ini bertujuan untuk mengidentifikasi dan menganalisis tantangan implementasi network slicing secara komprehensif melalui pendekatan Systematic Literature Review (SLR). Metode yang digunakan mengacu pada pedoman Kitchenham serta kerangka PRISMA dengan menganalisis literatur dari berbagai basis data ilmiah dalam periode 2020–2025. Hasil kajian menunjukkan bahwa tantangan implementasi network slicing bersifat multidimensi, mencakup aspek teknis, operasional, dan keamanan yang saling berinteraksi. Pada aspek teknis, tantangan utama meliputi kompleksitas orkestrasi end-to-end, alokasi sumber daya dinamis, isolasi antar-slice, serta interoperabilitas multi-domain. Pada aspek operasional, permasalahan muncul dalam pemenuhan Service Level Agreement (SLA), skalabilitas, serta kebutuhan otomasi jaringan. Sementara itu, pada aspek keamanan, peningkatan attack surface akibat virtualisasi dan lingkungan multi-tenant menjadi isu kritis. Selain itu, hasil penelitian mengungkap adanya hubungan kausal antar tantangan serta trade-off antara efisiensi, isolasi, dan keamanan. Kebaruan penelitian ini terletak pada penyusunan sintesis literatur yang terintegrasi lintas aspek serta identifikasi hubungan antar tantangan secara komprehensif. Temuan ini diharapkan dapat menjadi dasar dalam pengembangan solusi adaptif untuk mendukung implementasi network slicing pada jaringan generasi mendatang.
References
Afolayan, A. O., Taleb, T., Samdanis, K., & Ksentini, A. (2022). Network slicing and softwarization: A survey on principles, enabling technologies, and solutions. IEEE Communications Surveys & Tutorials, 24(1), 245–289. https://doi.org/10.1109/COMST.2021.3119121.
Dias, J., Pinto, P., Santos, R., & Malta, S. (2025). 5G network slicing: Security challenges, attack vectors, and mitigation approaches. Sensors, 25(13), 3940. https://doi.org/10.3390/s25133940.
Efunogbon, A., Liu, E., Qiu, R., & Efunogbon, T. (2025). Optimal 5G network sub-slicing orchestration in a fully virtualised smart company using machine learning. Future Internet, 17(2), 69. https://doi.org/10.3390/fi17020069.
Gao, S., Lin, R., Fu, Y., Li, H., & Cao, J. (2024). Security threats, requirements and recommendations on creating 5G network slicing system: A survey. Electronics, 13(10), 1860. https://doi.org/10.3390/electronics13101860.
Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report, Keele University and Durham University.
Li, X., Samdanis, K., Taleb, T., Corici, M., Fu, Y., & Elmokashfi, A. (2021). Network slicing for 5G: Challenges and opportunities. IEEE Internet Computing, 25(3), 20–27. https://doi.org/10.1109/MIC.2021.3056675.
Martins, J. S. B., Carvalho, T. C., Moreira, R., Both, C. B., Donatti, A., Corrêa, J. H., & Silva, F. D. O. (2023). Enhancing network slicing architectures with machine learning, security, sustainability and experimental networks integration. IEEE Access, 11, 69144–69163. https://doi.org/10.1109/ACCESS.2023.3290000.
Masoudi, M., Demir, Ö. T., Zander, J., & Cavdar, C. (2022). Energy-optimal end-to-end network slicing in cloud-based architecture. IEEE Open Journal of the Communications Society, 3, 574–592. https://doi.org/10.1109/OJCOMS.2022.3150000.
Min, Z., Gokhale, S., Shekhar, S., Mahmoudi, C., Kang, Z., Barve, Y., & Gokhale, A. (2024). Enhancing 5G network slicing for IoT traffic with a novel clustering framework. Pervasive and Mobile Computing, 104, 101974. https://doi.org/10.1016/j.pmcj.2023.101974.
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLOS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097.
Singh, S. K., Salim, M. M., Cha, J., Pan, Y., & Park, J. H. (2020). Machine learning-based network sub-slicing framework in a sustainable 5G environment. Sustainability, 12(15), 6250. https://doi.org/10.3390/su12156250.
Subedi, R., Nguyen, T. H., & Jung, H. (2021). A comprehensive survey on 5G network slicing: Architecture and challenges. IEEE Access, 9, 110842–110867. https://doi.org/10.1109/ACCESS.2021.3102300.
Wijethilaka, S., & Liyanage, M. (2021). Survey on network slicing for Internet of Things realization in 5G networks. IEEE Communications Surveys & Tutorials, 23(2), 957–994. https://doi.org/10.1109/COMST.2021.3055905
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 JURNAL ILMIAH PENELITIAN MAHASISWA

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.










