Taufiq Odhi Dwi Putra, Adi S. S. Ansyah, Miftahol Arifin, Royyana M. Ijtihadie


Replication is a data distribution technique for synchronization between databases so that data remains consistent. Replication can overcome data loss problems and perform system recovery quickly if a problem occurs on one of the servers. One of the problems is when a natural disaster occurs at the server location. As a result, if you do not have data replication in different locations, it will cause the system to not run and possibly lose data. Then, geo-replication can reduce latency because the distance between the client and the data center is much closer. The application of geo-replication in general replicates data in all data centers. As a result, the cost of implementation is high because it requires a lot of resources. Because of the various advantages and disadvantages in its application, it is necessary to group geo-replication techniques to make it easier for researchers and technicians to adjust as needed. Therefore, this paper surveys the articles on Geo-replication techniques to implement cost-effectiveness and latency. The articles surveyed included a method for selecting replication sites, a method for reducing round trip time, a method according to data type, and selecting a leader to determine which server node to use. The results of the article survey show that implementing geo-replication for cost-effectiveness is more suitable for use in systems where all users do not need to access all data. Meanwhile, low latency is more suitable for systems used by various types of users. This paper can utilize the techniques that have been reviewed to overcome the problem of cost-effectiveness and latency in implementing Geo-replication.

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T. K. Pandey, I. Singh, dan M. Kumar, “Replication in Distributed Systems and its Improvements,” Int. J. Curr. Microbiol. Appl. Sci., vol. 8, no. 05, hlm. 446–451, Mei 2019, doi: 10.20546/ijcmas.2019.805.052.

P. Fouto, J. Leitão, dan N. Preguiça, “Practical and Fast Causal Consistent Partial Geo-Replication,” dalam 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Nov 2018, hlm. 1–10. doi: 10.1109/NCA.2018.8548067.

AbdullahMSFT, “Active geo-replication - Azure SQL Database.” (diakses 22 Desember 2022).

N. Preguiça, M. Zawirski, A. Bieniusa, S. Duarte, V. Balegas, C. Baquero, dan M. Shapiro, “SwiftCloud: Fault-Tolerant Geo-Replication Integrated all the Way to the Client Machine,” dalam 2014 IEEE 33rd International Symposium on Reliable Distributed Systems Work-shops, Okt 2014, hlm. 30–33. doi: 10.1109/SRDSW.2014.33.

A. Asco, “Optimising Data Access with an Adaptive Geo-Replication Strategy,” Int. J. Swarm Intell. Evol. Comput., vol. 7, no. 3, hlm. 1–10, 2018, doi: 10.4172/2090-4908.1000171.

S. Liu dan M. Vukolić, “Leader Set Selection for Low-Latency Geo-Replicated State Machine,” IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 7, hlm. 1933–1946, Jul 2017, doi: 10.1109/TPDS.2016.2636148.

G. Kaki, S. Priya, K. Sivaramakrishnan, dan S. Jagannathan, “Mergeable Replicated Data Types,” Proc ACM Program Lang, vol. 3, no. OOPSLA, Okt 2019, doi: 10.1145/3360580.

M. F. Mohamed, “Service replication taxonomy in distributed environments,” Serv. Oriented Comput. Appl., vol. 10, no. 3, hlm. 317–336, Sep 2016, doi: 10.1007/s11761-015-0189-7.

A. S. M. Noor, N. F. M. Zian, dan F. N. M. S. Bahri, “Survey on replication techniques for distributed system,” Int. J. Electr. Comput. Eng. IJECE, vol. 9, no. 2, Art. no. 2, Apr 2019, doi: 10.11591/ijece.v9i2.pp1298-1303.

B. Alami Milani dan N. Jafari Navimipour, “A comprehensive review of the data replication techniques in the cloud environments: Major trends and future directions,” J. Netw. Comput. Appl., vol. 64, hlm. 229–238, Apr 2016, doi: 10.1016/j.jnca.2016.02.005.

P. Padmanabhan, L. Gruenwald, A. Vallur, dan M. Atiquzzaman, “A survey of data replication techniques for mobile ad hoc network databases,” VLDB J., vol. 17, no. 5, hlm. 1143–1164, Agu 2008, doi: 10.1007/s00778-007-0055-0.

A. Shakarami, M. Ghobaei-Arani, A. Shahidinejad, M. Masdari, dan H. Shakarami, “Data replication schemes in cloud computing: a sur-vey,” Clust. Comput., vol. 24, no. 3, hlm. 2545–2579, Sep 2021, doi: 10.1007/s10586-021-03283-7.

B. A. Milani dan N. J. Navimipour, “A Systematic Literature Review of the Data Replication Techniques in the Cloud Environments,” Big Data Res., vol. 10, hlm. 1–7, Des 2017, doi: 10.1016/j.bdr.2017.06.003.

W. Li, Y. Yang, dan D. Yuan, “A Novel Cost-Effective Dynamic Data Replication Strategy for Reliability in Cloud Data Centres,” dalam 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing, Des 2011, hlm. 496–502. doi: 10.1109/DASC.2011.95.

“Latency is Everywhere and it Costs You Sales - How to Crush it - High Scalability -.” (diakses 22 Desember 2022).

P. Matri, A. Costan, G. Antoniu, J. Montes, dan M. S. Pérez, “Towards Efficient Location and Placement of Dynamic Replicas for Geo-Distributed Data Stores,” dalam Proceedings of the ACM 7th Workshop on Scientific Cloud Computing, New York, NY, USA, 2016, hlm. 3–9. doi: 10.1145/2913712.2913715.

T. Mahmood, S. P. Narayanan, S. Rao, T. N. Vijaykumar, dan M. Thottethodi, “Karma: Cost-Effective Geo-Replicated Cloud Storage with Dynamic Enforcement of Causal Consistency,” IEEE Trans. Cloud Comput., vol. 9, no. 1, hlm. 197–211, Jan 2021, doi: 10.1109/TCC.2018.2842184.

A. Cidon, R. Escriva, S. Katti, M. Rosenblum, dan E. G. Sirer, “Tiered replication: A cost-effective alternative to full cluster geo-replication,” dalam 2015 USENIX Annual Technical Conference (USENIX ATC 15), 2015, hlm. 31–43.

Z. Wu, C. Yu, dan H. V. Madhyastha, “CosTLO: Cost-effective redundancy for lower latency variance on cloud storage services,” dalam 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI 15), 2015, hlm. 543–557.

Z. Wu, M. Butkiewicz, D. Perkins, E. Katz-Bassett, dan H. V. Madhyastha, “Spanstore: Cost-effective geo-replicated storage spanning multiple cloud services,” dalam Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles, 2013, hlm. 292–308.

Z. Wu dan H. V. Madhyastha, “Cost-Effective Geo-Distributed Storage for Low-Latency Web Services.,” IEEE Data Eng Bull, vol. 40, no. 4, hlm. 26–40, 2017.

H. Yoon, A. Gavrilovska, dan K. Schwan, “Attribute-Based Partial Geo-Replication System,” dalam 2016 IEEE International Conference on Cloud Engineering (IC2E), Apr 2016, hlm. 127–130. doi: 10.1109/IC2E.2016.29.

D. House, H. Kuang, K. Surendran, dan P. Chen, “Toward Fast and Reliable Active-Active Geo-Replication for a Distributed Data Caching Service in the Mobile Cloud,” Procedia Comput. Sci., vol. 191, hlm. 119–126, Jan 2021, doi: 10.1016/j.procs.2021.07.018.

J. Zhou, J. Fan, J. Jia, B. Cheng, dan Z. Liu, “Location-Aware Data Placement for Geo-Distributed Online Social Networks,” dalam 2016 International Conference on Advanced Cloud and Big Data (CBD), Agu 2016, hlm. 234–239. doi: 10.1109/CBD.2016.048.

H. Khalajzadeh, D. Yuan, J. Grundy, dan Y. Yang, “Cost-Effective Social Network Data Placement and Replication Using Graph-Partitioning,” dalam 2017 IEEE International Conference on Cognitive Computing (ICCC), Jun 2017, hlm. 64–71. doi: 10.1109/IEEE.ICCC.2017.16.

H. Moniz, J. Leitão, R. J. Dias, J. Gehrke, N. Preguiça, dan R. Rodrigues, “Blotter: Low Latency Transactions for Geo-Replicated Storage,” dalam Proceedings of the 26th International Conference on World Wide Web, Republic and Canton of Geneva, CHE, 2017, hlm. 263–272. doi: 10.1145/3038912.3052603.

C. Gunawardhana, M. Bravo, dan L. Rodrigues, “Unobtrusive Deferred Update Stabilization for Efficient ${$Geo-Replication$}$,” dalam 2017 USENIX Annual Technical Conference (USENIX ATC 17), 2017, hlm. 83–95.

K. Ren, D. Li, dan D. J. Abadi, “Slog: Serializable, low-latency, geo-replicated transactions,” Proc. VLDB Endow., vol. 12, no. 11, 2019.

P. Coelho dan F. Pedone, “GeoPaxos+: Practical Geographical State Machine Replication,” dalam 2021 40th International Symposium on Reliable Distributed Systems (SRDS), Sep 2021, hlm. 233–243. doi: 10.1109/SRDS53918.2021.00031.

P. Matri, M. S. Pérez, A. Costan, L. Bougé, dan G. Antoniu, “Keeping up with storage: Decentralized, write-enabled dynamic geo-replication,” Future Gener. Comput. Syst., vol. 86, hlm. 1093–1105, Sep 2018, doi: 10.1016/j.future.2017.06.009.

M. Eischer, B. Straßner, dan T. Distler, “Low-latency geo-replicated state machines with guaranteed writes,” dalam Proceedings of the 7th Workshop on Principles and Practice of Consistency for Distributed Data, 2020, hlm. 1–9.



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