Synthesis of articles, question and analysis
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References
Baresi, L., & Garriga, M. (2019). Microservices: The Evolution and Extinction of Web Services? Microservices, 3–28. https://doi.org/10.1007/978-3-030-31646-4_1
Baškarada, S., Nguyen, V., & Koronios, A. (2018). Architecting Microservices: Practical Opportunities and Challenges. Journal of Computer Information Systems, 1–9. https://doi.org/10.1080/08874417.2018.1520056
Berman, E. (2017). An Exploratory Sequential Mixed Methods Approach to Understanding Researchers' Data Management Practices at UVM: Findings from the Quantitative Phase. Journal of EScience Librarianship, 6(1), e1098. https://doi.org/10.7191/jeslib.2017.1098
Brogi, A., Neri, D., & Soldani, J. (2018). A microservice-based architecture for (customizable) analyses of Docker images. Software: Practice and Experience, 48(8), 1461–1474. https://doi.org/10.1002/spe.2583
Celozzi, C. (2020, December 2). How Door Dash transitioned from a code monolith to microservices. Door Dash Engineering Blog. https://doordash.engineering/2020/12/02/how-doordash-transitioned-from-a-monolith-to-microservices/
Di Francesco, P., Lago, P., & Malavolta, I. (2019). Architecting with microservices: A systematic mapping study. Journal of Systems and Software, 150, 77–97. https://doi.org/10.1016/j.jss.2019.01.001
Habadi, A., Samih, Y., Almehdar, K., & Aljedani, E. (2017). An Introduction to ERP Systems: Architecture, Implementation, and Impacts. International Journal of Computer Applications, 167(9), 1–4. https://doi.org/10.5120/ijca2017914322
Kazanavičius, J., & Mažeika, D. (2019, April 1). I am migrating Legacy Software to Microservices Architecture. IEEE Xplore. https://doi.org/10.1109/eStream.2019.8732170
Khazaei, H., Barna, C., Beigi-Mohammadi, N., & Litoiu, M. (2016). Efficiency Analysis of Provisioning Microservices. 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom). https://doi.org/10.1109/cloudcom.2016.0051
Laigner, R., Zhou, Y., Salles, M. A. V., Liu, Y., & Kalinowski, M. (2021). Data Management in Microservices: State of the Practice, Challenges, and Research Directions. ArXiv: 2103.00170 [Cs]. https://arxiv.org/abs/2103.00170
Nawaz, N., & Channakeshavalu. (2013). The Impact of Enterprise Resource Planning (ERP) Systems Implementation on Business Performance. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3525298
Plutora. (2019, June 28). Understanding Microservices and Their Impact on Companies. Plutora. https://www.plutora.com/blog/understanding-microservices
Sampaio, A. R., Rubin, J., Beschastnikh, I., & Rosa, N. S. (2019). Improving microservice-based applications with runtime placement adaptation. Journal of Internet Services and Applications, 10(1). https://doi.org/10.1186/s13174-019-0104-0
Sandoe, K., & Olfman, L. (1992). Anticipating the mnemonic shift: Organizational remembering and forgetting in 2001. INTERNATIONAL CONFERENCE on INFORMATION SYSTEMS (ICIS), 1–12. https://core.ac.uk/download/pdf/301364184.pdf
Singh, V., & K Peddoju, S. (2017). Container-based microservice architecture for cloud applications. International Conference on Computing, Communication, and Automation (ICCCA), 847–852. https://doi.org/10.1109/CCAA.2017.8229914.
Siong Choy, C., & Yong Suk, C. (2005). Critical Factors In The Successful Implementation Of Knowledge Management. Journal of Knowledge Management Practice, 6(1), 234–258. http://www.tlainc.com/articl90.htm
Stubbs, J., Moreira, W., & Dooley, R. (2015, June 1). Distributed Systems of Microservices Using Docker and Serfnode. IEEE Xplore; 7th International Workshop on Science Gateways, Budapest, Hungary. https://doi.org/10.1109/IWSG.2015.16
J. Stubbs, W. Moreira and R. Dooley, "Distributed Systems of Microservices Using Docker and Serfnode," 2015 7th International Workshop on Science Gateways, Budapest, Hungary, 2015, pp. 34-39, doi: 10.1109/IWSG.2015.16.
Swoyer, M. L., Steve. (2020, July 15). Microservices Adoption in 2020. O'Reilly Media. https://www.oreilly.com/radar/microservices-adoption-in-2020/
Tapia, F., Mora, M. Á., Fuertes, W., Aules, H., Flores, E., & Toulkeridis, T. (2020). From Monolithic Systems to Microservices: A Comparative Study of Performance. Applied Sciences, 10(17), 5797. https://doi.org/10.3390/app10175797
Villamizar, M., Garces, O., Ochoa, L., Castro, H., Salamanca, L., Verano, M., Casallas, R., Gil, S., Valencia, C., Zambrano, A., & Lang, M. (2016). Infrastructure Cost Comparison of Running Web Applications in the Cloud Using AWS Lambda and Monolithic and Microservice Architectures. 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid). https://doi.org/10.1109/ccgrid.2016.37
Vrîncianu, M., Anica-Popa, L., & Anica-Popa, I. (2009). Organizational Memory: an Approach from Knowledge Management and Quality Management of Organizational Learning Perspectives. The AMFITEATRU ECONOMIC Journal, 11(26), 473–481. https://ideas.repec.org/a/aes/amfeco/v11y2009i26p473-482.html
Baboi, M., Iftene, A., & Gîfu, D. (2019). Dynamic Microservices to Create Scalable and Fault Tolerance Architecture. Procedia Computer Science, 159, 1035–1044. https://doi.org/10.1016/j.procs.2019.09.271
CHAN JIANLI1, D., AL-RASHDAN, M., & AL-MAATOUK, Q. (2020). SECURE DATA STORAGE SYSTEM. Journal of Critical Reviews, 7(03). https://doi.org/10.31838/jcr.07.03.18
Al-Debagy, O., & Martinek, P. (2019). A Comparative Review of Microservices and Monolithic Architectures. ArXiv:1905.07997 [Cs]. http://arxiv.org/abs/1905.07997
AL-Mandi, M. A., & AL-Sharjabi, A. (2020, December 1). Level of Effectiveness for ERP System in Improving the Educational Process in Higher Education Institutions in Yemen: A Case Study of the University of Science and Technology. المجلة العربية لضمان جودة التعليم الجامعي. https://doaj.org/article/e2f955aaa2d34ae9af4ec375d9db8cb7
Balalaie, A., Heydarnoori, A., Jamshidi, P., Tamburri, D. A., & Lynn, T. (2018). Microservices migration patterns. Software: Practice and Experience. https://doi.org/10.1002/spe.2608
Bergquist, N. R. (2001). A concept for the collection, consolidation and presentation of epidemiological data. Acta Tropica, 79(1), 3–5. https://doi.org/10.1016/s0001-706x(01)00132-2
Bhandary, A., & Maslach, D. (2018). Organizational Memory. The Palgrave Encyclopedia of Strategic Management, 1219–1223. https://doi.org/10.1057/978-1-137-00772-8_210
Bindley, P. (2019). Joining the dots: how to approach compliance and data governance. Network Security, 2019(2), 14–16. https://doi.org/10.1016/s1353-4858(19)30023-6
Boniecki, R., & Rawłuszko, J. (2018). ON THE DEVELOPMENT OF THE ERP SYSTEM IN THE PROCESSING-TRANSPORTING ENTERPRISES. Ekonomiczne Problemy Usług, 131, 49–56. https://doi.org/10.18276/epu.2018.131/1-05
Booth, C., & Rowlinson, M. (2006). Management and organizational history: Prospects. Management & Organizational History, 1(1), 5–30. https://doi.org/10.1177/1744935906060627
Borgerud, C., & Borglund, E. (2020). Correction to: Open research data, an archival challenge? Archival Science. https://doi.org/10.1007/s10502-020-09335-y
Bose, R. (2006). Understanding management data systems for enterprise performance management. Industrial Management & Data Systems, 106(1), 43–59. https://doi.org/10.1108/02635570610640988
Bruno, G. (2014). A Data-flow Language for Business Process Models. Procedia Technology, 16, 128–137. https://doi.org/10.1016/j.protcy.2014.10.076
Bucchiarone, A., Dragoni, N., Dustdar, S., Larsen, S. T., & Mazzara, M. (2018). From Monolithic to Microservices: An Experience Report from the Banking Domain. IEEE Software, 35(3), 50–55. https://doi.org/10.1109/ms.2018.2141026
Bukari Zakaria, H., & Mamman, A. (2014). Where is the Organisational Memory? A Tale of Local Government Employees in Ghana. Public Organization Review, 15(2), 267–279. https://doi.org/10.1007/s11115-014-0271-1
C. PRIYA, C. P. (2011). Need Based Technology for Innovation. Indian Journal of Applied Research, 4(4), 19–20. https://doi.org/10.15373/2249555x/apr2014/251
Cho, Y.-T., & Kim, I. (2014). The Difference Analyses between Users’ Actual Usage and Perceived Preference: The Case of ERP Functions on Legacy Systems. The Journal of Information Systems, 23(1), 185–202. https://doi.org/10.5859/kais.2014.23.1.185
Dragoni, N., Giallorenzo, S., Lafuente, A. L., Mazzara, M., Montesi, F., Mustafin, R., & Safina, L. (2017). Microservices: Yesterday, Today, and Tomorrow. Present and Ulterior Software Engineering, 195–216. https://doi.org/10.1007/978-3-319-67425-4_12
Ehrhart, M. G., Aarons, G. A., & Farahnak, L. R. (2015). Going above and beyond for implementation: the development and validity testing of the Implementation Citizenship Behavior Scale (ICBS). Implementation Science, 10(1). https://doi.org/10.1186/s13012-015-0255-8
Escobar, D., Cardenas, D., Amarillo, R., Castro, E., Garces, K., Parra, C., & Casallas, R. (2016). Towards the understanding and evolution of monolithic applications as microservices. 2016 XLII Latin American Computing Conference (CLEI). https://doi.org/10.1109/clei.2016.7833410
Esposito, C. (2018). Interoperable, dynamic and privacy-preserving access control for cloud data storage when integrating heterogeneous organizations. Journal of Network and Computer Applications, 108, 124–136. https://doi.org/10.1016/j.jnca.2018.01.017
Ferrari, E. (2010). Access Control in Data Management Systems. Synthesis Lectures on Data Management, 2(1), 1–117. https://doi.org/10.2200/s00281ed1v01y201005dtm004
Fujita, T., & Ogawara, M. (2005). Arbre: A File System for Untrusted Remote Block-level Storage. IPSJ Digital Courier, 1, 381–393. https://doi.org/10.2197/ipsjdc.1.381
Gao, M., Chen, M., Liu, A., Ip, W. H., & Yung, K. L. (2020). Optimization of Microservice Composition Based on Artificial Immune Algorithm Considering Fuzziness and User Preference. IEEE Access, 8, 26385–26404. https://doi.org/10.1109/access.2020.2971379
Gerber, M., & von Solms, R. (2008). Information security requirements – Interpreting the legal aspects. Computers & Security, 27(5-6), 124–135. https://doi.org/10.1016/j.cose.2008.07.009
Giacalone, M., Cusatelli, C., & Santarcangelo, V. (2018). Big Data Compliance for Innovative Clinical Models. Big Data Research, 12, 35–40. https://doi.org/10.1016/j.bdr.2018.02.001
Herrmann, F. (2016). Using Optimization Models for Scheduling in Enterprise Resource Planning Systems. Systems, 4(1), 15. https://doi.org/10.3390/systems4010015
Hujda, K., Marineau, C., & Wick, A. (2016). Maximum Product, Even Less Process: Increasing Efficiencies in Archival Processing Using ArchivesSpace. Journal of Archival Organization, 13(3-4), 100–113. https://doi.org/10.1080/15332748.2018.1443549
Hunter, J., & Cheung, K. (2007). Provenance Explorer-a graphical interface for constructing scientific publication packages from provenance trails. International Journal on Digital Libraries, 7(1-2), 99–107. https://doi.org/10.1007/s00799-007-0018-5
Jiang, L., Xu, L. D., Cai, H., Jiang, Z., Bu, F., & Xu, B. (2014). An IoT-Oriented Data Storage Framework in Cloud Computing Platform. IEEE Transactions on Industrial Informatics, 10(2), 1443–1451. https://doi.org/10.1109/tii.2014.2306384
Johansson, B. (2012). Exploring how open source ERP systems development impact ERP systems diffusion. International Journal of Business and Systems Research, 6(4), 361. https://doi.org/10.1504/ijbsr.2012.049468
K S, G., & T, Prof. P. (2019). A Better Solution Towards Microservices Communication In Web Application: A Survey. International Journal of Innovative Research in Computer Science & Technology, 7(3), 71–74. https://doi.org/10.21276/ijircst.2019.7.3.7
Kaufmann, E., Favretto, J., Filippim, E. S., & Cohen, E. D. (2018). Relationship Between The Organizational Memory and Innovativity: The Case of Software Development Companies in The Southern Region of Brazil. Journal of Information Systems and Technology Management, 16. https://doi.org/10.4301/S1807-1775201916004
Khidzir, N. Z., & Ahmed, S. A.-A.-M. (2018). Big Data Digital Evidences Integrity: Issues, Challenges and Opportunities. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3227714
Kilchenmann, A., Laurens, F., & Rosenthaler, L. (2019). Digitizing, archiving... and then? Ideas about the usability of a digital archive. Archiving Conference, 2019(1), 146–150. https://doi.org/10.2352/issn.2168-3204.2019.1.0.34
Killalea, T. (2016). The hidden dividends of microservices. Communications of the ACM, 59(8), 42–45. https://doi.org/10.1145/2948985
Kornei, K. (2019). More Than a Million New Earthquakes Spotted in Archival Data. Eos, 100. https://doi.org/10.1029/2019eo121757
Kumari, S., Archana, A., Shree, K., Ashwini, A., & M, C. (2019). EFFICIENT BLOCK-WISE IMAGE COMPARISON AND STORAGE REDUCTION USING DICE PROTOCOL. International Journal of Current Engineering and Scientific Research, 6(6), 175–181. https://doi.org/10.21276/ijcesr.2019.6.6.30
Laigner, R., Zhou, Y., Salles, M. A. V., Liu, Y., & Kalinowski, M. (2021). Data Management in Microservices: State of the Practice, Challenges, and Research Directions. ArXiv:2103.00170 [Cs]. http://arxiv.org/abs/2103.00170
Langos, C., & Giancaspro, M. (2015). Does Cloud Storage Lend Itself to Cyberbullying? IEEE Cloud Computing, 2(5), 70–74. https://doi.org/10.1109/mcc.2015.102
LaPolla, F. W. Z., & Rubin, D. (2018). The “Data Visualization Clinic”: a library-led critique workshop for data visualization. Journal of the Medical Library Association, 106(4). https://doi.org/10.5195/jmla.2018.333
Lee, N. C.-A., & Chang, J. Y. T. (2020). Adapting ERP Systems in the Post-implementation Stage: Dynamic IT Capabilities for ERP. Pacific Asia Journal of the Association for Information Systems, 28–59. https://doi.org/10.17705/1pais.12102
Leonhardt, J. M., Trafimow, D., & Niculescu, M. (2016). Selecting Field Experiment Locations with Archival Data. Journal of Consumer Affairs, 51(2), 448–462. https://doi.org/10.1111/joca.12117
Linger, H., Burstein, F., Zaslavsky, A., & Crofts, N. (1999). A Framework for a Dynamic Organizational Memory Information System. Journal of Organizational Computing and Electronic Commerce, 9(2), 189–203. https://doi.org/10.1207/s15327744joce0902&3_6
Maas, J.-B., van Fenema, P. C., & Soeters, J. (2014). ERP system usage: the role of control and empowerment. New Technology, Work and Employment, 29(1), 88–103. https://doi.org/10.1111/ntwe.12021
Marcinauskas, E. (2021, March 1). Research of ERP System integration into Lean Manufacturing. Mokslas: Lietuvos Ateitis. https://doaj.org/article/a6fb6fe1b19d488eb599c8a7b3fd47f1
Marquez, G., Taramasco, C., Astudillo, H., Zalc, V., & Istrate, D. (2021). Involving Stakeholders in the Implementation of Microservice-Based Systems: A Case Study in an Ambient-Assisted Living System. IEEE Access, 9, 9411–9428. https://doi.org/10.1109/access.2021.3049444
Mateus-Coelho, N., Cruz-Cunha, M., & Ferreira, L. G. (2021). Security in Microservices Architectures. Procedia Computer Science, 181, 1225–1236. https://doi.org/10.1016/j.procs.2021.01.320
Mazlami, G., Cito, J., & Leitner, P. (2017). Extraction of Microservices from Monolithic Software Architectures. 2017 IEEE International Conference on Web Services (ICWS). https://doi.org/10.1109/icws.2017.61
Milosch, J. C. (2014). Provenance: Not the Problem (The Solution). Collections, 10(3), 255–264. https://doi.org/10.1177/155019061401000304
Molchanov, H., & Zhmaiev, A. (2018). CIRCUIT BREAKER IN SYSTEMS BASED ON MICROSERVICES ARCHITECTURE. Advanced Information Systems, 2(4), 74–77. https://doi.org/10.20998/2522-9052.2018.4.13
Montesi, F., Peressotti, M., & Picotti, V. (2021). Sliceable Monolith: Monolith First, Microservices Later. ArXiv:2103.09518 [Cs]. http://arxiv.org/abs/2103.09518
Mosleh, M., Dalili, K., & Heydari, B. (2018). Distributed or Monolithic? A Computational Architecture Decision Framework. IEEE Systems Journal, 12(1), 125–136. https://doi.org/10.1109/jsyst.2016.2594290
Narayanan, H. T. S. (2020). Contact Tracing Proximity Data Exchange and Consolidation with App Design. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3691834
Neubert, S., Geißler, A., Roddelkopf, T., Stoll, R., Sandmann, K.-H., Neumann, J., & Thurow, K. (2019). Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources. International Journal of Telemedicine and Applications, 2019, 1–18. https://doi.org/10.1155/2019/9864246
Niu, J. (2014). Original order in the digital world. Archives and Manuscripts, 43(1), 61–72. https://doi.org/10.1080/01576895.2014.958863
Oberle, M. C., & Dreiss, P. (2018). Design and Implementation of a Cyber-Physical Production System for Personalized Skin Care: A Microservices Approach. International Journal of Materials, Mechanics and Manufacturing, 6(4), 295–302. https://doi.org/10.18178/ijmmm.2018.6.4.395
Олещенко, Л. М., & Глінський, В. В. (2017). Microservices system architecture video search vehicles that are wanted in connection of their misappropriation. Problems of Informatization and Management, 1(57-58). https://doi.org/10.18372/2073-4751.1.12794
Onggo, B. S. S., & Hill, J. (2014). Data identification and data collection methods in simulation: a case study at ORH Ltd. Journal of Simulation, 8(3), 195–205. https://doi.org/10.1057/jos.2013.28
Perez, G., & Ramos, I. (2013). Understanding Organizational Memory from the Integrated Management Systems (ERP). Journal of Information Systems and Technology Management, 10(3), 541–560. https://doi.org/10.4301/s1807-17752013000300005
Pylypenko, L., & Redko, M. (2019). ANALYSIS OF THE ADVANTAGES AND DISADVANTAGES OF ERP SYSTEM IMPLEMENTATION IN ENTERPRISES. Pryazovskyi Economic Herald, 6(17). https://doi.org/10.32840/2522-4263/2019-6-33
Rangus, K., & Slavec, A. (2017). The interplay of decentralization, employee involvement and absorptive capacity on firms’ innovation and business performance. Technological Forecasting and Social Change, 120, 195–203. https://doi.org/10.1016/j.techfore.2016.12.017
Ribeiro, F. (2001). Archival science and changes in the paradigm. Archival Science, 1(3), 295–310. https://doi.org/10.1007/bf02437693
Roth, G., & Kleiner, A. (1998). Developing organizational memory through learning histories. Organizational Dynamics, 27(2), 43–60. https://doi.org/10.1016/s0090-2616(98)90023-7
S, M., & Sathayanarayana, S. (2018). Enhanced Big Data Platform for Visualization of Employee Data. JOIV : International Journal on Informatics Visualization, 2(3), 169. https://doi.org/10.30630/joiv.2.3.132
S, Monisha., & Venkateshkumar, Dr. S. (2018). Cloud Computing in Data Backup and Data Recovery. International Journal of Trend in Scientific Research and Development, Volume-2(Issue-6), 865–867. https://doi.org/10.31142/ijtsrd18652
Sangat, P., Indrawan-Santiago, M., & Taniar, D. (2017). Sensor data management in the cloud: Data storage, data ingestion, and data retrieval. Concurrency and Computation: Practice and Experience, 30(1), e4354. https://doi.org/10.1002/cpe.4354
Schafer, G. (2004). Security in data communications: Security in Fixed and Wireless Networks – An introduction to securing data communications. Computer Law & Security Review, 20(5), 431. https://doi.org/10.1016/s0267-3649(04)00081-0
Senko, M. E. (1977). Data structures and data accessing in data base systems past, present, future. IBM Systems Journal, 16(3), 208–257. https://doi.org/10.1147/sj.163.0208
Sergeant, A. M. A., & Sergeant, C. S. (2010). Hidden costs of data storage. Journal of Corporate Accounting & Finance, 21(5), 41–47. https://doi.org/10.1002/jcaf.20610
Slamaa, A. A., El-Ghareeb, H. A., & Saleh, A. A. (2021). A Roadmap for Migration System-Architecture Decision by Neutrosophic-ANP and Benchmark for Enterprise Resource Planning Systems. IEEE Access, 9, 48583–48604. https://doi.org/10.1109/access.2021.3068837
Stokes, T. (2012, October 12). 12. Provenance and Original Order – GXP International. Gxpinternational. https://gxpinternational.com/provenance-original-order/
Sultan, M. (2020). Linking Stakeholders’ Viewpoint Concerns and Microservices-based Architecture. ArXiv:2009.01702 [Cs]. http://arxiv.org/abs/2009.01702
Suresh, S. (2012). Global challenges need global solutions. Nature, 490(7420), 337–338. https://doi.org/10.1038/490337a
Tapia, F., Mora, M. Á., Fuertes, W., Aules, H., Flores, E., & Toulkeridis, T. (2020, August 1). From Monolithic Systems to Microservices: A Comparative Study of Performance. Applied Sciences. https://doaj.org/article/a0df93c43ef04d40a39a81c1f773cc68
Tognoli, N. B., & Guimarães, J. A. C. (2018). Provenance. Www.isko.org. https://www.isko.org/cyclo/provenance
Vans, M., Simske, S., & Scott, Jr., W. (2018). Archiving Information Workflows. Archiving Conference, 2018(1), 75–76. https://doi.org/10.2352/issn.2168-3204.2018.1.0.17
Venugopal, M. V. L. N. (2017). Containerized Microservices architecture. International Journal of Engineering and Computer Science, 6(11). https://doi.org/10.18535/ijecs/v6i11.20
Villamizar, M., Garces, O., Castro, H., Verano, M., Salamanca, L., Casallas, R., & Gil, S. (2015). Evaluating the monolithic and the microservice architecture pattern to deploy web applications in the cloud. 2015 10th Computing Colombian Conference (10CCC). https://doi.org/10.1109/columbiancc.2015.7333476
Wickramasinghe, V., & Gunawardena, V. (2010). Effects of people-centred factors on enterprise resource planning implementation project success: empirical evidence from Sri Lanka. Enterprise Information Systems, 4(3), 311–328. https://doi.org/10.1080/17517570903576413
XIE, H., & CHEN, X. (2013). Cloud storage-oriented unstructured data storage. Journal of Computer Applications, 32(6), 1924–1928. https://doi.org/10.3724/sp.j.1087.2012.01924
Yi, Z., Meilin, W., RenYuan, C., YangShuai, W., & Jiao, W. (2019). Research on Application of SME Manufacturing Cloud Platform Based on Micro Service Architecture. Procedia CIRP, 83, 596–600. https://doi.org/10.1016/j.procir.2019.04.091
Yousif, M. (2016). Microservices. IEEE Cloud Computing, 3(5), 4–5. https://doi.org/10.1109/mcc.2016.101
Yuhuan, Q. (2017). Cloud Storage Technology. Big Data and Cloud Innovation, 1(1). https://doi.org/10.18063/bdci.v1i1.508
Zhao, Y., Zhang, X., Xu, X., & Zhang, S. (2020). Development of composite phase change cold storage material and its application in vaccine cold storage equipment. Journal of Energy Storage, 30, 101455. https://doi.org/10.1016/j.est.2020.101455