Abstract
We live in a connected world where billions of smartphones, as well as conventional computers, are used daily, resulting in an exponential growth of data to be shared as quickly as possible. Also, the concept of parallel computing has been addressed for many years, but many researchers have focused on conventional computers. Keeping in mind that it is essential for many distributed databases to retain ACID (Atomicity, Coherence, Isolation, Sustainability) properties despite their low availability, which is a direct consequence of the strict implementation of ACID (academic and industrial observation). We propose a state-of-the-art method based on the parallel calculation of the grid that will use the available computing power of all inactive devices (smartphone and PC) to increase the read operation on hybrid data storages.
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References
Cost–benefit analysis – evaluation model of cloud computing deployment for use in companies. Appl. Econ. 49(6). https://www.tandfonline.com/doi/abs/10.1080/00036846.2016.1200188?scroll=top&needAccess=true&journalCode=raec20
Cocco, L., Pinna, A., Marchesi, M.: Banking on blockchain: costs savings thanks to the blockchain technology. Future Internet 9, 25 (2017). https://doi.org/10.3390/fi9030025
Maresova, P., Sobeslav, V., Krejcar, O.: Cost–benefit analysis–evaluation model of cloud computing deployment for use in companies. Appl. Econ. 49, 521–533 (2017). https://doi.org/10.1080/00036846.2016.1200188
Average Storage Capacity in Smartphones to Cross 80 GB by End-2019 (2019). https://www.counterpointresearch.com/average-storage-capacity-smartphones-cross-80gb-end-2019/
Kemp, S., We are social, Hootsuite: Digital in 2017: Global Overview (2017). https://wearesocial.com/blog/2017/01/digital-in-2017-global-overview
Digital in 2018: World’s internet users pass the 4 billion mark (2018). https://wearesocial.com/us/blog/2018/01/global-digital-report-2018
Gemayel, N.: Analyzing google file system and Hadoop distributed file system. Res. J. Inf. Technol. 8, 66–74 (2016). https://doi.org/10.3923/rjit.2016.66.74
Nikam, P.P., Suryawanshi, R.S.: Microsoft Windows Azure: developing applications for highly available storage of cloud. Int. J. Sci. Res. 4, 662–665 (2015)
Kitamura, M., et al.: Beyond 4 K: 8 K 60p live video streaming to multiple sites. Future Gener. Comput. Syst. 27, 952–959 (2011). https://doi.org/10.1016/j.future.2010.11.025
Pérez-Miguel, C., Mendiburu, A., Miguel-Alonso, J.: Modeling the availability of Cassandra. J. Parallel Distrib. Comput. 86, 29–44 (2015). https://doi.org/10.1016/j.jpdc.2015.08.001
Lucchese, F.: From P2P to NoSQL: a continuous metric for classifying large-scale storage systems. J. Parallel Distrib. Comput. 113, 227–249 (2018). https://doi.org/10.1016/j.jpdc.2017.11.017
Adya, A., et al.: FARSITE: federated, available, and reliable storage for an incompletely trusted environment. In: Proceedings of the 5th Symposium on Operating Systems Design and Implementation (OSDI), pp. 1–14 (2002). https://doi.org/10.1145/1060289.1060291
Yang, J.: From Google file system to omega: a decade of advancement in big data management at Google. In: Proceedings - 2015 IEEE 1st International Conference on Big Data Computing Service and Applications, BigDataService 2015, pp. 249–255 (2015). https://doi.org/10.1109/BigDataService.2015.47
Edwards, W.K., Mynatt, E.D., Petersen, K., Spreitzer, M.J., Terry, D.B., Theimer, M.M.: Designing and implementing asynchronous collaborative applications with Bayou. In: Proceedings of the 10th Annual ACM Symposium on User Interface Software and Technology - UIST 1997, pp. 119–128 (1997). https://doi.org/10.1145/263407.263530
Zhang, H., Chen, G., Ooi, B.C., Tan, K.-L., Zhang, M.: In-memory big data management and processing: a survey. IEEE Trans. Knowl. Data Eng. 27, 1920–1948 (2015). https://doi.org/10.1109/TKDE.2015.2427795
Kang, Y.-S., Park, I.-H., Rhee, J., Lee, Y.-H.: MongoDB-Based Repository design for IoT-generated RFID/sensor big data. IEEE Sens. J. 16, 485–497 (2016). https://doi.org/10.1109/JSEN.2015.2483499
Olteanu, D., Zavodny, J.: Size bounds for factorised representations of query results. ACM Trans. Database Syst. 40, 2 (2015). https://doi.org/10.1145/2656335
DeCandia, G., et al.: Dynamo: Amazon’s highly available key-value store. In: Proceedings of the Symposium on Operating Systems Principles, pp. 205–220 (2007). https://doi.org/10.1145/1323293.1294281
Sobeslav, V., Balik, L., Hornig, O., Horalek, J., Krejcar, O.: Endpoint firewall for local security hardening in academic research environment. J. Intell. Fuzzy Syst. 32, 1475–1484 (2017). https://doi.org/10.3233/JIFS-169143
Gray, J., Helland, P., O’Neil, P., Shasha, D.: The dangers of replication and a solution. ACM SIGMOD Rec. 25, 173–182 (1996). https://doi.org/10.1145/235968.233330
Karger, D., Lehman, E., Leighton, T., Panigrahy, R., Levine, M., Lewin, D.: Consistent hashing and random trees. In: Proceedings of the Twenty-Ninth Annual ACM Symposium on Theory of Computing - STOC 1997, pp. 654–663 (1997). https://doi.org/10.1145/258533.258660
Ramachandran, V.: Let’s Talk about UX—Principles of User Interface Elements (2019). https://medium.com/nyc-design/lets-talk-about-ux-principles-of-user-interface-elements-125ea165c6d
image_slicer@github.com
Serrano-Alvarado, P., Roncancio, C., Adiba, M.: A survey of mobile transactions. Distrib. Parallel Databases 16, 193–230 (2004). https://doi.org/10.1023/B:DAPD.0000028552.69032.f9
Mambou, S., Krejcar, O., Kuca, K., Selamat, A.: novel human action recognition in RGB-D videos based on powerful view invariant features technique. In: Sieminski, A., Kozierkiewicz, A., Nunez, M., Ha, Q.T. (eds.) Modern Approaches for Intelligent Information and Database Systems. SCI, vol. 769, pp. 343–353. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76081-0_29
Mambou, S., Krejcar, O., Kuca, K., Selamat, A.: Novel cross-view human action model recognition based on the powerful view-invariant features technique. Future Internet 10, 89 (2018). https://doi.org/10.3390/fi10090089
Mambou, S., Krejcar, O., Selamat, A.: Approximate outputs of accelerated turing machines closest to their halting point. In: Nguyen, N.T., Gaol, F.L., Hong, T.-P., Trawiński, B. (eds.) ACIIDS 2019. LNCS (LNAI), vol. 11431, pp. 702–713. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-14799-0_60
Mambou, S., Krejcar, O., Maresova, P., Selamat, A., Kuca, K.: Novel four stages classification of breast cancer using infrared thermal imaging and a deep learning model. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds.) IWBBIO 2019. LNCS, vol. 11466, pp. 63–74. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17935-9_7
Mambou, S.J., Maresova, P., Krejcar, O., Selamat, A., Kuca, K.: Breast cancer detection using infrared thermal imaging and a deep learning model. Sensors (Basel) 18 (2018). https://doi.org/10.3390/s18092799
Mambou, S., Maresova, P., Krejcar, O., Selamat, A., Kuca, K.: Breast cancer detection using modern visual IT techniques. In: Sieminski, A., Kozierkiewicz, A., Nunez, M., Ha, Q.T. (eds.) Modern Approaches for Intelligent Information and Database Systems. SCI, vol. 769, pp. 397–407. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76081-0_34
Acknowledgement
The work was supported by the SPEV project “Smart Solutions in Ubiquitous Computing Environments”, 2019, University of Hradec Kralove, FIM, Czech Republic.
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Mambou, S., Krejcar, O., Selamat, A., Kuca, K. (2019). Hybrid Distributed Computing System Based on Canvas and Dynamo. In: Awan, I., Younas, M., Ünal, P., Aleksy, M. (eds) Mobile Web and Intelligent Information Systems. MobiWIS 2019. Lecture Notes in Computer Science(), vol 11673. Springer, Cham. https://doi.org/10.1007/978-3-030-27192-3_22
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DOI: https://doi.org/10.1007/978-3-030-27192-3_22
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