A Fog Assisted Cloud Paradigm for Accessibility and Collaboration to Genomic Data Analysis
DOI:
https://doi.org/10.37135/unach.ns.001.02.08Keywords:
Big data, Cloud computing, Distributed resource management, Fog computing, Next-generation sequencing (NGS)Abstract
Increasingly growing Next-generation sequencing requires large-scale computing resources to handle the huge amount of data produced. The Cloud computing paradigm readily handles huge data but the core issue with this paradigm is transfer of enormous data to and from cloud computers due to limited bandwidth which lies in the centralized nature of a Cloud computing architecture that is located far away from users. An architecture where computing power is distributed more evenly throughout the network is the way to combat this problem. The architecture should drive the processing capacity towards the edge of the network, closer to the source of the data. For this propose Fog computing offers a promising solution to move computational capabilities closer to the data generated and will be the solution to gain traction in genomics research. We propose a novel Collaborative-Fog (Co-Fog) model that adopts the Fog and Cloud computing paradigms to manage huge genomic data sets and to enable understanding of how key stakeholders can manage the interaction and collaboration. The present work describes the Co-Fog model that promises increased performance, energy efficiency, reduced latency, faster response time, scalability, and better localized accuracy for future large-scale collaborations in genomics.
Downloads
Download data is not yet available.
References
- Anawar, M. R., Wang, S., Azam Zia, M., Jadoon, A. K., Akram, U., and Raza, S. (2018). Fog computing: An overview of big iot data analytics. Wireless Communications and Mobile Computing, 2018.
- Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., et al. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
- Baccarelli, E., Naranjo, P. G. V., Scarpiniti, M., Shojafar, M., and Abawajy, J. H. (2017). Fog of everything: Energy-efficient networked computing architectures, research challenges, and a case study. IEEE access, 5, 9882-9910.
- Baccarelli, E., Scarpiniti, M., Naranjo, P. G. V., and Vaca-Cardenas, L. (2018). Fog of social iot: When the fog becomes social. IEEE Network, 32(4), 68-80.
- Bernstein, D. (2014). Containers and cloud: From lxc to docker to kubernetes. IEEE Cloud Computing, 1(3), 81-84.
- Bonomi, F. Connected vehicles, the internet of things, and fog computing. In The Eighth ACM International Workshop on Vehicular Inter-Networking (VANET), Las Vegas, USA, pp. 13-15.
- Bonomi, F., Milito, R., Natarajan, P., and Zhu, J. (2014). Fog computing: A platform for internet of things and analytics. In Big Data and Internet of Things: A Roadmap for Smart Environments, pp. 169-186. Springer.
- Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pp. 13-16. ACM.
- Botta, A., De Donato, W., Persico, V., and Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700.
- Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., and Brandic, I. (2009). Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems, 25(6), 599-616.
- Byers, C. C. and Wetterwald, P. (2015). Fog computing distributing data and intelligence for resiliency and scale necessary for {IoT}: The internet of things (ubiquity symposium). Ubiquity, 2015 (November), 4.
- Charlebois, K., Palmour, N., and Knoppers, B. M. (2016). The adoption of cloud computing in the field of genomics research: the influence of ethical and legal issues. PloS one, 11 (10), e0164347.
- DNAnexus (2018). A global network for genomics. https://www.dnanexus.com/company.
- Dove, E. S., Joly, Y., Tassé, A.-M., in Genomics, P. P. P., Committee, S. P. I. S., Burton, P., Chisholm, R., Fortier, I., Goodwin, P., Harris, J., et al. (2015). Genomic cloud computing: legal and ethical points to consider. European Journal of Human Genetics, 23(10), 1271.
- ENCODE (2018). Encyclopedia of dna elements. https://www.encodeproject.org/.
- Firdhous, M., Ghazali, O., and Hassan, S. Fog computing: Will it be the future of cloud computing? In The Third International Conference on Informatics & Applications (ICIA2014).
- Forer, L., Schönnherr, S., Weißensteiner, H., Specht, G., Kronenberg, F., and Kloss-Brandst, A. (2012). Cloud computing computational medicine. Computational Medicine.
- Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., and Stoica, I. (2009). Above the clouds: A berkeley view of cloud computing. Dept. Electrical Eng. and Comput. Sciences, University of California, Berkeley, Rep. UCB/EECS, 28(13), 2009.
- Genomics, E. (2018). Data driven innovation. https://www.eaglegenomics.com/tag/aws/.
- Group, N. P. (2017). The clinical cancer genome task team of the global alliance for genomics and health. sharing clinical and genomic data on cancer - the need for global solutions. N. Engl. J. Med., 376, 2006-2009.
- Horne, J. (2018). Social implications of big data and fog computing. International Journal of Fog Computing (IJFC), 1(2), 1-50.
- ICGC (2018). International cancer genome consortium. https://www.nhlbi.nih.gov/science/trans-omics-precision-medicine-topmed-program.
- Kai, K., Cong, W., and Tao, L. (2016). Fog computing for vehicular ad-hoc networks: paradigms, scenarios, and issues. The Journal of China Universities of Posts and Telecommunications, 23(2), 56-96.
- Langmead, B. and Nellore, A. (2018). Cloud computing for genomic data analysis and collaboration. Nature Reviews Genetics, 19 (4), 208.
- Luan, T. H., Gao, L., Li, Z., Xiang, Y., and Sun, L. (2015). Fog computing: Focusing on mobile users at the edge, arXiv preprint arXiv:1502.01815.
- Madsen, H., Burtschy, B., Albeanu, G., and Popentiu-Vladicescu, F. Reliability in the utility computing era: Towards reliable fog computing. In Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on, pp. 43-46. IEEE.
- Mell, P., Grance, T., et al. (2011). The nist definition of cloud computing. NIST.
- modENCODE (2018). The national human genome research institute model organism encyclopedia of dna elements. http://www.modencode.org/.
- Naranjo, P. G. V., Shojafar, M., Vaca-Cardenas, L., Canali, C., Lancellotti, R., and Baccarelli, E. Big data over smartgrid — a fog computing perspective. In Proceedings of the 24th International Conference on Software, Telecommunications and Computer Networks, pp. 22-24. SoftCOM 2016. NCBI (2018). Sequence read archive. https://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi
- Nellore, A., Jaffe, A. E., Fortin, J.-P., Alquicira-Hernández, J., Collado-Torres, L., Wang, S., Phillips III, R. A., Karbhari, N., Hansen, K. D., Langmead, B., et al. (2016). Human splicing diversity and the extent of unannotated splice junctions across human rna-seq samples on the sequence read archive. Genome biology, 17 (1), 266.
- NIH (2014).Trans-omics for precision medicine (topmed) program. https://www.nhlbi.nih.gov/science/trans-omics-precision-medicine-topmed-program.
- NIST (2018a). Definition of cloud computing. https://csrc.nist.gov/publications/detail/sp/800-145/final.
- NIST (2018b). Fog computing conceptual model. https://www.nist.gov/news-events/news/2018/03/nist-releases-special-publication-500-325\- fog-computing-conceptual-model.
- Portnoy, M. (2012). Virtualization essentials, volume 19. John Wiley & Sons.
- Ruiter, J. and Warnier, M. (2011). Privacy regulations for cloud computing: Compliance and implementation in theory and practice. In Computers, privacy and data protection: an element of choice, pp. 361-376. Springer.
- Saharan, K. and Kumar, A. (2015). Fog in comparison to cloud: A survey. International Journal of Computer Applications, 122(3).
- Shanker, A. (2012). Genome research in the cloud. Omics: a journal of integrative biology, 16 (7-8), 422-428.
- Soltesz, S., Potzl, H., Fiuczynski, M. E., Bavier, A., and Peterson, L. Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors. In ACM SIGOPS Operating Systems Review, pp. 275-287. ACM.
- Tang, B., Chen, Z., Hefferman, G., Pei, S., Wei, T., He, H., and Yang, Q. (2017). Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Transactions on Industrial informatics, 13(5), 2140-2150.
- Xu, X., Yu, H., and Pei, X. A novel resource scheduling approach in container based clouds. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on, pp. 257-264. IEEE.
- Zhang, Q., Liu, L., Pu, C., Dou, Q., Wu, L., and Zhou, W. (2018). A comparative study of containers and virtual machines in big data environment. arXiv preprint arXiv:1807.01842.
- Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., et al. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50-58.
- Baccarelli, E., Naranjo, P. G. V., Scarpiniti, M., Shojafar, M., and Abawajy, J. H. (2017). Fog of everything: Energy-efficient networked computing architectures, research challenges, and a case study. IEEE access, 5, 9882-9910.
- Baccarelli, E., Scarpiniti, M., Naranjo, P. G. V., and Vaca-Cardenas, L. (2018). Fog of social iot: When the fog becomes social. IEEE Network, 32(4), 68-80.
- Bernstein, D. (2014). Containers and cloud: From lxc to docker to kubernetes. IEEE Cloud Computing, 1(3), 81-84.
- Bonomi, F. Connected vehicles, the internet of things, and fog computing. In The Eighth ACM International Workshop on Vehicular Inter-Networking (VANET), Las Vegas, USA, pp. 13-15.
- Bonomi, F., Milito, R., Natarajan, P., and Zhu, J. (2014). Fog computing: A platform for internet of things and analytics. In Big Data and Internet of Things: A Roadmap for Smart Environments, pp. 169-186. Springer.
- Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pp. 13-16. ACM.
- Botta, A., De Donato, W., Persico, V., and Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700.
- Buyya, R., Yeo, C. S., Venugopal, S., Broberg, J., and Brandic, I. (2009). Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation computer systems, 25(6), 599-616.
- Byers, C. C. and Wetterwald, P. (2015). Fog computing distributing data and intelligence for resiliency and scale necessary for {IoT}: The internet of things (ubiquity symposium). Ubiquity, 2015 (November), 4.
- Charlebois, K., Palmour, N., and Knoppers, B. M. (2016). The adoption of cloud computing in the field of genomics research: the influence of ethical and legal issues. PloS one, 11 (10), e0164347.
- DNAnexus (2018). A global network for genomics. https://www.dnanexus.com/company.
- Dove, E. S., Joly, Y., Tassé, A.-M., in Genomics, P. P. P., Committee, S. P. I. S., Burton, P., Chisholm, R., Fortier, I., Goodwin, P., Harris, J., et al. (2015). Genomic cloud computing: legal and ethical points to consider. European Journal of Human Genetics, 23(10), 1271.
- ENCODE (2018). Encyclopedia of dna elements. https://www.encodeproject.org/.
- Firdhous, M., Ghazali, O., and Hassan, S. Fog computing: Will it be the future of cloud computing? In The Third International Conference on Informatics & Applications (ICIA2014).
- Forer, L., Schönnherr, S., Weißensteiner, H., Specht, G., Kronenberg, F., and Kloss-Brandst, A. (2012). Cloud computing computational medicine. Computational Medicine.
- Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., and Stoica, I. (2009). Above the clouds: A berkeley view of cloud computing. Dept. Electrical Eng. and Comput. Sciences, University of California, Berkeley, Rep. UCB/EECS, 28(13), 2009.
- Genomics, E. (2018). Data driven innovation. https://www.eaglegenomics.com/tag/aws/.
- Group, N. P. (2017). The clinical cancer genome task team of the global alliance for genomics and health. sharing clinical and genomic data on cancer - the need for global solutions. N. Engl. J. Med., 376, 2006-2009.
- Horne, J. (2018). Social implications of big data and fog computing. International Journal of Fog Computing (IJFC), 1(2), 1-50.
- ICGC (2018). International cancer genome consortium. https://www.nhlbi.nih.gov/science/trans-omics-precision-medicine-topmed-program.
- Kai, K., Cong, W., and Tao, L. (2016). Fog computing for vehicular ad-hoc networks: paradigms, scenarios, and issues. The Journal of China Universities of Posts and Telecommunications, 23(2), 56-96.
- Langmead, B. and Nellore, A. (2018). Cloud computing for genomic data analysis and collaboration. Nature Reviews Genetics, 19 (4), 208.
- Luan, T. H., Gao, L., Li, Z., Xiang, Y., and Sun, L. (2015). Fog computing: Focusing on mobile users at the edge, arXiv preprint arXiv:1502.01815.
- Madsen, H., Burtschy, B., Albeanu, G., and Popentiu-Vladicescu, F. Reliability in the utility computing era: Towards reliable fog computing. In Systems, Signals and Image Processing (IWSSIP), 2013 20th International Conference on, pp. 43-46. IEEE.
- Mell, P., Grance, T., et al. (2011). The nist definition of cloud computing. NIST.
- modENCODE (2018). The national human genome research institute model organism encyclopedia of dna elements. http://www.modencode.org/.
- Naranjo, P. G. V., Shojafar, M., Vaca-Cardenas, L., Canali, C., Lancellotti, R., and Baccarelli, E. Big data over smartgrid — a fog computing perspective. In Proceedings of the 24th International Conference on Software, Telecommunications and Computer Networks, pp. 22-24. SoftCOM 2016. NCBI (2018). Sequence read archive. https://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi
- Nellore, A., Jaffe, A. E., Fortin, J.-P., Alquicira-Hernández, J., Collado-Torres, L., Wang, S., Phillips III, R. A., Karbhari, N., Hansen, K. D., Langmead, B., et al. (2016). Human splicing diversity and the extent of unannotated splice junctions across human rna-seq samples on the sequence read archive. Genome biology, 17 (1), 266.
- NIH (2014).Trans-omics for precision medicine (topmed) program. https://www.nhlbi.nih.gov/science/trans-omics-precision-medicine-topmed-program.
- NIST (2018a). Definition of cloud computing. https://csrc.nist.gov/publications/detail/sp/800-145/final.
- NIST (2018b). Fog computing conceptual model. https://www.nist.gov/news-events/news/2018/03/nist-releases-special-publication-500-325\- fog-computing-conceptual-model.
- Portnoy, M. (2012). Virtualization essentials, volume 19. John Wiley & Sons.
- Ruiter, J. and Warnier, M. (2011). Privacy regulations for cloud computing: Compliance and implementation in theory and practice. In Computers, privacy and data protection: an element of choice, pp. 361-376. Springer.
- Saharan, K. and Kumar, A. (2015). Fog in comparison to cloud: A survey. International Journal of Computer Applications, 122(3).
- Shanker, A. (2012). Genome research in the cloud. Omics: a journal of integrative biology, 16 (7-8), 422-428.
- Soltesz, S., Potzl, H., Fiuczynski, M. E., Bavier, A., and Peterson, L. Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors. In ACM SIGOPS Operating Systems Review, pp. 275-287. ACM.
- Tang, B., Chen, Z., Hefferman, G., Pei, S., Wei, T., He, H., and Yang, Q. (2017). Incorporating intelligence in fog computing for big data analysis in smart cities. IEEE Transactions on Industrial informatics, 13(5), 2140-2150.
- Xu, X., Yu, H., and Pei, X. A novel resource scheduling approach in container based clouds. In Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on, pp. 257-264. IEEE.
- Zhang, Q., Liu, L., Pu, C., Dou, Q., Wu, L., and Zhou, W. (2018). A comparative study of containers and virtual machines in big data environment. arXiv preprint arXiv:1807.01842.
Additional Files
Published
2018-12-12
Issue
Section
Research Articles and Reviews
How to Cite
A Fog Assisted Cloud Paradigm for Accessibility and Collaboration to Genomic Data Analysis. (2018). Novasinergia, ISSN 2631-2654, 1(2), 70-82. https://doi.org/10.37135/unach.ns.001.02.08
