Research Difficulties and Possible Green Technology Uses in Cloud Computing
Keywords:
Architecture, Cloud Computing, Internet, Models, SoftwareAbstract
Clouds technology has sparked a great deal of curiosity and competition in the information technology business. As a scaled service distribution platform in the domain of applications computing, it has achieved widespread use. Its technical foundations comprise service-oriented architectures and virtualisation of software and hardware, among other things. The idea is for internet platform users to share their capabilities, cloud collaborators, and cloud providers to create a more efficient source restraint in the clouds. The technologies is confronted with a number of significant challenges, and the current research focuses on the technical problems that arise during the development and delivery of clouds, as well as the ramifications of these concerns for organizations and customers. Cloud computing initiatives are organized according to their technical aspects, and we cover related technologies; breakthroughs in the introduction of procedures, interactions, and norms; methodologies for modeling and establishing clouds; and viability, experimenting, and the prospective that is arising from cloud computing. Clouds technology is a significant step forward in the direction of green computing, which is an environmentally viable eternal computing with a very promising future.
Downloads
References
M. Khatri and A. Kumar, “Stability Inspection of Isolated Hydro Power Plant with Cuttlefish Algorithm,” 2020, doi: 10.1109/DASA51403.2020.9317242.
L. Goswami, M. K. Kaushik, R. Sikka, V. Anand, K. Prasad Sharma, and M. Singh Solanki, “IOT Based Fault Detection of Underground Cables through Node MCU Module,” 2020, doi: 10.1109/ICCSEA49143.2020.9132893.
M. S. Solanki, D. K. P. Sharma, L. Goswami, R. Sikka, and V. Anand, “Automatic Identification of Temples in Digital Images through Scale Invariant Feature Transform,” 2020, doi: 10.1109/ICCSEA49143.2020.9132897.
H. Yang and M. Tate, “A descriptive literature review and classification of cloud computing research,” Commun. Assoc. Inf. Syst., 2012, doi: 10.17705/1cais.03102.
M. S. Solanki, L. Goswami, K. P. Sharma, and R. Sikka, “Automatic Detection of Temples in consumer Images using histogram of Gradient,” 2019, doi: 10.1109/ICCIKE47802.2019.9004324.
A. Kumar and A. Jain, “Image smog restoration using oblique gradient profile prior and energy minimization,” Front. Comput. Sci., 2021, doi: 10.1007/s11704-020-9305- 8.
N. Gupta, K. S. Vaisla, A. Jain, A. Kumar, and R. Kumar, “Performance Analysis of AODV Routing for Wireless Sensor Network in FPGA Hardware,” Comput. Syst. Sci. Eng., 2021, doi: 10.32604/CSSE.2022.019911.
N. Gupta, A. Jain, K. S. Vaisla, A. Kumar, and R. Kumar, “Performance analysis of DSDV and OLSR wireless sensor network routing protocols using FPGA hardware and machine learning,” Multimed. Tools Appl., 2021, doi: 10.1007/s11042-021-10820-4.
B. Gupta, K. K. Gola, and M. Dhingra, “HEPSO: an efficient sensor node redeployment strategy based on hybrid optimization algorithm in UWASN,” Wirel. Networks, 2021, doi: 10.1007/s11276-021-02584-4.
H. Xia, Z. Jia, X. Li, L. Ju, and E. H. M. Sha, “Trust prediction and trust-based source routing in mobile ad hoc networks,” Ad Hoc Networks, 2013, doi: 10.1016/j.adhoc.2012.02.009.
L. D. Radu, “Green cloud computing: A literature survey,” Symmetry. 2017, doi: 10.3390/sym9120295.
P. Gupta and N. Tyagi, “An approach towards big data - A review,” 2015, doi: 10.1109/CCAA.2015.7148356.
L. Bala and A. K. Vatsa, “Quality based Bottom-up Detection and Prevention Techniques for DDOS in MANET,” Int. J. Comput. Appl., 2012, doi: 10.5120/8726- 2412.
R. Sood and M. Kalia, “Cloudbank: A secure anonymous banking cloud,” 2010, doi: 10.1007/978-3-642-14834- 7_28.
P. K. Senyo, E. Addae, and R. Boateng, “Cloud computing research: A review of research themes, frameworks, methods and future research directions,” Int. J. Inf. Manage., 2018, doi: 10.1016/j.ijinfomgt.2017.07.007.
M. Purohit and S. Mushtaq, “Applications of laplace adomian decomposition method for solving time-fractional advection dispersion equation,” J. Math. Comput. Sci., 2020, doi: 10.28919/jmcs/4798.
S. Gupta, D. Kumar, J. Singh, and Sushila, “An Efficient Computational Technique for Nonlinear Emden-Fowler Equations Arising in Astrophysics and Space Science,” 2020, doi: 10.1007/978-3-030-39112-6_5.
J. Singh, M. M. Rashidi, Sushila, and D. Kumar, “A hybrid computational approach for Jeffery–Hamel flow in non parallel walls,” Neural Comput. Appl., 2019, doi: 10.1007/s00521-017-3198-y.
A. Z. Bhat, V. R. Naidu, and B. Singh, “Multimedia Cloud for Higher Education Establishments: A Reflection,” 2019, doi: 10.1007/978-981-13-2285-3_81.
O. Ali, A. Shrestha, J. Soar, and S. F. Wamba, “Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review,” International Journal of Information Management. 2018, doi: 10.1016/j.ijinfomgt.2018.07.009.
N. Abbas, Y. Zhang, A. Taherkordi, and T. Skeie, “Mobile Edge Computing: A Survey,” IEEE Internet of Things Journal. 2018, doi: 10.1109/JIOT.2017.2750180.
H. M. Sabi, F. M. E. Uzoka, K. Langmia, and F. N. Njeh, “Conceptualizing a model for adoption of cloud computing in education,” Int. J. Inf. Manage., 2016, doi: 10.1016/j.ijinfomgt.2015.11.010.
J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, “Internet of Things (IoT): A vision, architectural elements, and future directions,” Futur. Gener. Comput. Syst., 2013, doi: 10.1016/j.future.2013.01.010.
P. Mach and Z. Becvar, “Mobile Edge Computing: A Survey on Architecture and Computation Offloading,” IEEE Communications Surveys and Tutorials. 2017, doi: 10.1109/COMST.2017.2682318.
S. Iqbal, M. L. M. Kiah, N. B. Anuar, B. Daghighi, A. W. A. Wahab, and S. Khan, “Service delivery models of cloud computing: security issues and open challenges,” Security and Communication Networks. 2016, doi: 10.1002/sec.1585.
J. M. Maqueira-Marín, S. Bruque-Cámara, and B. Minguela-Rata, “Environment determinants in business adoption of Cloud Computing,” Ind. Manag. Data Syst., 2017, doi: 10.1108/IMDS-11-2015-0468.