Energy-Efficient Network Architectures for High-performance Cloud Computing

References

[1] Al‑Fares, M., Loukissas, A., & Vahdat, A. (2008). A scalable, commodity data center network architecture. ACM SIGCOMM Computer Communication Review, 38(4), 63–74.

[2] Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy‑aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5), 755–768.

[3] Calheiros, R. N., Ranjan, R., Beloglazov, A., De Rose, C. A., & Buyya, R. (2011). CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Software: Practice and Experience, 41(1), 23–50.

[4] Dimitrakopoulos, G. (2011). Intelligent transportation systems based on internet-connected vehicles: Fundamental research areas and challenges. In 2011 11th International Conference on ITS Telecommunications, ITST 2011 (pp. 145–151). https://doi.org/10.1109/ITST.2011.6060042

[5] Fang, C., Yu, F. R., Huang, T., Liu, J., & Liu, Y. (2015). A survey of green information-centric networking: Research issues and challenges. IEEE Communications Surveys and Tutorials, 17(3), 1455–1472. https://doi.org/10.1109/COMST.2015.2394307

[6] Gupta, L., Jain, R., & Vaszkun, G. (2016). Survey of Important Issues in UAV Communication Networks. IEEE Communications Surveys and Tutorials, 18(2), 1123–1152. https://doi.org/10.1109/COMST.2015.2495297

[7] Greenberg, A., Hamilton, J. R., Jain, N., Kandula, S., Kim, C., Lahiri, P., … & Sengupta, S. (2009). VL2: A scalable and flexible data center network. ACM SIGCOMM Computer Communication Review, 39(4), 51–62.

[8] Jangid, J. (2023). Enhancing security and efficiency in wireless mobile networks through blockchain. International Journal of Intelligent Systems and Applications in Engineering, 11(4), 958–969. https://www.ijisae.org/index.php/IJISAE/article/view/7309

[9] Jiang, X., Wang, X., & Li, Y. (2013). Energy‑efficient network design in cloud data centers. IEEE Transactions on Cloud Computing, 1(2), 123–133.

[10] Hossain, E., Bhargava, V. K., & Fettweis, G. P. (2012). Green radio communication networks. Green Radio Communication Networks (Vol. 9781107017542, pp. 1–410). Cambridge University Press. https://doi.org/10.1017/CBO9781139084284

[11] Kreutz, D., Ramos, F. M. V., Verissimo, P. E., Rothenberg, C. E., Azodolmolky, S., & Uhlig, S. (2015). Software-defined networking: A comprehensive survey. Proceedings of the IEEE, 103(1), 14–76. https://doi.org/10.1109/JPROC.2014.2371999

[12] Kim, H., & Feamster, N. (2013). Improving network management with software defined networking. IEEE Communications Magazine, 51(2), 114–119. https://doi.org/10.1109/MCOM.2013.6461195

[13] Kliazovich, D., Bouvry, P., & Khan, S. (2012). Energy‑efficient resource management in cloud computing data centers. IEEE Transactions on Cloud Computing, 1(1), 58–68.

[14] Lantz, B., Heller, B., & McKeown, N. (2010). A network in a laptop: Rapid prototyping for software-defined networks. In Proceedings of the 9th ACM Workshop on Hot Topics in Networks, Hotnets-9. https://doi.org/10.1145/1868447.1868466

[15] Machireddy, Jeshwanth, Harnessing AI and Data Analytics for Smarter Healthcare Solutions (January 14, 2023). International Journal of Science and Research Archive, 2023, 08(02), 785-798 , Available at SSRN: http://dx.doi.org/10.2139/ssrn.5159750

[16] Malhotra, S., Saqib, M., Mehta, D., & Tariq, H. (2023). Efficient algorithms for parallel dynamic graph processing: A study of techniques and applications. International Journal of Communication Networks and Information Security, 15(2), 519–534. https://www.ijcnis.org/index.php/ijcnis/article/view/7990

[17] Mao, M., Li, J., & Humphrey, M. (2010). Cloud computing: A perspective study. New Generation Computing, 28(2), 137–146.Mell, P., & Grance, T. (2011). The NIST definition of cloud computing. NIST Special Publication 800‑145.

[18] Machireddy, Jeshwanth, Automation in Healthcare Claims Processing: Enhancing Efficiency and Accuracy(April 16, 2023). International Journal of Science and Research Archive, 2023, 09(01), 825-834, Available at SSRN: https://ssrn.com/abstract=5159747 or http://dx.doi.org/10.2139/ssrn.5159747

[19] Nunes, B. A. A., Mendonca, M., Nguyen, X. N., Obraczka, K., & Turletti, T. (2014). A survey of software-defined networking: Past, present, and future of programmable networks. IEEE Communications Surveys and Tutorials, 16(3), 1617–1634. https://doi.org/10.1109/SURV.2014.012214.00180

[20] Wu, J., Zhang, Y., Zukerman, M., & Yung, E. K. N. (2015). Energy-efficient base-stations sleep-mode techniques in green cellular networks: A survey. IEEE Communications Surveys and Tutorials, 17(2), 803–826. https://doi.org/10.1109/COMST.2015.2403395

[21] Yu, F. R., Zhang, X., & Leung, V. C. M. (2016). Green communications and networking. Green Communications and Networking (pp. 1–360). CRC Press. https://doi.org/10.1201/9780429344213-10

[22] Yashu, F., Saqib, M., Malhotra, S., Mehta, D., Jangid, J., & Dixit, S. (2021). Thread mitigation in cloud native application development. Webology, 18(6), 10160–10161. https://www.webology.org/abstract.php?id=5338

[23] Zheng, Q., & Ma, Z. (2014). Energy‑efficient network architectures for data centers. IEEE Access, 2, 1101–1109.

[24] Zhang, Q., Cheng, L., & Boutaba, R. (2010). Cloud computing: State‑of‑the‑art and research challenges. Journal of Internet Services and Applications, 1(1), 7–18.

@article{1707652,
      author = {ONI Samuel Boluwatife},
      title = {Energy-Efficient Network Architectures for High-performance Cloud Computing},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {6},
      pages = {474-483},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1707652.pdf},
      abstract = {Cloud computing growth creates higher energy needs that create major environmental and financial problems for businesses. Network design for cloud systems helps reduce power usage while promoting top-level performance when these systems expand. This research analyzes the latest SDN NFV and AI techniques to create energy-efficient network infrastructure for cloud computing systems. We study important methods for automatic resource management as well as routing choices that save energy plus green data center planning. The research shares details about effective network energy use steps and demonstrates this practice with actual business examples. It also explains how balancing energy savings and network capabilities impacts security levels. The essay shows ways to advance sustainable cloud infrastructure design through its review of energy-saving networking issues and modern development paths. The study helps researchers find better ways to lower cloud service impacts on the environment while maintaining network stability and speed.},
      keywords = {Energy-efficient cloud computing, Green networking architectures, Software-Defined Networking (SDN), AI-driven network optimization, Network Function Virtualization (NFV).},
      month = {December},
  }