Load Balancing Optimization for Green Cloud Environment Using Effective Scheduling
Keywords:Energy sustainability, scheduling, cloud computing, load balancing, Green cloud computing, Energy efficiency, Data centers, Cost, Scheduling, Virtualization, Node, Parallel processing, Schedulers
A solution of the green cloud is not only to save the consumption of energy but expressively reduce operational costs. The main objective is to make the comprehensive computing influence of a vast collection of resources offered to a single application. High consumption of energy is the main concern in green cloud computing because of high computations happened in tightly connected data centers that need managed resources and smooth operations. The research is implemented on green cloud computing based on the scheduling process for energy conservation which is the main concern. The groups deal with the high efficient arrangement in which every industry is required with high uniformity, scalability, and effective performance over different cloud computing scenarios. This research work deals with the efficient performance to achieve efficient load balancing and the optimization process for high energy efficiency which will be the key feature of our proposed system. The proposed work deals with the hybrid scheduling process i.e. priority-based weighted round-robin and minimum completion time to reduce the energy consumption in green cloud systems. The performance will be evaluated for low error rates and achieve high energy efficiency to balance loads of the requests.
Patel, Yashwant Singh, Neetesh Mehrotra, and Swapnil Soner. "Green cloud computing: A review on Green IT areas for the cloud computing environment." In 2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE), pp. 327-332. IEEE, 2015.
Wankhede, Pallavi, Mr Nayan Agrawal, and Ms Jasneet Kaur Saini. "Review on Green Cloud Computing: A Step Towards Saving Global Environment."
Atrey, Ankita, Nikita Jain, and N. Iyengar. "A study on green cloud computing." International Journal of Grid and Distributed Computing 6, no. 6 (2013): 93-102.
Tume-Bruce, B. A. A. ., A. . Delgado, and E. L. . Huamaní. “Implementation of a Web System for the Improvement in Sales and in the Application of Digital Marketing in the Company Selcom”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 5, May 2022, pp. 48-59, doi:10.17762/ijritcc.v10i5.5553.
Radu, Laura-Diana. "Green cloud computing: A literature survey." Symmetry 9, no. 12 (2017): 295.
Jeba, Jenia Afrin, Shanto Roy, Mahbub Or Rashid, Syeda Tanjila Atik, and Md Whaiduzzaman. "Towards green cloud computing an algorithmic approach for energy minimization in cloud data centers." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, pp. 846-872. IGI Global, 2021.
Geetha, P., and CR Rene Robin. "Power conserving resource allocation scheme with improved QoS to promote green cloud computing." Journal of Ambient Intelligence and Humanized Computing (2020): 1-12.
Alarifi, Abdulaziz, Kalka Dubey, Mohammed Amoon, Torki Altameem, Fathi E. Abd El-Samie, Ayman Altameem, S. C. Sharma, and Aida A. Nasr. "Energy-efficient hybrid framework for green cloud computing." IEEE Access 8 (2020): 115356-115369.
Liao, Yongjian, Ganglin Zhang, and Hongjie Chen. "Cost-Efficient Outsourced Decryption of Attribute-Based Encryption Schemes for Both Users and Cloud Server in Green Cloud Computing." IEEE Access 8 (2020): 20862-20869.
Mandal, Riman, Manash Kumar Mondal, Sourav Banerjee, and Utpal Biswas. "An approach toward design and development of an energy-aware VM selection policy with improved SLA violation in the domain of green cloud computing." The Journal of Supercomputing (2020): 1-20.
Sharma, V. N., & Hans, D. A. . (2022). A Study to Reconnoitering the dynamics of Talent Management Procedure at Hotels in Jharkhand. International Journal of New Practices in Management and Engineering, 11(01), 41–46. https://doi.org/10.17762/ijnpme.v11i01.172
Bhattacherjee, Srimoyee, Rituparna Das, Sunirmal Khatua, and Sarbani Roy. "Energy-efficient migration techniques for cloud environment: a step toward green computing." The Journal of Supercomputing 76, no. 7 (2020): 5192-5220.
Zhou, Qiheng, Minxian Xu, Sukhpal Singh Gill, Chengxi Gao, Wenhong Tian, Chengzhong Xu, and Rajkumar Buyya. "Energy efficient algorithms based on VM consolidation for cloud computing: comparisons and evaluations." In 2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), pp. 489-498. IEEE, 2020.
Ghazaly, N. M. . (2022). Data Catalogue Approaches, Implementation and Adoption: A Study of Purpose of Data Catalogue. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 8(1), 01–04. https://doi.org/10.17762/ijfrcsce.v8i1.2063
Ahuja, Sanjay P., and Karthika Muthiah. "Advances in green cloud computing." In Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing, pp. 2651-2662. IGI global, 2021.
Gamsiz, Mustafa, and Ali Haydar Özer. "An energy-aware combinatorial virtual machine allocation and placement model for green cloud computing." IEEE Access 9 (2021): 18625-18648.
Jumde, Monali, and Snehlata Dongre. "Analysis on energy efficient green cloud computing." In Journal of Physics: Conference Series, vol. 1913, no. 1, p. 012100. IOP Publishing, 2021.
Dursun, M., & Goker, N. (2022). Evaluation of Project Management Methodologies Success Factors Using Fuzzy Cognitive Map Method: Waterfall, Agile, And Lean Six Sigma Cases. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 35–43. https://doi.org/10.18201/ijisae.2022.265
Houssein, Essam H., Ahmed G. Gad, Yaser M. Wazery, and Ponnuthurai Nagaratnam Suganthan. "Task scheduling in cloud computing based on meta-heuristics: Review, taxonomy, open challenges, and future trends." Swarm and Evolutionary Computation (2021): 100841.
Muniswamaiah, Manoj, Tilak Agerwala, and Charles C. Tappert. "Green computing for Internet of Things." In 2020 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2020 6th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), pp. 182-185. IEEE, 2020.
Gulati, Rishu, and S. Tyagi. "‘A systematic review on the various approaches used for achieving energy consumption in cloud." TEST Eng. Manage 82 (2020): 3936-3953.
Dougherty, Brian, Jules White, and Douglas C. Schmidt. "Model-driven auto-scaling of green cloud computing infrastructure." Future Generation Computer Systems 28, no. 2 (2012): 371-378.
Hosseinioun, Pejman, Maryam Kheirabadi, Seyed Reza Kamel Tabbakh, and Reza Ghaemi. "A new energy-aware tasks scheduling approach in fog computing using hybrid meta-heuristic algorithm." Journal of Parallel and Distributed Computing 143 (2020): 88-96.
Xu, Xiaolong, Xuyun Zhang, Maqbool Khan, Wanchun Dou, Shengjun Xue, and Shui Yu. "A balanced virtual machine scheduling method for energy-performance trade-offs in cyber-physical cloud systems." Future Generation Computer Systems 105 (2020): 789-799.
Saadi, Youssef, and Said El Kafhali. "Energy-efficient strategy for virtual machine consolidation in cloud environment." Soft Comput. 24, no. 19 (2020): 14845-14859.
N. A. Libre. (2021). A Discussion Platform for Enhancing Students Interaction in the Online Education. Journal of Online Engineering Education, 12(2), 07–12. Retrieved from http://onlineengineeringeducation.com/index.php/joee/article/view/49
Belgacem, Ali, Kadda Beghdad-Bey, Hassina Nacer, and Sofiane Bouznad. "Efficient dynamic resource allocation method for cloud computing environment." Cluster Computing 23, no. 4 (2020): 2871-2889.
Yuan, Haitao, MengChu Zhou, Qing Liu, and Abdullah Abusorrah. "Fine-grained resource provisioning and task scheduling for heterogeneous applications in distributed green clouds." IEEE/CAA Journal of Automatica Sinica 7, no. 5 (2020): 1380-1393.
Silveira, M. R. ., Cansian, A. M. ., Kobayashi, H. K. ., & da Silva, L. M. (2022). Early Identification of Abused Domains in TLD through Passive DNS Applying Machine Learning Techniques. International Journal of Communication Networks and Information Security (IJCNIS), 14(1). https://doi.org/10.17762/ijcnis.v14i1.5256
Zolfaghari, Rahmat, and Amir Masoud Rahmani. "Virtual machine consolidation in cloud computing systems: Challenges and future trends." Wireless Personal Communications 115, no. 3 (2020): 2289-2326.
Shu, Wanneng, Wei Wang, and Yunji Wang. "A novel energy-efficient resource allocation algorithm based on immune clonal optimization for green cloud computing." EURASIP Journal on Wireless Communications and Networking 2014, no. 1 (2014): 1-9.
Singh, Juhi. "Energy consumption analysis and proposed power-aware scheduling algorithm in cloud computing." In Intelligent Computing and Applications, pp. 193-201. Springer, Singapore, 2021.
Hussain, Mehboob, Lian-Fu Wei, Abdullah Lakhan, Samad Wali, Soragga Ali, and Abid Hussain. "Energy and performance-efficient task scheduling in heterogeneous virtualized cloud computing." Sustainable Computing: Informatics and Systems 30 (2021): 100517.
Gopi, R., S. T. Suganthi, R. Rajadevi, P. Johnpaul, Nebojsa Bacanin, and S. Kannimuthu. "An Enhanced Green Cloud Based Queue Management (GCQM) System to Optimize Energy Consumption in Mobile Edge Computing." Wireless Personal Communications 117, no. 4 (2021): 3397-3419.
Jeevitha, J. K., and G. Athisha. "A novel scheduling approach to improve the energy efficiency in cloud computing data centers." Journal of Ambient Intelligence and Humanized Computing 12, no. 6 (2021): 6639-6649.
Ibrahim, Ibrahim Mahmood. "Task scheduling algorithms in cloud computing: A review." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 4 (2021): 1041-1053.
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