Abstract
Adoption of cloud computing based computing solutions is growing day by day in nearly all sectors of society. Technological advancements such as load balancing help service providers uphold the quality of service, and thereby retain the confidence of service consumers. Collaborations among cloud environments can be established for resolving load balancing and fault tolerance issues up to a certain extent. However, the gigantic increase in consumption of cloud services makes cloud resource management difficult in intercloud environments too. Load balancing helps resolve workload balancing problems for collaborated cloud platforms. We present an enhanced and priority-oriented mechanism for sharing resources for workload balancing in collaborated cloud environments. In order to provide enhanced load balancing solution, the suggested resource sharing mechanism works on the priority values of participating instances. Employment of the suggested load balancing mechanism avoids starvation by means of lowering waiting time. The suggested technique has been implemented on a physical cloud testbed built using OpenStack cloud computing setup on CentOS Linux operating system. The experimental results reveal lesser waiting time of the highly loaded cloud instances.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Joshi NA (2014) Performance-centric cloud-based e-learning. IUP J Inform Technol 10(2)
Kumar M, Suman (2019) Priority Based Virtual Machine Selection Algorithm in Cloud Computing, International Journal of Recent Trends and Engineering 8(3)
Tripathi A, Shukla S, Arora D (2018) A hybrid optimization approach for load balancing in cloud computing. In: Bhatia S, Mishra K, Tiwari S, Singh V, Advances in computer and computational sciences. Springer Advances in Intelligent Systems and Computing 554
Polepally V, Chatrapati KS (2018) Exponential gravitational search algorithm-based VM migration strategy for load balancing in cloud computing. Int J Model Simul Scientif Comput 9(1)
Vasudevan S, Anandaram S, Menon A, Aravinth A (2016) A novel improved honey bee based load balancing technique in cloud computing environment. Asian J Inform Technol 15(9)
Dubey S, Dahiya M, Jain S (2019) Implementation of load balancing algorithm with cloud computing for logistics. J Eng Appl Sci 14(2)
Joshi NA (2022) Technique for balanced load balancing in cloud computing environment. Int J Adv Comput Sci Appl 13(3)
Haidri R, Padmanabh Katti C, Saxena P (2021) Capacity based deadline aware dynamic load balancing model in cloud computing environment. Int J Comput Appl 43(10)
Joshi NA (2020) Priority based mechanism for resource sharing in cloud. Int J Innov Technol Explor Eng 9(3)
Singh A, Juneja D, Malhotra M (2015) Autonomous agent based load balancing algorithm in cloud computing. International Conference on Advanced Computing Technologies and Applications. Proc Comput Sci 45
Hsieh H, Ching M (2019) The incremental load balancer cloud algorithm by using dynamic data deployment. J Grid Comput 17(3)
Manasser S, Alzghoul M, Mohmad M (2019) An advanced algorithm for load balancing in cloud computing using MEMA technique. Int J Innov Technol Explor Eng 8(3)
Joshi NA (2019) Optimized mechanism for resource sharing in cloud. Int J Eng Adv Technol 9(2)
Ji H, Bao W, Zhu X (2017) Adaptive workflow scheduling for diverse objectives in cloud environments. Trans Emerging Telecommun Technol 28(2)
Kaur A, Kaur B (2022) Load balancing optimization based on hybrid heuristic-metaheuristic techniques in cloud environment. J King Saud Univ – Comput Inform Sci 34 (3)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Joshi, N.A. (2024). Priority Based Load Balancing for Intercloud Computing Environments. In: Namasudra, S., Trivedi, M.C., Crespo, R.G., Lorenz, P. (eds) Data Science and Network Engineering. ICDSNE 2023. Lecture Notes in Networks and Systems, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-99-6755-1_30
Download citation
DOI: https://doi.org/10.1007/978-981-99-6755-1_30
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6754-4
Online ISBN: 978-981-99-6755-1
eBook Packages: EngineeringEngineering (R0)