International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 16, No. 5, 8 Oct. 2024
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IBOA: Cost-aware Task Scheduling Model for Integrated Cloud-fog Environments
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Author(s)
Santhosh Kumar Medishetti
1,2,*
Ganesh Reddy Karri
1
Rakesh Kumar Donthi
3
Index Terms
Task Scheduling, Resource Utilization, Butterfly Optimization Algorithm (BOA), Swarm Intelligence, Communication Cost, Computation Cost
Abstract
Scheduling is an NP-hard problem, and metaheuristic algorithms are often used to find approximate solutions within a feasible time frame. Existing metaheuristic algorithms, such as ACO, PSO, and BOA address this problem either in cloud or fog environments. However, when these environments are combined into a hybrid cloud-fog environment, these algorithms become inefficient due to inadequate handling of local and global search strategies. This inefficiency leads to suboptimal scheduling across the cloud-fog environment because the algorithms fail to adapt effectively to the combined challenges of both environments. In our proposed Improved Butterfly Optimization Algorithm (IBOA), we enhance adaptability by dynamically updating the computation cost, communication cost, and total cost, effectively balancing both local and global search strategies. This dynamic adaptation allows the algorithm to select the best resources for executing tasks in both cloud and fog environments. We implemented our proposed approach in the CloudSim simulator and compared it with traditional algorithms such as ACO, PSO, and BOA. The results demonstrate that IBOA offers significant reductions in total cost, communication cost, and computation cost by 19.65%, 18.28%, and 25.41%, respectively, making it a promising solution for real-world cloud-fog computing (CFC) applications.
Cite This Paper
Santhosh Kumar Medishetti, Ganesh Reddy Karri, Rakesh Kumar Donthi, "IBOA: Cost-aware Task Scheduling Model for Integrated Cloud-fog Environments", International Journal of Information Technology and Computer Science(IJITCS), Vol.16, No.5, pp.52-68, 2024. DOI:10.5815/ijitcs.2024.05.04
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