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Efficient metaheuristic population-based and deterministic algorithm for resource provisioning using ant colony optimization and spanning tree - 2020

Research Area:  Cloud Computing

Abstract:

Resource provisioning is the core function of cloud computing which is faced with serious challenges as demand grows. Several strategies of cloud computing resources optimization were considered by many researchers. Optimization algorithms used are still under reckoning and modification so as to enhance their potentials. As such, a dynamic scheme that can combine several algorithms characteristics is required. Quite a number of optimization techniques have been reassessed based on metaheuristics and deterministic to map out with the challenges of resource provisioning in the Cloud. This research work proposes to involve the ant colony optimization (ACO) population-based mechanism by extending it to form a hybrid meta-heuristic through deterministic spanning tree (SPT) algorithm incorporation. Extensive experiment conducted in the cloudsim simulator provided an efficient result in terms of faster convergence, and makespan time minimization as compared to other population-based and deterministic algorithms as it significantly improves performance.

Author(s) Name:  Muhammad Aliyu , Murali M , Abdulsalam Y. Gital , Souley Boukari

Journal name:  International Journal of Cloud Applications and Computing

Conferrence name:  

Publisher name:  ACM

DOI:  10.4018/IJCAC.2020040101

Volume Information:  Volume 10,Issue 2,Apr 2020,pp 1–21