An Efficient SFLA and CUCKOO Search Hybridization for Source Distribution in Cloud Computing

• Published in: 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS) pp. 01 - 05
• Main Authors: Malsoru, Vankudothu, Patil, Amareshwari, Kusuma, S M, Shivakanth, Gandla, Samanvita, N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24-02-2023
• Subjects: Bandwidth; Cloud computing; Computational modeling; habccs; Integrated circuits; Memory; Prototypes; Safety; sfla
• DOI: 10.1109/ICICACS57338.2023.10100133

Cloud calculating is a computing prototype that offers inexpensive, scalable computing resources like CPU, storage, and network bandwidth. It provides a pay-as-you-go model for gaining instantaneous online access to a shared pool of resources. This strategy is proposed to cut down on the required amount of computing time. In the most recent paper, authors employ a hybrid approach to resource allocation by combining two powerful optimization algorithms: the Shuffled Frog Leaping Algorithm (SFLA) and the Cuckoo Search (CS) Algorithm. With this algorithm, we can get around the computational time constraints of the HABCCS algorithm and the krill herd algorithm. It's easily scalable, so even niche uses can benefit. The SFLA has the potential to generate a global optimization solution and comes with the added benefits of faster convergence and simpler implementation. Algorithms from the field of computer science are used in difficult situations because of their advantageous simplicity in evaluation. The knapsack problems that normally crop up during the phase of allocating resources are also addressed. The efficacy of the third strategy is evaluated. The investigational consequences demonstrate the greater presentation of the projected method equated to the state-of-the-art methods.