Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Subject: search.filters.subject.Cuckoo search

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    Clustering using levy flight cuckoo search
    (Springer Verlag service@springer.de, 2013) Senthilnath, J.; Das, V.; Omkar, S.N.; Mani, V.
    In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role. © 2013 Springer.
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    Cuckoo search for influence maximization in social networks
    (Springer Science and Business Media Deutschland GmbH info@springer-sbm.com, 2016) Sinha, N.; Annappa, B.
    In a social network, the influence maximization is to find out the optimal set of seeds, by which influence can be maximized at the end of diffusion process. The approaches which are already existing are greedy approaches, genetic algorithm and ant colony optimization. Eventhough these existing algorithms take more time for diffusion, they are not able to generate a good number of influenced nodes. In this paper, a Cuckoo Search Diffusion Model (CSDM) is proposed which is based on a metaheuristic approach known as the Cuckoo Search Algorithm. It uses fewer parameters than any other metaheuristic approaches. Therefore parameter tuning is an easy task for this algorithm which is the main advantage of the Cuckoo Search algorithm. Experimental results show that this model gives better results than previous works. © Springer India 2016.
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    Optimization-Aware scheduling in cloud computing
    (Association for Computing Machinery acmhelp@acm.org, 2016) Binu, A.; George, N.; Chandrasekaran, K.
    Cloud computing allows delivery of computational resources via internet. Some of the computational resources include signals, codes and physical resources. Cloud users require computational resources for execution of their tasks. The computational elements, when thoroughly assigned to the cloud users according to requirement facilitate an efficient scheduling mechanism. The efficiency is dependent on the parameters chosen to promote the assignment of task to resources. Here, computational cost is chosen as the optimization factor, and the solution with the least cost is selected as the best assignment. A Cuckoo Search inspired technique is used, and task assignment to resources is done by validating the solution with the least value of cost. © 2016 ACM.