Computer Science-Conference Papers

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    Open Access
    ANALYSIS OF TWO-PHASED APPROACHES TO LOAD BALANCING IN CLOUD COMPUTING
    (IEEE, 2015) Ajayi, O.O.; Oladeji, F.A.; Uwadia, C.O.
    Cloud computing is an emerging trend in computing whereby computing resources are offered as a service to users. Providing resources to an increasing number of users and managing these resources is a major challenge in Cloud Computing. Numerous researchers have proposed diverse ways of addressing these issues, either with the aim of effectively allocating user workload to resources or redistribution / load balancing of workloads amongst resources for improved utilization. These approaches have broadly been categorized into single phased load balancing. In alternate works, authors have proposed a combination of these single phased approaches, such that allocation of workload is done in the first phase and an improvement on the allocation done in the second phase. This combined approach is referred to as the two-phased approaches to load balancing. This paper therefore analyses the various state-of-the-arts two-phased approaches to load balancing in cloud computing.
  • Item
    Open Access
    Asymmetric Model for Modeling Skewed Data
    (Nasarawa State University, Keffi, 2023-07) Badmus, N.I; Ogundeji, R.K; Olufolabo, O.O
    In this article, we present a new asymmetric distribution called Topp-Leone modified Weighted Rayleigh (TLMWR) distribution from Topp-Leone distribution. We study and examine several properties of the propose distribution such as density, distribution, reliability, hazard rate function, moment, generating function, quantile function and order statistics. The estimation of model parameters is obtain using method of maximum likelihood estimates. Exploratory data analysis, diagnostic test, normality test and goodness of fit statistics are carry out on the data used for the direction of skewness andlevel of kurtosis. The fitness and effectiveness of the proposed distribution is tested using both simulation and real data set to compare with other existing and new distributions. Therefore, we conclude based on the results from the analysis and supported the validity of the proposed model than other distributions considered.