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Item type:Publication, Intelligent water drops algorithm-based aggregation in heterogeneous wireless sensor network(Hindawi Limited, 2022-01-01)This paper provides a novel implementation of the intelligent water drops (IWD) method for resolving data aggregation issues in heterogeneous wireless sensor networks (WSN). When the aggregating node is utilized to transmit the data to the base station, the research attempts to show that the traffic situations of WSN may be modified appropriately by parameter tuning and algorithm modification. IWD is used to generate an optimum data aggregation tree in WSN as one of its applications. IWD assumes that all nodes in the environment are identical, resulting in identical parameter updates for all nodes. In practical scenarios, however, diverse nodes with variable beginning energy, communication range, and sensing range characteristics are deployed. In order to replicate the influence of heterogeneity in the environment, improved IID (IIWD) is offered as an enhancement to the original IID. The suggested enhancement is appropriate for scenarios in which the aggregation node is utilized to transmit data to the base station in heterogeneous configurations. In terms of residual energy, dead nodes, payload, and network lifespan, a series of simulation results demonstrates that the proposed IIWD significantly improves the accuracy and effectiveness of the IWD method in comparison. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An efficient outlier detection with deep learning-based financial crisis prediction model in big data environment(Hindawi Limited, 2022-01-01)As Big Data, Internet of Things (IoT), cloud computing (CC), and other ideas and technologies are combined for social interactions. Big data technologies improve the treatment of financial data for businesses. At present, an effective tool can be used to forecast the financial failures and crises of small and medium-sized enterprises. Financial crisis prediction (FCP) plays a major role in the country's economic phenomenon. Accurate forecasting of the number and probability of failure is an indication of the development and strength of national economies. Normally, distinct approaches are planned for an effective FCP. Conversely, classifier efficiency and predictive accuracy and data legality could not be optimal for practical application. In this view, this study develops an oppositional ant lion optimizer-based feature selection with a machine learning-enabled classification (OALOFS-MLC) model for FCP in a big data environment. For big data management in the financial sector, the Hadoop MapReduce tool is used. In addition, the presented OALOFS-MLC model designs a new OALOFS algorithm to choose an optimal subset of features which helps to achieve improved classification results. In addition, the deep random vector functional links network (DRVFLN) model is used to perform the grading process. Experimental validation of the OALOFS-MLC approach was conducted using a baseline dataset and the results demonstrated the supremacy of the OALOFS-MLC algorithm over recent approaches. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of cloud computing technology in computer secure storage(Hindawi Limited, 2022-01-01)To investigate the use of cloud computing technologies in safe computer storage, firstly, it is proposed to complete the central control function by building a cloud computing data center, collect multiple platforms and network safety technologies, and then connect computers in unlike sites to confirm computer information security. Then, based on the implementation advantages of cloud computing technique in computer network safe storage, specific applications are analyzed. Finally, a cloud computing secure modeling and analysis idea based on multiqueue and multiserver is proposed. The proposed cloud security approach ensures that both data and applications are easily accessible to authorized users. One always has a consistent way to access your cloud data and applications, allowing you to address any potential security issues as soon as they arise. It has greatly improved computer security storage convenience while also greatly improving computer network storage security. After verification, with the cloud computing technology platform to carry out relevant businesses at any time, the operation effectiveness has been meaningfully enhanced by 80%. At the same time, it promotes the construction of information sharing and gives full performance to the benefits of hardware, accelerates the process of resource integration, and provides information support for the formulation of enterprise strategic plans. Combined with the actual situation, the current study discusses the development and application direction of cloud computing, so as to add new impetus to the economic growth of enterprises.