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Efficient Network Selection Using Multi-Depot routing Problem for Smart Cities

Intelligent Automation & Soft Computing 2023年第5期36卷 1991-2005页

作者： r.shanthakumari Yun-Cheol Nam Yunyoung Nam Mohamed Abouhawwash Department of Information Technology Kongu Engineering CollegePerundurai638060India Department of Architecture Joongbu UniversityGoyang10279Korea Department of ICT Convergence Soonchunhyang UniversityKorea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Smart cities make use of a variety of smart technology to improve societies in better ways.Such intelligent technologies,on the other hand,pose sig-niﬁcant concerns in terms of power usage and emission of carbons.The suggested study is focused on technological networks for big data-driven systems.With the support of software-deﬁned technologies,a transportation-aided multicast routing system is suggested.By using public transportation as another communication platform in a smart city,network communication is enhanced.The primary objec-tive is to use as little energy as possible while delivering as much data as possible.The Attribute Decision Making with Capacitated Vehicle(CV)routing Problem(rP)and Half Open Multi-Depot Heterogeneous Vehicle routing Problem is used in the proposed research.For the optimum network selection,a Multi-Attribute Decision Making(MADM)method is utilized.For the sake of reducing energy usage,the Capacitated Vehicle routing Problem(CVrP)is employed.To reduce the transportation cost and risk,Half Open Multi-Depot Heterogeneous Vehicle routing Problem is used.Moreover,a mixed-integer programming approach is used to deal with the problem.To produce Pareto optimal solutions,an intelligent algorithm based on the epsilon constraint approach and genetic algorithm is cre-ated.A scenario of Auckland Transport is being used to validate the concept of ofﬂoading the information onto the buses for energy-efﬁcient and delay-tolerant data transfer.Therefore the experiments have demonstrated that the buses may be used effectively to carry out the data by customer requests while using 30%of less energy than the other systems.

关键词： Smart cities data ofﬂoading energy consumption bi-objective capacitated vehicle routing problem public transportation big data

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Protecting Data Mobility in Cloud Networks Using Metadata Security

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Computer Systems Science & Engineering 2022年第7期42卷 105-120页

作者： r.Punithavathi M.Kowsigan r.shanthakumari Miodrag Zivkovic Nebojsa Bacanin Marko Sarac Department of Information Technology M.Kumarasamy College of EngineeringKarur639113India Department of Computer Science and Engineering School of ComputingSRM Institute of TechnologyKattankulathur CampusChennai603203India Department of Information Technology Kongu Engineering CollegeErode638060India Singidunum University Belgrade11000Serbia

At present,health care applications,government services,and banking applications use big data with cloud storage to process and implement data.Data mobility in cloud environments uses protection protocols and algorithms to secure sensitive user data.Sometimes,data may have highly sensitive information,lead-ing users to consider using big data and cloud processing regardless of whether they are secured are not.Threats to sensitive data in cloud systems produce high risks,and existing security methods do not provide enough security to sensitive user data in cloud and big data environments.At present,several security solu-tions support cloud systems.Some of them include Hadoop Distributed File Sys-tem(HDFS)baseline Kerberos security,socket layer-based HDFS security,and hybrid security systems,which have time complexity in providing security inter-actions.Thus,mobile data security algorithms are necessary in cloud environ-ments to avoid time risks in providing security.In our study,we propose a data mobility and security(DMoS)algorithm to provide security of data mobility in cloud environments.By analyzing metadata,data are classiﬁed as secured and open data based on their importance.Secured data are sensitive user data,whereas open data are open to the public.On the basis of data classiﬁcation,secured data are applied to the DMoS algorithm to achieve high security in HDFS.The pro-posed approach is compared with the time complexity of three existing algo-rithms,and results are evaluated.

关键词： Data mobility data security cloud computing big data DMoS algorithm

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