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Stochastic Ranking Improved Teaching-Learning and Adaptive Grasshopper Optimization Algorithm-Based Clustering Scheme for Augmenting Network Lifetime in WSNs

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China Communications 2024年第9期21卷 159-178页

作者： N Tamilarasan SB Lenin P Mukunthan NC Sendhilkumar department of Electronics and Communications engineering Sri Indu College of Engineering and TechnologyHyderabadTelanganaIndia department of Electronics and Communications engineering Sri Manakula Vinayagar Engineering CollegePondicherryIndia

In Wireless Sensor Networks(WSNs),Clustering process is widely utilized for increasing the lifespan with sustained energy stability during data *** clustering protocols were devised for extending network lifetime,but most of them failed in handling the problem of fixed clustering,static rounds,and inadequate Cluster Head(CH)selection criteria which consumes more *** this paper,Stochastic Ranking Improved Teaching-Learning and Adaptive Grasshopper Optimization Algorithm(sriTL-AGOA)-based Clustering Scheme for energy stabilization and extending network *** sriTL-AGOA selected CH depending on the weightage of factors such as node mobility degree,neighbour's density distance to sink,single-hop or multihop communication and Residual Energy(RE)that directly influences the energy consumption of sensor *** specific,Grasshopper Optimization Algorithm(GOA)is improved through tangent-based nonlinear strategy for enhancing the ability of global *** the other hand,stochastic ranking and violation constraint handling strategies are embedded into Teaching-Learning-based Optimization Algorithm(TLOA)for improving its exploitation ***,SR and VCH improved TLOA is embedded into the exploitation phase of AGOA for selecting better CH by maintaining better balance amid exploration and *** results confirmed that the proposed sriTL-AGOA improved throughput by 21.86%,network stability by 18.94%,load balancing by 16.14%with minimized energy depletion by19.21%,compared to the competitive CH selection approaches.

关键词： Adaptive Grasshopper Optimization Algorithm(AGOA) Cluster Head(CH) network lifetime Teaching-Learning-based Optimization Algorithm(TLOA) Wireless Sensor Networks(WSNs)

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FEWSS-FRAMEWORK TO EVALUATE THE SERVICE SUITABILITY AND PRIVACY IN A DISTRIBUTED WEB SERVICE ENVIRONMENT

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International Journal of Modeling, Simulation, and Scientific Computing 2014年第1期5卷 68-104页

作者： D.CHANDRAMOHAN T.VENGATTARAMAN P.DHAVACHELVAN R.BASKARAN V.S.K.VENKATACHALAPATHY department of Computer Science pondicherry University PondicherryIndia department of Computer Science and engineering Anna University ChennaiIndia department of mechanical engineering sri manakula vinayagar engineering college pondicherry India

This paper focuses on addressing the problem of web service monitoring by evaluating its suitability and privacy in a distributed web service environment(DWS).The need for web services monitoring and evaluation is necessary because the quantity and quality of retrieved web services generally does not fulfill the demands or requirements of the web service *** the literature,many authors proposed suitable solutions for checking the quality of web service in an ad hoc scenario but there is no available testbed for this *** this work,it is proposed to develop a framework as a testbed for evaluating the web service for its suitability and *** order to verify,the retrieved web services fulfill the demands and requirements of the requester in a DWS *** Framework to Evaluate the Web Service Suitability(FEWSS)supports service providers in modeling the services with testbed and to design service behavior to comply the service *** generates run-time instances of web services,client’s requests,service registries and other entities in order to emulate realistic SOA *** generating a real testbed,our approach assists in runtime test for provider system/*** focus has been put on the privacy policy extensibility to allow the service providers and users in a complex *** also provides an intuitive interface for testing all services under SOA control.

关键词： Distributed web service privacy service-oriented architecture quality of service service evaluation web service selection UDDI

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Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing

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Intelligent Information Management 2016年第3期8卷 41-65页

作者： Panneerselvam Sivasankaran Peer Mohamed Shahabudeen department of mechanical engineering Manakula Vinayagar Institute of Technology Pondicherry India department of Industrial engineering College of Engineering Anna University Chennai India

The growing global competition compels organizations to use many productivity improvement techniques. In this direction, assembly line balancing helps an organization to design its assembly line such that its balancing efficiency is maximized. If the organization assembles more than one model in the same line, then the objective is to maximize the average balancing efficiency of the models of the mixed model assembly line balancing problem. Maximization of average balancing efficiency of the models along with minimization of makespan of sequencing models forms a multi-objective function. This is a realistic objective function which combines the balancing efficiency and makespan. This assembly line balancing problem with multi-objective comes under combinatorial category. Hence, development of meta-heuristic is inevitable. In this paper, an attempt has been made to develop three genetic algorithms for the mixed model assembly line balancing problem such that the average balancing efficiency of the model is maximized and the makespan of sequencing the models is minimized. Finally, these three algorithms and another algorithm in literature modified to solve the mixed-model assembly line balancing problem are compared in terms of the stated multi-objective function using a randomly generated set of problems through a complete factorial experiment.

关键词： Assembly Line Balancing Genetic Algorithm Crossover Operation Mixed-Model Model Sequencing Makespan

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An Integrated Drive for Two PMSMs Involved Automotive Applications and Development of Current Reference Expanded Two Arm Modulation Technique

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Circuits and Systems 2016年第8期7卷 1794-1815页

作者： V. Krishnakumar V. Kamaraj C. Adrien Perianayagam Research Scholar Department of EEE SSN College of Engineering Chennai India department of Electrical and Electronics engineering SSN College of Engineering Chennai India department of Electrical and Electronics engineering Sri Manakula Vinayagar Engineering College Pondicherry India

A five leg inverter (FLI) control is incorporated to drive two independent rated permanent magnet synchronous motors (PMSMs) for automotive applications. Literature evidences many attempts of employing the FLI for controlling two general purpose/special motors, where variety of modulation techniques has been practiced for performance enhancement. Also in these cases one leg of inverter is common to both the motors. The expanded two arm modulation (ETAM) has been generally engaged in FLI. In ETAM the percentage voltage utilization factor (VUF) is calculated based on “αmax”, where “αmax” is the maximum modulation index and equal to and hence it restricts the VUF to 50%. This makes the FLI drives to use the dc link in inefficient way, which is due to the fact that conventional ETAM works with voltage reference. This paper modifies the ETAM in an ingenious way to improve the VUF further through current reference. In addition, the developed current reference expanded two arm modulation (CRETAM) minimizes the current harmonics and torque ripple as well. A detailed comparison of the CRETAM with the conventional ETAM and the competent digital counterpart, space vector pulse width modulation (SVPWM), is also presented. The enhancement in VUF, torque ripple minimization and current total harmonic distortion (THD) reduction are found in the MATLAB based simulation results.

关键词： EV/HEV Traction Drive SVPWM Five Leg Inverter Two Permanent Magnet Synchronous Motor Drive Current Reference Expanded Two Arm Modulation (CRETAM) Expanded Two Arm Modulation (ETAM)

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