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Analytical study of load scheduling algorithms in cloud computing

Analytical study of load scheduling algorithms in cloud comp...

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International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Divya Chaudhary Bijendra Kumar Department of Computer Engineering Netaji Subhas Institute of Technology New Delhi India

Scheduling enables the cloud in balancing the large amount of load present in the system for faster computation. It plays a vital and significant part in the execution of the load in the various heterogeneous systems. The scheduling portrays a selection of resources for the tasks for better resource utilization. This paper differentiates the various load scheduling algorithms applied in the various heterogeneous systems in detail. It plays a key role in larger resource utilization and handling. This paper defines the basic cloud computing fundamentals and the concept of load balancing i.e., scheduling of load in cloud. The applied load scheduling algorithms are elaborated and surveyed extensively.

关键词： Resource management Scheduling algorithms Biological cells Cloud computing Genetic algorithms Load management

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Analysis of information diffusion in dynamic information networks

Analysis of information diffusion in dynamic information net...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Geetika Sarna Rhythm Walia MPS Bhatia Computer Engineering Department Netaji Subhas Institute of Technology New Delhi India

Dynamic information network is a social network in which data and topology continuously keeps on changing. Number of users are approaching and departing the social networks and share information. Information diffusion plays a key role in this information sharing. So it is very important to understand the process of information diffusion in this type of network. It also helps to analyze the effective design of advertising campaigns, viral marketing and recommender systems. In this paper two major models of information diffusion i.e. Independent Cascade Model and Linear Threshold Model are studied and implemented with respect of dynamic information network While these methods gave promising results on static networks, but because of their linear and scalable properties, they are insufficient to model dynamic information networks.

关键词： Network topology Computational modeling Data models Twitter Topology Image color analysis

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Handling data incompleteness using Rough Sets on multiple decision systems

Handling data incompleteness using Rough Sets on multiple de...

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International Conference on Data Mining and Intelligent Computing (ICDMIC)

作者： Kanchan Lata Shampa Chakraverty Department of Computer Engineering Netaji Subhas Institute of Technology New Delhi India

A practical problem that arises in data analysis is to handle missing attribute values in an information system that has suffered degradation, so as to retain its quality. In this paper, we present a new Rough Set (RS) based approach to deal with incomplete data. The core idea is to tap the redundant information garnered from different databases that share common attributes. The attribute suffering missing entries in a deficient database is recast as a decision attribute in another reference database. The tenets of RS theory are then applied to derive rules that predict the missing values. Experimental results on pairs of two different pairs of related databases taken from the UCI repository reveal that our approach could predict missing values with a high degree of accuracy giving an average error of 15.75%.

关键词： Databases Iris Accuracy Approximation methods Set theory Information systems Explosions

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An energy efficient clustering protocol with fuzzy logic for WSNs

An energy efficient clustering protocol with fuzzy logic for...

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International Conference on Confluence The Next Generation Information technology Summit (Confluence)

作者： Samayveer Singh Satish Chand Bijendra Kumar Department of Computer Engineering Netaji Subhas Institute of Technology New Delhi India

This paper discusses a new protocol HEED-FL that follows the basic approach of the HEED protocol, but selects the cluster head by using fuzzy logic based on the three parameters: residual energy, degree of node, and distance between a sensor and base station. The HEED-FL protocol performs more than twelve times better than the original HEED protocol. It indeed performs better than many important protocols that have similar kind functionality as that of the HEED protocol.

关键词： Protocols Wireless sensor networks Fuzzy logic Energy efficiency Base stations Peer-to-peer computing Monitoring

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Optimal design of Weighted Least Square based fractional delay FIR filter using Genetic Algorithm

Optimal design of Weighted Least Square based fractional del...

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International Conference on Signal Propagation and computer technology (ICSPCT)

作者： Kamini Upadhyay Manjeet Kumar Tarun Kumar Rawat Division of Electronics and Communication Engineering Netaji Subhas Institute of Technology New Delhi

In this paper, a Weighted Least Square based designing of fractional delay FIR filter using Genetic Algorithm is proposed. In this method, Genetic Algorithm is implemented to evaluate the closed form error function. This helps in speeding up the process of filter design and achieving globally optimized final solution. Three design examples are given to illustrate the results of proposed approach. These examples demonstrate the effectiveness of proposed approach as compared to the existing filter design methods.

关键词： Filtering algorithms Algorithm design and analysis Optimization

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An analysis of the load scheduling algorithms in the cloud computing environment: A survey

An analysis of the load scheduling algorithms in the cloud c...

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International Conference on Industrial and Information Systems, ICIIS

作者： Divya Chaudhary Bijendra Kumar Department of Computer Engineering Netaji Subhas Institute of Technology Dwarka New Delhi India

Cloud Computing is a recent developmental paradigm in the field of computing offering huge power to next generation computers. The dynamic provisioning acts as a base for cloud computing facilitating and supporting the network services. It focuses on making the vision of utility computing a reality with pay-as-you-go. It offers immense potential to bloom the world with applications and products focussing on greater resource utilization and scalability. This paper presents the basic cloud computing fundamentals and the concepts of load balancing i.e., scheduling of load in the cloud. It elaborates the existing load scheduling algorithms with their merits/demerits and suitability in the cloud and heterogeneous computing environment and proposes a new perspective for better results as per desired parameters.

关键词： Cloud computing Resource management Scheduling Scheduling algorithms Quality of service Scalability

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Optimum deployment of sensors in WSNs

Optimum deployment of sensors in WSNs

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International Conference on Information Systems and computer Networks (ISCON)

作者： Samayveer Singh Satish Chand Bijendra Kumar Department of Computer Engineering Netaji Subhas Institute of Technology New Delhi India

Ant Colony Optimization (ACO) is one of the important techniques for solving optimization problems. It has been used to find locations to deploy sensors in a grid environment [12], in which the targets, called point of interest (PoI), are located on grid points in a square grid. The locations of sensors, which are grid points, are determined by considering the sink location as the starting point for deploying sensors. Though that work provides optimum number of sensors to cover all targets with respect to the given sink location, yet it does not provide which sink location provides minimum number of sensors to cover the targets. In this paper, we use ACO technique and find the sink location for which the number of sensors is minimum among all available locations in the grid. In our algorithm, we compute sum of distances of the targets from that sensor, which are in its range. Then we add these sums for all sensors in the grid. This distance corresponds to the given sink location. We repeat same process for computing the distance by changing the sink location in the grid. We choose that sink location for which the distance is minimum and this sink location requires minimum number of sensors to cover all targets. We carry out simulations to demonstrate the effectiveness of our proposed work.

关键词： Wireless sensor networks Sensor systems Genetic algorithms Ant colony optimization Monitoring Base stations

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Comparative study of some optimization techniques applied to DC motor control

Comparative study of some optimization techniques applied to...

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IEEE International Advance Computing Conference, IACC

作者： Vikrant Vishal Vineet Kumar K.P.S. Rana Puneet Mishra Division of Instrumentation and Control Engineering Netaji Subhas Institute of Technology New Delhi India

ISBN: (纸本)9781479925735

Traditional tuning techniques for classical Proportional-Integral-Derivative (PID) controller suffer from many disadvantages like non-customized performance measure and insufficient process information. For the past two decades nature inspired optimization algorithms are efficiently being implemented for tuning of PID controllers. In this paper, four optimization methods namely Genetic Algorithm (GA), Accelerated Particle Swarm Optimization (APSO), Differential Evolution (DE) and Cuckoo Search (CS) are studied and used to optimize the controller gains of a Proportional-Integral (PI) controller for set point tracking in speed control of a DC motor by minimizing Integral Time Absolute Error (ITAE). Hardware validation of the efficiency of above mentioned optimization algorithms is studied and presented. The plant under study is a DC motor control module (MS15) from M/S LJ CREATE™. M/S National Instruments (NI) based software and hardware components i.e. LabVIEW™ and its add-ons toolkit and data acquisition (DAQ) card has been utilized for the closed loop control in real time. The system identification is done in LabVIEW™ and then offline performance optimization is carried out in MATLAB™. The tuned gains are further used to study the run time performances in LabVIEW™ environment. This is done because MATLAB™ has very good optimization tools and on the other hand LABVIEW™ makes the measurement very easy. From the results obtained it can be clearly inferred that CS algorithm outperformed other algorithms studied in this paper, particularly in disturbance rejection.

关键词： DC motors Optimization Algorithm design and analysis Tuning Genetic algorithms Vectors Data acquisition

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Bidirectional DC/DC converter for hybrid electric vehicle

Bidirectional DC/DC converter for hybrid electric vehicle

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Atul Kumar Prerna Gaur Division of Instrumentation and Control Engineering Netaji Subhas Institute of Technology New Delhi India

ISBN: (纸本)9781479930814

Hybrid electric vehicle (HEV) technology is an effective and efficient alternative for conventional vehicles. It provides fuel efficiency, reduces harmful emission and enhances performance. The technology has gain enormous attention because of depleting conventional resources and measured carbon emission. This paper proposes a bidirectional buck boost converter with interleaved control, which minimizes input current and output voltage ripples. This leads to reduce size of passive components with higher efficiency and make whole system more reliable.

关键词： Hybrid electric vehicles Batteries Inductors Acceleration Generators Control systems

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Online PI controller tuning for a nonlinear plant using genetic algorithm

Online PI controller tuning for a nonlinear plant using gene...

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Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), Innovative Applications of

作者： Vikrant Vishal Vineet Kumar K. P. S. Rana Puneet Mishra Jitendra Kumar Division of Instrumentation and Control Engineering Netaji Subhas Institute of Technology New Delhi India

Proportional - Integral - Derivative (PID) controller performs well for linear systems. For systems with nonlinearity, controller parameters need to be tuned every time for new operating point to obtain `local gain parameters'. These local gain parameters are not sufficient to get satisfactory performance at other operating points. In this paper a novel approach `Aggregate Fitness Function' is presented to obtain the `global gain parameters' that works satisfactorily at various operating points. Online optimization scheme with Genetic Algorithm (GA) is adopted to tune the Proportional-Integral (PI) controller parameters for setpoint tracking of DC Motor by minimizing Integral-Time-Absolute-Error (ITAE). Hardware validation of the results is presented and studied. The plant under study is DC Motor Control Module (MS15) from M/S LJ CREATE™. M/S National Instrument (NI) based software and hardware components i.e. LabVIEW™ and its add-ons toolkit and Data Acquisition (DAQ) Card has been utilized for online tuning and closed loop run time control. The simulation and run time results clearly show the efficiency of the proposed approach.

关键词： DC motors Tuning Genetic algorithms Optimization Data acquisition Aggregates

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