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A Sec‎ure D‎ata Ag‎gregation Mecha‎nism in Wire‎less Senso‎r Netw‎ork

The addition of mobility in WSN ha‎s att‎racted signific‎ant i‎nterest in recent years. Mo‎bile nodes incre‎ase the ca‎pabilities of the WSN in m‎any way‎s. W‎e c‎lassify mobile wireless sensor networks (MWSNs) as a spec‎ial and ada‎ptable c‎lass of WSN, in which one or more th‎an one e‎lement of the network is mobile. The mobile componen‎t can b‎e any of the sensor nodes, rela‎ys (i‎f any), data c‎ollectors or sink or any combina‎tion of them. Fr‎om d‎eployment to data disseminat‎ion, mobility p‎lays a‎n i‎mportant rol‎e in ever‎y f‎unction of sensor networks. F‎or examp‎le, a mobile node can visi‎t oth‎er nodes in the network and ga‎ther data direct‎ly t‎hrough sin‎gle-ho‎p tra‎nsmissions. Simila‎rly a mobile node can trave‎l ar‎ound the sensor network and collect data from sens‎ors, bu‎ffer them, and t‎hen t‎ransfer them to base station. This considerabl‎y red‎uces onl‎y colli‎sions and data loss‎es, and als‎o minimiz‎es the pres‎sure of data forward‎ing ta‎sk by nodes and as a r‎esult spre‎ads the energy cons‎umption more consi‎stently througho‎ut the network. The proposed data aggregati‎on mechani‎sm us‎es bacteria‎l foraging optimization algorithm. This techn‎ique is i‎nspired by the so‎cial foraging behav‎iour lik‎e a‎nt col‎ony and pa‎rticle swar‎m optimization. The proposed algorithm improves WSN th‎roughput, coll‎ects data more efficientl‎y, and save‎s energy.

Published by: Sandhya Sehraw‎at, Dr. D‎INESH SIN‎GH

Author: Sandhya Sehraw‎at

Paper ID: V2I6-1147

Paper Status: published

Published: November 10, 2016

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Optimizing Channel Estimation for SCFDMA

The third generation partnership project has employed SCFDMA for its uplink transmission because of its low PAPR. SCFDMA signal while travelling through channel is affected by noise contained in the channel. Various channel estimation techniques has been given in the literature. This paper presents a channel estimation based on LMS with its parameters being optimised using PSO. The paper also compares result with existing LMS algorithm based systems. It has been observed that the proposed technique provides improvement in Bit Error Rate as compared to other technique.

Published by: Priyanka Malhotra, Garima Saini

Author: Priyanka Malhotra

Paper ID: V2I6-1146

Paper Status: published

Published: November 9, 2016

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Behavior Analysis of OSPF and ISIS Routing Protocols with Service Provider Network

OSPF is mainly designed for IP networks from scratch and runs in almost all sorts of environments like enterprise, data centers, or service providers, while ISIS, which was mainly designed by ISO was not intended to run for IP based networks from scratch and IETF in the early 1990’s adopted ISIS for its advantages. As a scalability purpose ISIS is better than OSPF, but when we have a large database or a large service provider, with only a single level design inside the service provider Both the routing protocols have different authentication mechanisms with ISIS providing key chain based mechanism and provides both plain-text and MD5 based integration with it, while OSPF also provide MD5 and SHA1 hashing based authentication when used with IPv6. Multiprotocol label switching technology (MPLS) is used to transfer the data in service provider network. Apart from Interconnecting Data Centers, L2VPNs are also used for Inter-AS service provider’s connectivity and connecting various Enterprise Branch offices with each other. Selection of right L2VPN technology is very important as wrong technology can harm the network. The main focus of this technique to give the solutions for slow speed, quality of service, lack of traffic engineer, less security and problem in trouble shouting. The motive is to improve the speed, high security, easily trouble shoot, high quality in terms of packet transformation and better results for traffic engineering.

Published by: Vikasdeep Kaur, Harpreet Kaur, Jaspreet Kaur

Author: Vikasdeep Kaur

Paper ID: V2I6-1145

Paper Status: published

Published: November 9, 2016

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Proposed Approach on CSTR with PID

In this paper conventional PID controller provides satisfactory results, still inefficiency persists due to extreme non-linear nature and uncertainty in the dynamics of the plant. So optimize the pidnon linear behavior by Gravitational search algorithm and partical swarm optimization. The PID controller is the most common form of feedback. PID control isused at the lowest level; the multivariable controller gives the set points to the controllers at the lower level. The PID controller can thus be saidto be the “bread and butter’ of control engineering. It is an importantcomponent in every control engineer’s tool box.PIDcontrollers have survived many changes in technology, from mechanicsand pneumatics to microprocessors via electronic tubes, transistors,integrated circuits.

Published by: Ramandeep Kaur, Jaspreet Kaur

Author: Ramandeep Kaur

Paper ID: V2I6-1144

Paper Status: published

Published: November 9, 2016

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Comparison of State Observer Design Algorithms for DC Servo Motor Systems

a state observer is a system that models a real system in order to provide an estimate of the internal state of the system. The design techniques and comparison of four different types of state observers are presented in this paper. The considered observers include Luenberge observer, unknown input observer and sliding mode observer. The application of these observers to a Multiple Input Multiple Output (MIMO) DC servo motor model and the performance of observers is assessed. In order to evaluate the effectiveness of these schemes, the simulated results on the position of DC servo motor in terms of residuals including white noise disturbance and additive faults are compared.

Published by: Kaustav Jyoti Borah, Jutika Borah

Author: Kaustav Jyoti Borah

Paper ID: V2I6-1143

Paper Status: published

Published: November 8, 2016

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Automated Vehicle Detection and Classification with Probabilistic Neural Network

The number of vehicles in the urban areas is rising at high pace. The critical issues are arising with the rise in the number of vehicles for the traffic analysis. The analysis of the vehicle running across the roads is usually done for the density analysis, traffic shaping and many other similar applications. The vehicle detection in the rushed areas produces the real challenge of independent component selection and classification, which requires the precise object detector with deep analytical ability based classification algorithm. In this paper, the unique method with probabilistic neural network (PNN) classification model along with the non-negative matrix factorization for the purpose of vehicular object localization and classification in the urban imagery. The proposed model is expected to solve the problems associated with the accuracy, precision and recall.

Published by: Ramanpreet Kaur, Meenu Talwar

Author: Ramanpreet Kaur

Paper ID: V2I6-1141

Paper Status: published

Published: November 2, 2016

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