Efficient DAG Task Scheduling Algorithm for Wireless Sensor Networks
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.735-743, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.735743
Abstract
WSN (Wireless Sensor Network) has to be systemized to being resource effective and extensible. The concept of task scheduling requires less task completion time, less energy consumption and proper utilization of energy with fewer energy nodes. DAG (Directed Acyclic Graph) is considered for WSN organization as of the routing redundancy for the root. This research paper has aimed to enhance the performance of DAG in WSN. For the improvement, Cuckoo Search as an optimization algorithm and Support Vector Machine as a classification algorithm is utilized. For the evaluation of the proposed work, QoS parameters, such as Throughput, PDR (Packet Delivery Ratio), Energy Consumption, Network Lifetime and Delay are considered. The proposed algorithm stood very positive results for each QoS parameter. The results are compared on the base of with and without the proposed architecture.
Key-Words / Index Term
WSN, DAG, Cuckoo Search, Support Vector Machine
References
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Citation
Mandeep Kaur, Balwinder Singh Sohi, "Efficient DAG Task Scheduling Algorithm for Wireless Sensor Networks," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.735-743, 2018.
A Multi-class Ruling Classification Technique using Diabetes Dataset
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.744-748, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.744748
Abstract
Diabetes dataset is described by hyperglycemia happening because of abnormalities in insulin discharge which would thusly result in sporadic raise of glucose level. This overview exhibits an analytical investigation of a few algorithms which diagnosis and arranges Diabetes dataset information successfully. As of late, the effect of Diabetes dataset has expanded, as it were, particularly in creating nations like India. This is for the most part because of the irregularities in the sustenance habits of a few IT professionals. In this way, early diagnosis and order of this lethal malady has turned into a functioning region of research in the most recent decade. Various methods have been produced to manage his illness. Various grouping and arrangements strategies are accessible in the literature to envision fleeting information to recognizing patterns for controlling diabetes dataset. The multi-class ruling algorithms are broke down altogether to distinguish their focal points and limitations. The execution assessment of the multi-class ruling algorithms is completed to decide the best methodology. A best methodology among the multi-class ruling methodology is resolved and a solution is likewise proposed to enhance the general execution of diagnosis process.
Key-Words / Index Term
Diabetes dataset, Classification, Gestational diabetes
References
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[3] Aiswarya Iyer, S. Jeyalatha and Ronak Sumbaly, “Diagnosis Of Diabetes Using Classification Mining Techniques”, International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.5, No.1, January 2015.
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[6] V.Karthikeyani, I.Parvin Begum, K.Tajudin, I.Shahina Begam, “Comparative of Data Mining Classification Algorithm (CDMCA) in Diabetes Disease Prediction”, International Journal of Computer Applications (0975 – 8887) Volume 60– No.12, December 2012.
[7] Rajesh, M., and J. M. Gnanasekar. “Congestion control in heterogeneous WANET using FRCC.” Journal of Chemical and Pharmaceutical Sciences ISSN 974 (2015): 2115.
[8] Rajesh, M., and J. M. Gnanasekar. “A systematic review of congestion control in ad hoc network.” International Journal of Engineering Inventions 3.11 (2014): 52-56.
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Citation
S. Thaiyalnayaki, J. Chockalingam, "A Multi-class Ruling Classification Technique using Diabetes Dataset," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.744-748, 2018.
A Survey of Hybrid Routing Protocol for Interconnecting Mobile Ad Hoc Network and Internet
Survey Paper | Journal Paper
Vol.6 , Issue.12 , pp.749-756, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.749756
Abstract
Mobile node is a collection of mobile nodes which forms a temporary network. Some of the nodes in an ad hoc network may want access to an external network, such as internet. Different mechanisms have been proposed to integrate MANETs and the Internet. These mechanisms are differing based on gateway discovery mechanism, and Adhoc routing protocol. When MANET is connected to the Internet, it is important for the mobile nodes to detect an available gateway providing an access to the Internet. The objective of this paper is a survey on the Mobile Ad-hoc Network (MANET) routing protocols used in gateways. This article presents a survey of hybrid solutions for integrating MANETs with the Internet.
Key-Words / Index Term
MANET, AODV, DSDV, Gateway, Routing, Hybrid protocol, OLSR
References
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Citation
G. Ramesh, M.Geetha, "A Survey of Hybrid Routing Protocol for Interconnecting Mobile Ad Hoc Network and Internet," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.749-756, 2018.
Swarm Approach Combined With Artificial Neural Networks to Constructive Data Organization and Information Extrapolation
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.757-762, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.757762
Abstract
Swarm intelligence is a cooperative behavior of collective systems like insects such as ant colony optimization (ACO), fish schooling, birds flocking, bee Colony Optimization (BCO) particle swarm optimization (PSO) and so on. In this paper, a hybrid performances for data organization and information extrapolation is recommended. The Honey Bee Mating Optimization algorithm and Artificial Neural Networks (HBMO-ANN) may also be considered as a distinctive swarm-based optimization, in which the exploration algorithm is encouraged by the development of real honey-bee marital and mimic the iterative mating process of honey bees and approaches to select applicable drones for mating progression through the fitness function enrichment for selection of superlative weights for hidden layers of Neural Network classifiers. Enhanced HBMO with Neural Network (EHBMO-NN) algorithm is now realistic to classify the data proficiently by training the neural network. The classification accuracy of EHBMO is much more compared with other algorithm such as Support Vector Clustering Algorithm (EHBMO-SVC). In this paper, enhanced honey-bee mating optimization algorithm is offered and verified. A developed way of Honey Bee Mating Optimization performance is combined with Neural Network which expands accuracy and moderate time delay in difficulty of various real world datasets.
Key-Words / Index Term
Swarm intelligence, Honey Bee Mating Optimization Algorithm, Support Vector Clustering, Artificial Neural Networks
References
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[10] “L. Qingyong, S. Zhiping, S. Jun and S. Zhongzhi, “Swarm Intelligence Clustering Algorithm Based on Attractor”, Lecture Notes in Computer Science, Springer Link, Vol. 3621, 2005, pp. 496-504.
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Citation
K . Kalyani, T. Chakravarthi, "Swarm Approach Combined With Artificial Neural Networks to Constructive Data Organization and Information Extrapolation," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.757-762, 2018.
Predictive Maintenance Approach on Automobiles
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.763-767, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.763767
Abstract
The main purpose of this paper is exploring the fact that how to use a machine learning model in order to perform predictive maintenance on Automobile. Maintenance and Care play a key role in the smooth and safe running of your motorcycle. The goal is to predict when the automobile require service or maintenance. If the model runs successfully, it gives us enough data about determining what the problem is and not only providing the necessary solutions but also ordering the parts and scheduling the people necessary to repair it. The innovative solutions of Predictive Maintenance recursively monitor, evaluates and report the component and system conditions in the vehicle. Various techniques are discussed and tested, such as linear and quantile regression. The primary aim of the system is to increase the vehicle’s efficiency due to the observed and supervised driving behavior which is able to minimize the fuel consumptions and exhaust. Based on received data from the various connected vehicle and transmitting it to the cloud i.e. Azure where the processing of the data takes place, errors are predicted and fixed before time and with less damage of vehicle whereby reducing the overall cost of maintenance
Key-Words / Index Term
Predictive maintenance, machine learning automobiles, 2-wheelers, Internet of Things, AZURE
References
[1]. Jong-Ho Shin and Hong-Bae Jun. “On condition based maintenance policy”. Journal of Computational Design and Engineering, 2(2): pp.119–127, 2015.
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[4]. Xunyuan Yin, Zhaojian Li, Sirish L. Shah, Lisong Zhang, Changhong Wang , “Fuel Efficiency Modelling and Prediction for Automotive Vehicles: A Data-Driven Approach”, 2015 IEEE International Conference on Systems, Man, and Cybernetics, Chain ,pp 2527-2532, 2015.
[5]. Rohit Dhall, Vijender Solanki, “An IoT Based Predictive Connected Car Maintenance Approach”, International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 4, Nº3,pp. 16-22, 2017.
[6]. Gian Antonio Susto, Andrea Schirru, Simone Pampuri, Se´an McLoone Senior Member, IEEE, Alessandro Beghi Member, IEEE, “Machine Learning for Predictive Maintenance: a Multiple Classifier Approach”, IEEE Transactions on Industrial Informatics, 11(3), 812-820, pp.1-8 , 2014.
[7]. Emir Husni , Galuh Boy Hertantyo , Daniel Wahyu , Muhamad Agus Triawan , “Applied Internet Of Things (IoT):Car monitoring system using IBM BlueMix”, 2016 International Seminar on Intelligent Technology and Its Application©2016 IEEE, Indonesia, pp. 417-422, 2016.
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Citation
Prakash Patel, Pallavi Jain, Swapnil Bhambure, Yashraj Sen, N.F. Shaikh, "Predictive Maintenance Approach on Automobiles," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.763-767, 2018.
Migration from Subversion to Git Version Control System
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.768-771, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.768771
Abstract
In recent years, software development in software industries is getting a transition from centralized version control systems (CVCSs) like subversion, mercurial, perforce, CVS etc. to decentralized version control systems (DVCSs) like Git due to a number of reasons like time, space, branching, merging, offline commits & builds and repository etc. Both centralized VCSs and distributed VCSs have gone through ample investigations in recent past but individually from the software developer’s point of view in a large commercial software industry. There has been a little focus on the transition across Git having a share of more than three-fourth of total VCS, and Subversion having a share of 13.5%. In this work transition process from Subversion VCS to Git VCS has been investigated.
Key-Words / Index Term
Version control system, distributed VCS, centralized VCS, transition, branching, merging, time, space
References
[1]. N. B. Ruparelia. “The history of version control,” ACM SIGSOFT Software Engineering Notes vol. 35, no. 1, pp. 5-9, 2010.
[2]. B. De Alwis and J. Sillito, “Why are software projects moving from centralized to decentralized version control systems?” ICSE Workshop on Cooperative and Human Aspects on Software Engineering (CHASE`09), pp. 36-39, 2009.
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[6]. Loeliger, J., Matthew McCullough, “Version Control with Git: Powerful Tools and Techniques for Collaborative Software Development,” O’Reilly Media, Inc. Second Edition, 2009.
[7]. Tom De Nies, Sara Magliacane, Ruben Verborgh, Sam Coppens, Paul Groth, Erik Mannens, and Rik Van de Walle, “Git2PROV: Exposing Version Control System Content as W3C PROV,” Proc. 12th Int. Semantic Web Conf., pp. 1-4, Oct. 2013.
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Citation
Monika Varshney, Azad Kumar Shrivastava, Alok Aggarwal, Adarsh Kumar, "Migration from Subversion to Git Version Control System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.768-771, 2018.
Review of Clustering Algorithm for Cluster Head Selection of MANET Using Weighted Metrics
Review Paper | Journal Paper
Vol.6 , Issue.12 , pp.772-774, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.772774
Abstract
A Mobile Ad hoc Network (MANET) is an accumulation of wireless portable nodes shaping a system without utilizing any current infrastructure. The mobility characteristic of MANETs is an extremely critical one. The mobile nodes may follow different mobility patterns that may affect connectivity and performance. In MANET due to decentralize of resources every nodes have to perform the routing functionalities themselves. Communication in such type of network is challenge and complex. To overcome these problems Clustering is the best solution for wide, flexible and high portability Ad-Hoc System. It increases the potential of network and reduces the routing overhead for efficient routing in MANET. Different types of phases involve in Cluster are Designing of Cluster and Maintenance of Cluster. In Cluster designing, selecting proper cluster head is one of the primary issues of research. For Maintenance of cluster an efficient system is required so that cluster head can keep update all the data of cluster, due to change in cluster structure because of nodes mobility. This paper basically focused on the Weighted Metric algorithms in MANET
Key-Words / Index Term
MANET,Cluster Head, Clustering
References
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[6] Basagni S, “Finding a Maximal Wеightеd Indеpеndеnt Sеt in Wirеlеss Nеtworks", Tеlеcomm. Systеms. 18(1/3):155-168, Sеptеmbеr 2001.
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[10] F. Li, S. Zhang, X. Wang, X. Xue, H. Shen, “Vote-Based Clustering Algorithm in Mobile Ad Hoc Networks,” in Information Networking, vol. 3090, Springer Berlin Heidelberg, 2004, pp.13-23
[11] A. Karimi, F.Zarafshan, A. Afsharfarnia and S.A.R Al Haddad, “A Novel Clustering Algorithm for Mobile AdHoc Newtorks Based on Determination of Virutal Links’ Weight to Increase Network Stability” in The Scientific World Journal, vol. 2014, Iran: Hindawi, 2014.
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Citation
Sandeep Monga, J.L Rana, Jitendra Agarwal, "Review of Clustering Algorithm for Cluster Head Selection of MANET Using Weighted Metrics," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.772-774, 2018.
Possibilities of Existence of a Third Force J In Between Action and Reaction Forces of Newton
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.775-776, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.775776
Abstract
In this research paper, the spite of action and reaction forces in case of Newton’s third law of motion there is a third force which plays vital role in the sustainability of any body. This force makes able the body to resist its shape in spite of the existing intermolecular forces. As long as the angle of responding the applying forces increases, value of reactionary forces decreases even with its components. Macro and Micro spectrum of air particle spreaded in the Universe protect the body as a plasma layer, angle β, force F give burn a new magnitude of force Ј which is plays decisive role and may be taken as the guiding factor to save the physical structure of a body. Values of this J =K(F+β)n where K= is the repetition of the frequency ranging from the whole number domain. n is supposed as the number of trial of any strike of any magnitude of a variable force during a certain moment provided no additional lubricants or viscous material is supplied during the application of these action and reaction of the forces
Key-Words / Index Term
Force, Responding Force, Adhesive, Cohesive, Perpendicular, Third Force
References
[1]. Newton , Isaac Mathematical Principles of Natural Philosophy pp.19-20 , London, 1727 , translated by Andrew Motte from the Latin.
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Citation
Shobha Lal, Jitendra Joshi, "Possibilities of Existence of a Third Force J In Between Action and Reaction Forces of Newton," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.775-776, 2018.
A Blended Biometric Approach Using Matching Score Level Architecture
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.777-780, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.777780
Abstract
This paper aims at security authentication for an unmanned surveillance system. The system takes the Face image, impressions of a person’s finger and images of eyes and prepares a database. A blended biometric approach is followed for calculating the weighted average of scores appraised from the three most trivial biometric traits, Face, Eye and Finger impressions. The features are extracted from the pre-processed images of iris, face and finger impressions.The details of a probing image are to be matched with the database we have .the individual details obtained after tallying are sent to the fusion module. This module consists of three major steps i.e., Pre-Processing, Discrete Wavelet Transformation and Image fusion. At the final phase the hidden key Analysis approach is followed to authenticate the subject under investigation.
Key-Words / Index Term
Biometric Identity, IRIS Recognition, Finger print, Face Recognition, DWT, WAMS
References
[1] Hiren D. Joshi, “A Multimodal Biometric Authentication System for Person Identification and Verification using Fingerprint and Face Recognition” International Journal of Computer Applications (0975 – 8887) Volume 51– No.17, August 2012
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Citation
K. Divya, K. G. R. Narayan, V. Ramachandran, R. Eswariah, "A Blended Biometric Approach Using Matching Score Level Architecture," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.777-780, 2018.
A Survey on Caching in Named Data Network
Survey Paper | Journal Paper
Vol.6 , Issue.12 , pp.781-787, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.781787
Abstract
To replace the present host-driven IP-based Internet architecture, Content-Centric Networking (CCN) is considered as conceivable substitution and is been developing worldwide. In CCN, the content name rather than IP address of host becomes the primary entity. Content is in this manner decoupled from its location. In addition to other things, this allows the cache to be ubiquitously present. One of the famous examples of CCN is Named Data Networking (NDN). To satisfy the incoming request for data, every node in NDN is permitted to have its own local cache. For productive huge scale content dissemination, NDN is been made a decent architecture because of this. This paper focuses on various caching techniques and explains many of them briefly. NS-3 based Named Data Networking simulator named as ndnSIM is used to assess proposed scheme.
Key-Words / Index Term
NDN, CCN , CS, FIB, PIT, ndnSIM, NS-3
References
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Citation
Ganesh Pakle, Neha Bais, Ramchandra Manthalkar, "A Survey on Caching in Named Data Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.781-787, 2018.