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Neural Computing and Applications

Erschienen in:

27.02.2017 | Original Article

Uncertainty in sensor data acquisition for SOA system

verfasst von: Robin Singh Bhadoria, Narendra S. Chaudhari, Sovan Samanta

Erschienen in: Neural Computing and Applications | Ausgabe 10/2018

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Abstract

The computational data received from sensors are varying according to situation depending on data accuracy. So, for a particular time period, it is very tough to find the appropriate data for its certainty. In this paper, all received sensor data are to be assumed as fuzzy numbers, and such assumption could be beneficial to improve the functionality of data availability and accessibility in service-oriented architecture (SOA) system. Whenever any service is requested for updated sensor data, it must be handled through well-defined architecture, and this is governed by enterprise service bus (ESB). This ESB extends the features for SOA as well as strengthen the service middleware architecture. Sensor data received through this ESB would need corrections and cleanliness which could be done through fuzzy theory and help in reducing the uncertainty in data.

Vorheriger Artikel Numerical solution of second-order fuzzy nonlinear two-point boundary value problems using combination of finite difference and Newton’s methods

Nächster Artikel Analysis of natural convective heat transport in homocentric annuli containing nanofluids with an oriented magnetic field using nonhomogeneous dynamic model

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Kanagaraj E, Kamarudin LM, Zakaria A, Gunasagaran R, Shakaff AYM (2015) Cloud-based remote environmental monitoring system with distributed WSN weather stations. In: SENSORS, 2015 IEEE, pp 1–4

Stoimenov L, Bogdanovic M, Bogdanovic-Dinic S (2013) ESB-based sensor web integration for the prediction of electric power supply system vulnerability. Sensors 13(8):10623–10658CrossRef

Lin F, Zeng W, Yang L, Wang Y, Lin S, Zeng J (2016) Cloud computing system risk estimation and service selection approach based on cloud focus theory. Neural Comput Appl. doi:10.1007/s00521-015-2166-7 CrossRef

Romero D, Vernadat F (2016) Enterprise information systems state of the art: past, present and future trends. Comput Ind 79:3–13CrossRef

Qiu X, Luo H, Xu G, Zhong R, Huang GQ (2015) Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP). Int J Prod Econ 159:4–15CrossRef

Chang C, Srirama SN, Buyya R (2015). Mobile cloud business process management system for the internet of things: review, challenges and blueprint. arXiv preprint arXiv:1512.07199

Lucas Martínez N, Martínez JF, Hernández Díaz V (2014) Virtualization of event sources in wireless sensor networks for the internet of things. Sensors 14(12):22737–22753CrossRef

Alena R, Ossenfort J, Stone T, Baldwin J (2014) Wireless space plug-and-play architecture (SPA-Z). In: Aerospace conference, 2014 IEEE, pp 1–17

Castillejo P, Martínez JF, López L, Rubio G (2013) An internet of things approach for managing smart services provided by wearable devices. Int J Distrib Sens Netw 9(2):1–9CrossRef

10.

Rocchini D, Foody GM, Nagendra H, Ricotta C, Anand M, He KS, Feilhauer H (2013) Uncertainty in ecosystem mapping by remote sensing. Comput Geosci 50:128–135CrossRef

11.

Medjahed H, Istrate D, Boudy J, Baldinger JL, Dorizzi B (2011) A pervasive multi-sensor data fusion for smart home healthcare monitoring. In: IEEE international conference on fuzzy systems (FUZZ), 2011, IEEE, pp 1466–1473

12.

Sánchez L, Couso I, Casillas J (2009) Genetic learning of fuzzy rules based on low quality data. Fuzzy Sets Syst 160(17):2524–2552MathSciNetCrossRef

13.

Benz UC, Hofmann P, Willhauck G, Lingenfelder I, Heynen M (2004) Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS J Photogr Remote Sens 58(3):239–258CrossRef

14.

Mauris G, Lasserre V, Foulloy L (2000) Fuzzy modeling of measurement data acquired from physical sensors. IEEE Trans Instrum Meas 49(6):1201–1205CrossRef

15.

Bhadoria RS (2015) Performance analysis for enterprise service bus in SOA system. Int J IT-Based Bus Strategy Manag 1(1):1–10CrossRef

16.

Samanta S, Pal M (2015) Fuzzy planar graphs. IEEE Trans Fuzzy Syst 23(6):1936–1942CrossRef

17.

Samanta S, Pal M (2013) Fuzzy k-competition graphs and p-competition fuzzy graphs. Fuzzy Eng Info 5(2):191-204.MathSciNetCrossRef

18.

Samanta S, Pal M, Rashmanlou H, Borzooei RA (2016) Vague graphs and strengths. J Intell Fuzzy Sys 30:3675–3680.CrossRef

19.

Samanta S, Sarkar B, Shin D, Pal M (2016) Completeness and regularity of generalized fuzzy graphs. Springer Plus 5(1979):1–15

20.

Samanta S, Pal M (2011) Fuzzy tolerance graphs. Int J Latest Trends Math 1(2):57–67

21.

Martínez-Carreras MA, García Jimenez FJ, Gómez Skarmeta AF (2015) Building integrated business environments: analysing open-source ESB. Enterp Inf Syst 9(4):401–435CrossRef

22.

Bhadoria RS, Chaudhari NS, Tomar GS (2017) The performance metric for Enterprise Service Bus (ESB) in SOA system: theoretical underpinnings and empirical illustrations for information processing. Info Sys 65:158–171CrossRef

23.

Palumbo F, Ullberg J, Štimec A, Furfari F, Karlsson L, Coradeschi S (2014) Sensor network infrastructure for a home care monitoring system. Sensors 14(3):3833–3860CrossRef

24.

Dan A, Johnson R, Arsanjani A (2007) Information as a service: modeling and realization. In: International workshop on systems development in SOA environments. SDSOA’07: ICSE workshops 2007, IEEE. pp 2–2

25.

Sharma V, Kumar R (2016) Three-tier neural model for service provisioning over collaborative flying ad hoc networks. Neural Comput Appl. doi:10.1007/s00521-016-2584-1 CrossRef

Titel: Uncertainty in sensor data acquisition for SOA system
verfasst von: Robin Singh Bhadoria
Narendra S. Chaudhari
Sovan Samanta
Publikationsdatum: 27.02.2017
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 10/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-017-2910-2

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