Optimizing a network for smart home based on IEEE 802.15.4g for advanced metering infrastructure
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ISSN: 1680-8894
E-ISSN: 2219-6714
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Dec 14, 2016
Published: Dec 13, 2016
Published: Dec 13, 2016
Abstract
This article describes the optimization of infrastructure and elements involved in the communication and transmission of information. In the model will minimize the number of points of wireless Access-Point (WAP), taking into account restrictions on capacity, coverage and interference with LTE technology in a WLAN system for a network of sensors IEEE 802.15.4g under the concept of Smart Home through the use of software Matlab and LPSolver, presents a mathematical formulation, which will be used for the location of a set of wireless Access-Point that give coverage to the smart devices using the software LPSolver will facilitate the resolution of equations to provide a reduction of time and resources for the study of design in Smart Metering, through the exemplification of problems which are of great importance for design conditions of wireless networks, applying a hierarchical topology.
Keywords
Capacity, Smart home, coverage, Advanced Metering Infrastructure, interference, optimization, Smart Grid.Downloads
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How to Cite
Arciniega Calderón, M., Ayala Arciniegas, N., & Inga Ortega, E. (2016). Optimizing a network for smart home based on IEEE 802.15.4g for advanced metering infrastructure. I+D Tecnológico, 12(2), 79-88. Retrieved from https://revistas.utp.ac.pa/index.php/id-tecnologico/article/view/1238
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(3) A. Boustani, M. Jadliwala, H. M. Kwon, and N. Alamatsaz, “Optimal Resource Allocation in Cognitive Smart Grid Networks,” pp. 499–506, 2015.
(4) M. Collotta and G. Pau, “A Novel Energy Management Approach for Smart Homes using Bluetooth Low Energy,” IEEE J. Sel. Areas Commun., vol. 33, no. 12, pp. 1–1, 2015.
(5) S. E. Nezhad, H. J. Kamali, and M. E. Moghaddam, “Solving KCoverage Problem in Wireless Sensor Networks Using Improved Harmony Search,” 2010 Int. Conf. Broadband, Wirel. Comput. Commun. Appl., pp. 49–55, 2010.
(6) D.-M. Han and J.-H. Lim, “Smart home energy management system using IEEE 802.15.4 and ZigBee,” IEEE Trans. Consum. Electron., vol. 56, no. 3, pp. 1403–1410, 2010.
(7) M. Erol-Kantarci and H. T. Mouftah, “Wireless Sensor Networks for Cost-Efficient Residential Energy Management in the Smart Grid,” IEEE Trans. Smart Grid, vol. 2, no. 2, pp. 314 –325, 2011.
(8) R. Amin and J. Martin, “Smart Grid Communication using Next Generation Heterogeneous Wireless Networks,” Smart Grid Commun. (SmartGridComm), 2012 IEEE Third Int. Conf., pp. 229– 234, 2012.
(9) C. S. Sum, F. Kojima, and H. Harada, “Coexistence of homogeneous and heterogeneous systems for IEEE 802.15.4g smart utility networks,” 2011 IEEE Int. Symp. Dyn. Spectr. Access Networks, DySPAN 2011, no. d, pp. 510–520, 2011.
(10) R. Missaoui, H. Joumaa, S. Ploix, and S. Bacha, “Managing energy Smart Homes according to energy prices: Analysis of a Building Energy Management System,” Energy Build., vol. 71, pp. 155–167, 2014. [11] Y. Liu, “Wireless Sensor Network Applications in Smart Grid : Recent Trends and Challenges,” vol. 2012, pp. 2–7, 2012. [12] D. F. R. Hincapié and S. Céspedes, “Evaluation of mesh-under and route-over routing strategies in AMI systems,” Commun. Conf. (COLCOM), 2012 IEEE Colomb., pp. 1–6, 2012.
(13) O. Asad, M. Erol-Kantarci, and H. Mouftah, “Sensor network web services for Demand-Side Energy Management applications in the smart grid,” Consum. Commun. Netw. Conf. (CCNC), 2011 IEEE, pp. 1176–1180, 2011.
(14) F. Viani, F. Robol, A. Polo, P. Rocca, G. Oliveri, and A. Massa, “Wireless architectures for heterogeneous sensing in smart home applications: Concepts and real implementation,” Proc. IEEE, vol. 101, no. 11, pp. 2381–2396, 2013.
(15) R. Hincapié, “Optimal Planning for Cellular Networks for Smart Metering Infrastructure in Rural and Remote Areas * Óptima Planeación de Redes Celulares para la Infraestructura de Medición Inteligente en Zonas Rurales y Remotas,” vol. 11, no. 2, pp. 49–58, 2015.
(16) G. Koutitas and L. Tassiulas, “A delay based optimization scheme for peak load reduction in the smart grid,” Proc. 3rd Int. Conf. Futur. Energy Syst. Where Energy, Comput. Commun. Meet - e-Energy ’12, pp. 1–4, 2012.
(17) I. Workshop and S. Processing, “A LARGE SCALE AND LOW COST SOLUTION FOR REAL-TIME INDOOR Universit ´ e de technologie de Troyes Institut Charles Delaunay ICD , UMR STMR 6279 BP 2060 - 10010 TROYES Cedex email : [email protected],” no. 2, pp. 392–395, 2011.
(18) A. R. Devidas, T. S. Subeesh, and M. V. Ramesh, “Design and implementation of user interactive wireless smart home energy management system,” 2013 Int. Conf. Adv. Comput. Commun. Informatics, pp. 626–631, 2013.
(19) S. K. Das, D. J. Cook, A. Bhattacharya, E. O. Heierman, and T. Y. Lin, “The role of prediction algorithms in the MavHome smart home architecture,” IEEE Wirel. Commun., vol. 9, no. 6, pp. 77–84, 2002. [20] E. Inga, G. Arevalo, and R. Hincapié, “Optimal deployment of cellular networks for Advanced Measurement Infrastructure in Smart Grid,” Commun. Comput. (COLCOM), 2014 IEEE Colomb. Conf., pp. 1–6, 2014.