Abstract
Daily human actions cause positive or negative side effects on Environment. A city is a kind of Environment that supports a big amount of people daily causing side effects on it. Urban wastes and car driving are typical actions that pollute the city. Smart city treats to reinvent cities making them a good living environment. Wireless Sensor Networks are the base technology of Smart cities. These networks are in charge to sense physical variables that could feedback the behaviour of humans. These sensors usually send data to a cloud server for applying big data technology in order to discover behaviour patterns of humans. In this way a smart city could take corrective actions in order to reduce, for example, polluted air in a critical zone. But the sensors and the backbone network that send data to that server also consume electric power. Usually the wireless backbone elements are always turned on, which could incur a high pattern of electric energy consumption. In this paper we present a new mechanism for energy saving in the wireless backbone network. Our energy saving mechanism also allows us to produce a portable wireless backbone network that could be used in several places.
Similar content being viewed by others
References
Yi WY, Lo KM, Mak T, Leung KS, Leung Y, Meng ML (2015) A survey of wireless sensor network based air pollution monitoring systems. Sensors 15:31392–31427. doi:10.3390/s151229859
Seidl M, Da G, Ausset P, Haenn S, Géhin E, Moulin L (2016) Evaluating exposure of pedestrians to airborne contaminants associated with non-potable water use for pavement cleaning. Environ Sci Pollut Res 23(7):6091–6101. doi:10.1007/s11356-015-5062-x
Ericsson (2015) Technology for good. Ericsson sustainability and corporate responsibility report. https://www.esmartcity.es/images/ESMARTCITY/media/content/. 2015-corporate-responsibility-and-sustainability-report.pdf. Accessed 15 Jul 2016
Greengard S (2015) The internet of things. The MIT Press Essential Knowledge series
He Y, Stojmenovic I, Liu Y, Gu Y (2014) Smart city. Int J Distrib Sens N 2014:867593. doi:10.1155/2014/867593
Escolar S, Carretero J, Marinescu MC, Chessa S (2014) Estimating energy savings in smart street lighting by using an adaptive control system. Int J Distrib Sens N 2014:971587. doi:10.1155/2014/971587
Cellucci L, Burattini C, Drakou D, Gugliermetti F, Bisegna F, Vollaro AL, Salata F, Golasi I (2015) Urban lighting project for a small town: comparing citizens and authority benefits. Sustainability 7(10):14230–14244. doi:10.3390/su71014230
Rodríguez J, Martínez JF, Castillejo P, Diego R (2013) SMArc: a proposal for a smart, semantic middleware architecture focused on smart city energy management. Int J Distrib Sens N 2013:560418. doi:10.1155/2013/560418
Li Q, Yang P (2014) eCOTS: efficient and cooperative task sharing for large-scale smart city sensing application. Int J Distrib Sens N 2014:463876. doi:10.1155/2014/463876
Ha RH, Ho PH, Shen XS (2010) Optimal sleep scheduling with transmission range assignment in application-specific wireless sensor networks. International Journal of Sensor Networks 1:1–17. doi:10.1504/IJSNET.2006.010836
Olwal TO, Van Wyk BJ, Ntlatlapa N, Djouani K, Siarry P, Hamam Y (2010) Dynamic power control for wireless backbone mesh networks: a survey. Network Protocols and Algorithms 2(1):1–44. doi:10.5296/npa.v2i1.336
Lanza J, Sánchez L, Muñoz L, Galache JA, Sotres P, Santana JR, Gutiérrez V (2015) Large-scale mobile sensing enabled internet-of-things testbed for smart city services. Int J Distrib Sens N. doi:10.1155/2015/785061
Shi J, Wei X, Zhu W (2016) An efficient algorithm for energy management in wireless sensor networks via employing multiple mobile sinks. Int J Distrib Sens N 2016:3179587 doi:10.1155/2016/3179587
Ebadi S (2012) A multihop clustering algorithm for energy saving in wireless sensor networks. ISRN Sensor Networks 2012(2012):817895. doi:10.5402/2012/817895
Shaikh FK, Zeadally S (2016) Energy harvesting in wireless sensor networks: a comprehensive review. Renew Sust Energ Rev 55:1041–1054. doi:10.1016/j.rser.2015.11.010
Kim HY (2016) An energy-efficient load balancing scheme to extend lifetime in wireless sensor networks. Cluster Comput 19(1):279–283. doi:10.1007/s10586-015-0526-9
Rani S, Ahmed SH (2016) Multi-hop routing in wireless sensor networks: An overview, taxonomy, and research challenges. Springer Singapore. ISBN: 978–981–287-729-1 (Print) 978–981–287-730-7 (Online), 2016, doi:10.1007/978-981-287-730-7
Alotaibi E, Mukherjee B (2012) A survey on routing algorithms for wireless ad-hoc and mesh networks. Comput Netw 56(2):940–965. doi:10.1016/j.comnet.2011.10.011
Vijayakumar KP, Ganeshkumar P, Anandaraj M (2012) Review on routing algorithms in wireless mesh networks. International Journal of Computer Science and Telecommunications 3(5):87–92
Ahmeda SS, Farhan RK (2014) Routing protocols for wireless mesh networks: performance study. In: International congress on computer, electronics, electrical, and communication engineering. ICCEECE 2014, p 142–148 doi:10.7763/IPCSIT.2014.V59.26
Data Synergy (2016) Wake on LAN. www.datasynergy.co.uk/products/wakeman/pdfs/Wake-on-LANExplained.pdf. Accessed 15 Jul 2016
Linksys official support (2016) Wireless-G BroadBand router. http://www.linksys.com/us/support-product?pid=01t80000003KXPxAAO. Accessed 15 Jul 2016
Unleash your router (2016). http://www.dd-wrt.com/site/index. Accessed 15 Jul 2016
OCU (2016). Consumption in standby. http://www.ocu.org/vivienda-y-energia/nc/calculadora/consumo-en-stand-by. Accessed 15 Jul 2016
Linksys official support (2016). Linksys WRT160NL Wireless-N broadband router with storage link. http://www.linksys.com/us/support-product?pid=01t80000003K7eJAASXX 19. Accessed 15 Jul 2016
Jain K, Padhye J, Padmanabhan VN, Qiu L (2005) Impact of interference on multi-hop wireless network performance. Wirel Netw 11(4):471–487. doi:10.1007/s11276-005-1769-9
Barcelona WiFi map (2016). http://w152.bcn.cat/PlanolBCN/es/act/wifi-bcn-P001/. Accessed 15 Jul 2016
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Marrero, D., Macías, E., Suárez, Á. et al. Energy Saving in Smart City Wireless Backbone Network for Environment Sensors. Mobile Netw Appl 24, 700–711 (2019). https://doi.org/10.1007/s11036-016-0786-5
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11036-016-0786-5