Abstract
Driven by the increasing use of mobile phone’s user, major telecommunication providers deploy more base stations to cover a wider geographic area. However, that leads to soaring energy consumption. The primary contribution of this paper is to propose a visual analytics approach to enhance energy awareness for cellular network planning. With the goal of increasing energy efficiency and maintaining the quality of service, we present a map-based visual analysis tool called Aureole for the exploration and analysis of cellular networks in spatial and temporal aspects. Moreover, it was designed with circular composition theory to allow users to concentrate on the area of interest while not losing the context information. With this method, users can conduct a multi-level analysis of the cellular network. Finally, we show the effectiveness of the approach in a set of usage scenarios.
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References
Arietta SM, Efros AA, Ramamoorthi R, Agrawala M (2014) City forensics: using visual elements to predict non-visual city attributes. IEEE Trans Vis Comput Graph 20(12):2624–2633
Arnheim R (1956) Art and visual perception: a psychology of the creative eye. Univ of California Press, Oakland
Boroumand A, Rajaee T (2017) Discrete entropy theory for optimal redesigning of salinity monitoring network in san francisco bay. Water Sci Technol Water Supply 17(2):606–612
Calabrese F, Pereira FC, Di Lorenzo G, Liu L, Ratti C (2010) The Geography of taste: analyzing cell-phone mobility and social events. In: Floréen P, Krüger A, Spasojevic M (eds) Pervasive computing. Pervasive 2010. Lecture notes in computer science, vol 10. Springer, Berlin, Heidelberg, pp 22–37
De Montjoye Y-A, Hidalgo CA, Verleysen M, Blondel VD (2013) Unique in the crowd: the privacy bounds of human mobility. Sci Rep 3(6):1376
Jiang H, Wu Y, Zhang Y, Wang S, Zhang Y (2017) From social community to spatio-temporal information: a new method for mobile data exploration. J Vis Lang Comput 41:1–9
Liu D, Weng D, Li Y, Bao J, Zheng Y, Qu H, Wu Y (2016) Smartadp: visual analytics of large-scale taxi trajectories for selecting billboard locations. IEEE Trans Vis Comput Graph 23(1):1–10
Marsan MA, Chiaraviglio L, Ciullo D, Meo M (2009) Optimal energy savings in cellular access networks. In: Communications workshops, 2009. ICC Workshops 2009. IEEE international conference. IEEE, pp. 1–5
Meulemans W, Riche NH, Speckmann B, Alper B, Dwyer T (2013) Kelpfusion: a hybrid set visualization technique. IEEE Trans Vis Comput Graph 19(11):1846–1858
Niu Z (2011) Tango: traffic-aware network planning and green operation. Wirel Commun IEEE 18(5):25–29
Ofcom GC, Plextek GM, Plextek CF, Eftec EO, Eftec ID, Forster C, Dickie I, Maile G, Smith H, Crisp M (2009) Understanding the environmental impact of communication systems. https://www.ofcom.org.uk/__data/assets/pdf_file/0026/31886/environ.pdf. Accessed 3 May 2017
Proebster M, Kaschub M, Valentin S (2011) Context-aware resource allocation to improve the quality of service of heterogeneous traffic. In: Proceedings of the IEEE international conference on communications (ICC), Context-aware resource allocation to improve the quality of service of heterogeneous traffic, ACM, USA, 2011, pp 1–6
Pulselli R, Ramono P, Ratti C, Tiezzi E (2008) Computing urban mobile landscapes through monitoring population density based on cellphone chatting. Int J Des Nat Ecodyn 3(2):121–134
Son K, Kim H, Yi Y, Krishnamachari B (2011) Base station operation and user association mechanisms for energy-delay tradeoffs in green cellular networks. IEEE J Sel Areas Commun 29(8):1525–1536
Werstuck C, Coulibaly P (2017) Hydrometric network design using dual entropy multi-objective optimization in the Ottawa River Basin. Hydrol Res 48(6):1639–1651
Wu F, Zhu M, Wang Q, Zhao X, Chen W, Maciejewski R (2017) Spatial-temporal visualization of city-wide crowd movement. J Vis 20(2):183–194
Wu W, Xu J, Zeng H, Zheng Y, Qu H, Ni B, Yuan M, Ni LM (2016) Telcovis: visual exploration of co-occurrence in urban human mobility based on telco data. IEEE Trans Vis Comput Graph 22(1):935–944
Xie Q, Liu X, Yan X (2016) Base station location optimization based on the google earth and acis. International conference on human centered computing. Springer, Cham, pp 487–496
Yi Z, Peng Y, Wang T, Zhang X, Wang W (2016) Traffic scenario recognition and analysis for wireless cellular system: from social network perspective. In: 2016 IEEE canadian conference on electrical and computer engineering (CCECE), pp 1–5
Yigitel MA, Incel OD, Ersoy C (2015) Qos vs. energy: a traffic-aware topology management scheme for green heterogeneous networks. Comput Netw 78:130–139
Zhou S, Gong J, Yang Z, Niu Z, Yang P (2009) Green mobile access network with dynamic base station energy saving. ACM MobiCom 9:10–12
Acknowledgements
This work is supported by National Key Research and Development Program of China (2016QY04W0801), the Fund of Fundamental Sichuan Civil-military Integration Institute (No. JMRH01) and the Fund of Sichuan Province Science and Technology Program (2017TJPT0200, 2017KZ0023, 2017GZ0186).
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Jiang, H., Tang, K., Zhao, W. et al. Aureole: a multi-perspective visual analytics approach for green cellular networks. J Vis 21, 485–494 (2018). https://doi.org/10.1007/s12650-017-0467-x
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DOI: https://doi.org/10.1007/s12650-017-0467-x