Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Non-isolated Sextuple Output Hybrid Triad Converter Configurations for High Step-Up Renewable Energy Applications Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Energy-Aware Data Aggregation Techniques in Wireless Sensor Network

Authors : M. Ambigavathi, D. Sridharan

Published in: Advances in Power Systems and Energy Management

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

A Wireless Sensor Network (WSN) is an exigent technology and it has huge number of applications in disaster management, health monitoring, military, security, and so on. This network faces some critical barriers like fault tolerance, energy consumption due to heterogeneous traffic loads and redundant data transmission. In which, nodes are miniscule and have restricted capability of processing with reduced power of battery. This limitation of reduced power of battery makes the sensor network prone to failure. Data aggregation is a vital technique for active data processing in WSN. With the support of data aggregation, the energy depletion is minimized by eliminating redundant data or by decreasing the number of sent packets. This study reviews various data aggregation techniques such as clustered aggregation, tree-based aggregation, in-network aggregation, and centralized data aggregation with focus on energy consumption of sensor nodes.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
previous chapter Ecology and Energy Dimension in Infrastructural Designs
next chapter Design and Performance Analysis of Noise Equivalent Model for Optical Fiber Link
Literature
1.
Sneha, R., Nithya, D.: Wireless sensor network: a survey. Int. J. Adv. Res. Comput. Sci. Soft. Eng. 6(2), 92–95 (2016). ISSN: 2277 128X
2.
Maraiya, K., Kant, K., Gupta, N.: Architectural based data aggregation techniques in wireless sensor network: a comparative study. Int. J. Comput. Sci. Eng. (IJCSE) 3(3), 1131–1138 (2011). ISSN: 0975-3397
3.
Cheng, C.-T., Leung, H., Maupin, P.: A delay-aware network structure for wireless sensor networks with in-network data fusion. IEEE Sens. J. 13(5), 1622–1631 (2013)
4.
Rajeswari, A., Kalaivaani, P.T.: Energy efficient routing protocol for wireless sensor networks using spatial correlation based medium access control protocol compared with IEEE 802.11. In: International Conference on Process Automation, Control and Computing (PACC), pp. 1–6 (2011)
5.
Hirani, P.K.: Energy-efficiency based clustering and data aggregation for wireless sensor networks. Int. J. Comput. Appl. 119(21), 1–4 (2015)
6.
Patel, R.B., Aseri, T.C., Kumar, D.: Energy efficiency heterogeneous clustered scheme for wireless sensor network. Elsevier Int. J. Comput. Commun. 32, 662–667 (2009)
7.
Krishna, M.B., Vashishta, N.: Energy efficient data aggregation techniques in wireless sensor networks. In: 5th International Conference on Computational Intelligence and Communication Networks, pp. 160–165 (2013). doi:10.​1109/​CICN.​2013.​143
8.
Ujawe, P.V., Khiani, S.: Review on data aggregation techniques for energy efficiency in wireless sensor networks. Int. J. Emerg. Technol. Adv. Eng. 4(7), 142–145 (2014). ISSN 2250-2459
9.
Yuan, F., Zhan, Y., Wang, Y.: Data density correlation degree clustering method for data aggregation in WSN. IEEE Sens. J. 14(4), 1089–1098 (2014)
10.
Atoui, I., Ahmadt, A., Medlej, M.: Tree-based Data aggregation approach in wireless sensor network using fitting functions. 146–150 (2016). ISBN: 978-1-4673-7504-7
11.
He (Selena), J., Ji, S., Pan, Y., Li, Y.: Constructing load-balanced data aggregation trees in probabilistic wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 25(7), 1681–1690 (2014)
12.
Chinh Hoang, D., Kumar, R., Kumar Panda, S.: Optimal data aggregation tree in wireless sensor networks based on intelligent water drops algorithm. IET J. Wireless Sens. Syst. 2(3), 282–292 (2012)
13.
Zhao, C., Zhang, W., Yang, Y., Yao, S.: Treelet-based clustered compressive data aggregation for wireless sensor networks. IEEE Trans. Veh. Technol. 64(9), 4257–4267 (2015)
14.
Kaur, S., Gangwar, R.C.: A study of tree based data aggregation techniques for WSNs. Int. J. Database Theor. Appl. 9(1), 109–118 (2016)
15.
Boubiche, D.E., Boubiche, S., Bilami, A.: A Cross-layer watermarking-based mechanism for data aggregation integrity in heterogeneous WSNs. IEEE Commun. Lett. 19(5), 823–826 (2015)
16.
Harb, H., Makhoul, A., Tawil, R., Jaber, A.: Energy-efficient data aggregation and transfer in periodic sensor networks. IET J. Wireless Sens. Syst. 4(4), 149–158 (2014)
17.
Joo, C., Shroff, N.B.: On the delay performance of in-network aggregation in lossy wireless sensor networks. IEEE/ACM Trans. Netw. 22(2), 662–672 (2014)
18.
Rohankar, R., Katti, C.P., Kumar, S.: Comparison of energy efficient data collection techniques in wireless sensor networks. Procedia Comput. Sci. 57, 146–151 (2015)CrossRef
19.
Bagaa, M., Challal, Y., Ksentini, A.: Data aggregation scheduling algorithms in wireless sensor networks: solutions and challenges. IEEE Commun. Surv. Tutorials 16(3), 1339–1369 (2014)
20.
Dagar, M., Mahajan, S.: Data aggregation in wireless sensor network: a survey. Int. J. Inf. Comput. Technol. 3(3), 167–174 (2013). ISSN 0974-2239
21.
Gopikrishnan, S., Priakanth, P., Mahendhiran, P.D.: A survey of energy efficient data aggregation schemes in wireless sensor networks. Middle-East J. Sci. Res. 23(10), 2603–2612 (2015)
22.
Yu, Y., Prasanna, V.K., Krishnamachari, B.: Energy minimization for real-time data gathering in wireless sensor networks. IEEE Trans. Wireless Commun. 5(11), 3087–3096 (2006)
Metadata
Title
Energy-Aware Data Aggregation Techniques in Wireless Sensor Network
Authors
M. Ambigavathi
D. Sridharan
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Power Systems and Energy Management

Print ISBN: 978-981-10-4393-2

Electronic ISBN: 978-981-10-4394-9

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-4394-9_17