ENERY EFFICIENT NEW DATA AGGREGATION METHOD FOR IoT

Authors

  • Vani S Badiger
  • Dr.anashree. T.S

Keywords:

Data aggregation, Internet of Things, Power productivity, Power utilization, Network lifetime.

Abstract

Energy Efficiency is one of the essential difficulties in remote sensor arrange (WSNs) provisioning for continuous information, for example, sound and video in huge Internet of Things. Information collection based plans are exceptionally utilized so as to keep up attractive assistance nature of the detected information from the earth, such plans accumulate and total information parcels in an effective way in order to build arrange lifetime, lessen power utilization, organize overhead, traffic clog, and information exactness, and so forth. In this paper, a power effective hybrid information aggregation (PEHDA) plot is proposed. The proposed conspire consolidates a portion of the attentional highlights of the group and tree-based information collection plans while tending to a portion of their significant restrictions. Reproduction results show that power effective hybrid data aggregation (PEHDA) beats group and tree-based conglomeration conspires regarding power utilization, arrange lifetime, and transmission inactivity.

Downloads

Download data is not yet available.

References

1.Conference proceeding

Azharuddin M, Kuila P, Jana PK (2015) Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks. Comput Electr Eng 41:177–190.

2. Conference proceeding

Bahi JM, Makhoul A, Medlej M (2014) A two tiers data aggregation scheme for periodic sensor networks. Ad-hoc & Sensor Wireless Networks 21(1-2):77–100.

3. Conference proceeding

Geetha V, Kallapur PV, Tellajeera S (2012) Clustering in wireless sensor networks: performance comparison of LEACH & LEACH-C protocols using NS2. Procedia Technol 4:163–170.

6.2.Journal Article

Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans WirelCommun 1(4):660–670.

5. Journal Article

Heinzelman WR, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsen-sor networks. In: 33rd annual Hawaii international conference on System sciences, IEEE, pp 10–19.

6. Journal Article

Karthikeyan B, Velumani M, Kumar R, Inabathini S (2015) Analysis of data aggregation in wireless sensor network. In: 2nd international conference on electronics and communication systems (ICECS), pp 1435–1439.

7. Journal Article

Kaur S, Gangwar R (2016) A study of tree based data aggregation techniques for WSNs. International Journal of Database Theory and Application 9(1):109–118.

8. Journal Article

Keswani K, Bhaskar A (2016) Wireless sensor networks: a survey. Futuristic Trends in Engineering, Science, Humanities, and Technol-ogy (FTESHT)

pp 1–7.

9. Journal Article

Mantri D, Prasad NR, Prasad R, Ohmori S (2012) Two tier cluster based data aggregation (TTCDA) in wireless sensor network. In: International conference on advanced networks and telecommuncations systems (ANTS), IEEE, pp 117–122.

10. Journal Article

Meng L, Zhang H, Zou Y (2011) Data aggregation transfer pro-tocol based on clustering and data prediction in wireless sensor networks. In: 7th international conference on wireless communi-cations, networking and mobile computing (WiCOM), IEEE, pp 1–5.

11. Journal Article

Misra G, Kumar V, Agarwal A, Agarwal K (2016) Internet of things (IoT) technological analysis and survey on vision, concepts, challenges, innovation directions, technologies, and applications. American Journal of Electrical and Electronic Engineering 4(1):23–32.

12. Chapter in a Book

NS (2009) Network simulator-NS2. http://www.isi.edu/nsnam/ns.

13. Conference proceeding

Pandey V (2010) A review on data aggregation techniques in wireless sensor network. J Electron Electr Eng 1(2):1–8.

14. Journal Article

Pantazis N, Nikolidakis S, Vergados D (2013) Energy-efficient routing protocols in wireless sensor networks: a survey. IEEE CommunSurv Tutorials 15(2):551–591.

15. Journal Article

Rahman H, Ahmed N, Hussain MI (2016) A hybrid data aggregation scheme for provisioning Quality of Service (QoS) in Internet of Things (IoT). In: 2016 cloudification of the internet of things (CIoT), pp 1–5.

16. Conference proceeding

Rajasekaran A, Nagarajan V (2016) Improved cluster head selection for energy efficient data aggregation in sensor networks. Int J Appl Eng Res 11(2):1379–1385.

17. Journal Article

.Ray A, De D (2012) Data aggregation techniques in wireless sensor network: a survey. International Journal of Engineering Innovation and Research 1(2):81–92.

18. Journal Article

Sain.i S, Singh RS, Gupta V (2010) Analysis of energy efficient routing protocols in wireless sensor networks. International Journal of Computer Science and Communications 1(1):113–118.

19. Conference proceeding

Satapathy SS, Sarma N (2006) TREEPSI: tree based energy efficient protocol for sensor information. In: International conference on wireless and optical communications networks, IFIP, pp 4–7.

20. Conference proceeding

Sirsikar S, Anavatti S (2015) Issues of data aggregation methods in wireless sensor network: a survey. Procedia Computer Science 49:194–201.

21. Journal Article

Solis I, Obraczka K (2004) The impact of timing in data aggregation for sensor networks. In: International conference on communications, IEEE, vol 6, pp 3640– 3645.

22. Journal Article Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 3(4):366–379.

23. Conference proceeding

Zeng D, Guo S, Cheng Z (2011) The web of things: a survey. J Commun 6(6):424–438.

Downloads

Published

2021-06-30

How to Cite

Badiger, V. S. ., & T.S, D. (2021). ENERY EFFICIENT NEW DATA AGGREGATION METHOD FOR IoT. The Journal of Contemporary Issues in Business and Government, 27(3), 1834–1848. Retrieved from https://cibgp.com/au/index.php/1323-6903/article/view/1793