Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2020

29.01.2020

An Effective Relay Node Selection Technique for Energy Efficient WSN-Assisted IoT

verfasst von: Anurag Shukla, Sarsij Tripathi

Erschienen in: Wireless Personal Communications | Ausgabe 4/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The internet of things (IoT) is one of the emerging network paradigms that are reducing the distance between the physical and cyber world. In wireless sensor Network (WSN)-assisted IoT, hundreds to thousands of sensor nodes are deployed at a large scale, which in turn increases the complexity. Therefore, the issues and challenges of such network differ from WSN. The sensor nodes are an important component of WSN-Assisted IoT network running on limited and non-rechargeable energy resource. So, developing robust and energy-efficient routing protocol is a challenging task to prolong the network lifetime. In contrast to the state-of-the-art techniques this paper introduces: (1) a hierarchical cluster framework for network deployment; (2) an effective Relay Node (RN) selection scheme by considering the following parameters: node density in the cluster, shortest distance node selection as a RN, RN communication range as threshold distance for next RN selection; (3) an efficient routing algorithm to meet the requirement of proposed model. The proposed protocol has been compared with standard WSN routing protocols, viz., LEACH, MOD-LEACH, ME-CBCCP, EESAA, TDEEC, DEEC, and SEP. By extensive simulation for various network parameters, the proposed effective relay node selection for energy efficient consumption protocol found to be more effective in terms of network lifetime, energy consumption and supports scalability.
Vorheriger Artikel Two-Stage Ransomware Detection Using Dynamic Analysis and Machine Learning Techniques
Nächster Artikel Data Replication in Mobile Edge Computing Systems to Reduce Latency in Internet of Things

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

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!

Jetzt informieren

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!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
2.
Jelicic, V., Magno, M., Brunelli, D., Paci, G., & Benini, L. (2013). Context-adaptive multimodal wireless sensor network for energy-efficient gas monitoring. IEEE Sensors Journal,13(1), 328–338.CrossRef
3.
Dener, M. (2018). A new energy efficient hierarchical routing protocol for wireless sensor networks. Wireless Personal Communications,101(1), 269–286.CrossRef
4.
Huang, J., Meng, Y., Gong, X., Liu, Y., & Duan, Q. (2014). A novel deployment scheme for green internet of things. IEEE Internet of Things Journal,1(2), 196–205.CrossRef
5.
Shen, W., & Wu, Q. (2011). Exploring redundancy in sensor deployment to maximize network lifetime and coverage. In Sensor, Mesh and Ad Hoc communications and networks (SECON), 2011 8th annual IEEE communications society conference on (pp. 557–565). IEEE.
6.
Li, F., Luo, J., Wang, W., & He, Y. (2015). Autonomous deployment for load balancing k-surface coverage in sensor networks. IEEE Transactions on Wireless Communications,14(1), 279–293.CrossRef
7.
Li, F., Luo, J., Xin, S. Q., Wang, W. P., & He, Y. (2012). LAACAD: Load balancing k-area coverage through autonomous deployment in wireless sensor networks. In Distributed computing systems (ICDCS), 2012 IEEE 32nd international conference on (pp. 566–575). IEEE.
8.
Rani, S., Malhotra, J., & Talwar, R. (2013). EEICCP—energy efficient protocol for wireless sensor networks. Wireless sensor network,5(07), 127.CrossRef
9.
Rani, S., Malhotra, J., & Talwar, R. (2014). Energy efficient protocol for densely deployed homogeneous network. In Issues and challenges in intelligent computing techniques (ICICT), 2014 international conference on (pp. 292–298). IEEE.
10.
Xu, M., & Leung, H. (2011). A joint fusion, power allocation and delay optimization approach for wireless sensor networks. IEEE Sensors Journal,11(3), 737–744.CrossRef
11.
Lee, J. S., & Cheng, W. L. (2012). Fuzzy-logic-based clustering approach for wireless sensor networks using energy predication. IEEE Sensors Journal,12(9), 2891–2897.CrossRef
12.
Majumder, R., Bag, G., & Kim, K. H. (2012). Power sharing and control in distributed generation with wireless sensor networks. IEEE Transactions on Smart Grid,3(2), 618–634.CrossRef
13.
Ye, W., Heidemann, J., & Estrin, D. (2002). An energy-efficient MAC protocol for wireless sensor networks. In INFOCOM 2002, Twenty-First annual joint conference of the IEEE computer and communications societies. Proceedings. IEEE (Vol. 3, pp. 1567–1576). IEEE.
14.
Cardei, M., Thai, M. T., Li, Y., & Wu, W. (2005). Energy-efficient target coverage in wireless sensor networks. In INFOCOM 2005, 24th annual joint conference of the IEEE computer and communications societies. Proceedings IEEE (Vol. 3, pp. 1976–1984). IEEE.
15.
Liu, C., & Cao, G. (2012). Distributed critical location coverage in wireless sensor networks with lifetime constraint. In INFOCOM, 2012 proceedings IEEE (pp. 1314–1322). IEEE.
16.
Rani, S., Talwar, R., Malhotra, J., Ahmed, S. H., Sarkar, M., & Song, H. (2015). A novel scheme for an energy efficient internet of things based on wireless sensor networks. Sensors,15(11), 28603–28626.CrossRef
17.
Mohamed, R. E., Saleh, A. I., Abdelrazzak, M., & Samra, A. S. (2018). Survey on wireless sensor network applications and energy efficient routing protocols. Wireless Personal Communications,101(2), 1019–1055.CrossRef
18.
Kapnadak, V., & Coyle, E. J. (2011). Optimal non-uniform deployment of sensors for detection in single-hop wireless sensor networks. In Sensor, Mesh and Ad Hoc communications and networks (SECON), 2011 8th annual IEEE communications society conference on (pp. 89–97). IEEE.
19.
Xu, X., Ansari, R., & Khokhar, A. (2013). Power-efficient hierarchical data aggregation using compressive sensing in WSNs. In 2013 IEEE international conference on communications (ICC) (pp. 1769–1773). IEEE.
20.
Yang, D., Misra, S., Fang, X., Xue, G., & Zhang, J. (2012). Two-tiered constrained relay node placement in wireless sensor networks: computational complexity and efficient approximations. IEEE Transactions on Mobile Computing,11(8), 1399–1411.CrossRef
21.
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In System sciences, 2000. Proceedings of the 33rd annual Hawaii international conference on (p. 10). IEEE.
22.
Manap, Z., Ali, B. M., Ng, C. K., Noordin, N. K., & Sali, A. (2013). A review on hierarchical routing protocols for wireless sensor networks. Wireless Personal Communications,72(2), 1077–1104.CrossRef
23.
Aslam, M., Javaid, N., Rahim, A., Nazir, U., Bibi, A., & Khan, Z. A. (2012). Survey of extended LEACH-based clustering routing protocols for wireless sensor networks. In High performance computing and communication and 2012 IEEE 9th international conference on embedded software and systems (HPCC-ICESS), 2012 IEEE 14th international conference on (pp. 1232–1238). IEEE.
24.
Buttyán, L., & Schaffer, P. (2010). Position-based aggregator node election in wireless sensor networks. International Journal of Distributed Sensor Networks,6(1), 679205.CrossRef
25.
Jung, S. M., Han, Y. J., & Chung, T. M. (2007). The concentric clustering scheme for efficient energy consumption in the PEGASIS. In Advanced communication technology, The 9th international conference on (Vol. 1, pp. 260–265). IEEE.
26.
Saini, P., & Sharma, A. K. (2010). Energy efficient scheme for clustering protocol prolonging the lifetime of heterogeneous wireless sensor networks. International Journal of Computer Applications,6(2), 30–36.CrossRef
27.
Shah, T., Javaid, N., & Qureshi, T. N. (2012). Energy efficient sleep awake aware (EESAA) intelligent sensor network routing protocol. In Multitopic conference (INMIC), 2012 15th international (pp. 317–322). IEEE.
28.
Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. Boston University Computer Science Department.
29.
Loscri, V., Morabito, G., & Marano, S. (2005). A two-levels hierarchy for low-energy adaptive clustering hierarchy (TL-LEACH). In Vehicular technology conference, 2005. VTC-2005-Fall. 2005 IEEE 62nd (Vol. 3, pp. 1809–1813). IEEE.
30.
Kumar, D., & Patel, R. B. (2011). Multi-hop data communication algorithm for clustered wireless sensor networks. International Journal of Distributed Sensor Networks,7(1), 984795.CrossRef
31.
Younis, O., & Fahmy, S. (2004). HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing,3(4), 366–379.CrossRef
32.
Yueyang, L., Hong, J., & Guangxin, Y. (2006). An energy-efficient PEGASIS-based enhanced algorithm in wireless sensor networks. China Communications, 91–97.
33.
Lee, S., Yoo, J., & Chung, T. (2004). Distance-based energy efficient clustering for wireless sensor networks. In Local computer networks, 2004. 29th annual IEEE international conference on (pp. 567–568). IEEE.
34.
Dehghani, S., Barekatain, B., & Pourzaferani, M. (2018). An enhanced energy-aware cluster-based routing algorithm in wireless sensor networks. Wireless Personal Communications,98(1), 1605–1635.CrossRef
35.
Mahmood, D., Javaid, N., Mahmood, S., Qureshi, S., Memon, A. M., & Zaman, T. (2013). MODLEACH: a variant of LEACH for WSNs. In Broadband and wireless computing, communication and applications (BWCCA), 2013 Eighth international conference on (pp. 158–163). IEEE.
36.
Muruganathan, S. D., Ma, D. C., Bhasin, R. I., & Fapojuwo, A. O. (2005). A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Communications Magazine,43(3), S8–13.CrossRef
37.
Ye, M., Li, C., Chen, G., & Wu, J. (2005). EECS: an energy efficient clustering scheme in wireless sensor networks. In Performance, computing, and communications conference, 2005. IPCCC 2005. 24th IEEE international (pp. 535–540). IEEE.
38.
Dehni, L., Krief, F., & Bennani, Y. (2006). Power control and clustering in wireless sensor networks. In Challenges in Ad Hoc networking (pp. 31–40). Springer, Boston, MA.
39.
Rani, S., Malhotra, J., & Talwar, R. (2014). On the development of realistic cross layer communication protocol for wireless sensor networks. Wireless Sensor Network,6(05), 57.CrossRef
40.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications,1(4), 660–670.CrossRef
41.
Hussain, S., Matin, A. W., & Islam, O. (2007). Genetic algorithm for hierarchical wireless sensor networks. JNW,2(5), 87–97.CrossRef
42.
Bara’a, A. A., & Khalil, E. A. (2012). A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks. Applied Soft Computing,12(7), 1950–1957.CrossRef
43.
Mittal, V., Gupta, S., & Choudhury, T. (2018). Comparative analysis of authentication and access control protocols against malicious attacks in wireless sensor networks. In Smart computing and informatics (pp. 255–262). Springer, Singapore.
44.
Han, Z., Wu, J., Zhang, J., Liu, L., & Tian, K. (2014). A general self-organized tree-based energy-balance routing protocol for wireless sensor network. IEEE Transactions on Nuclear Science,61(2), 732–740.CrossRef
45.
Chang, J. H., & Tassiulas, L. (2000). Energy conserving routing in wireless ad-hoc networks. In INFOCOM 2000, Nineteenth annual joint conference of the IEEE computer and communications societies. Proceedings. IEEE (Vol. 1, pp. 22–31). IEEE.
46.
Solaiman, B. (2016). Energy optimization in wireless sensor networks using a hybrid k-means pso clustering algorithm. Turkish Journal of Electrical Engineering and Computer Sciences,24(4), 2679–2695.CrossRef
47.
Deniz, F., Bagci, H., & Korpeoglu, I. (2016). An adaptive, energy-aware and distributed fault-tolerant topology-control algorithm for heterogeneous wireless sensor networks. Ad Hoc Networks,44, 104–117.CrossRef
48.
Islam, K., Shen, W., & Wang, X. (2012). Wireless sensor network reliability and security in factory automation: a survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews),42(6), 1243–1256.CrossRef
49.
Yildiz, H. U., Temiz, M., & Tavli, B. (2015). Impact of limiting hop count on the lifetime of wireless sensor networks. IEEE Communications Letters,19(4), 569–572.CrossRef
50.
Amjad, M., Afzal, M. K., Umer, T., & Kim, B. S. (2017). QoS-aware and heterogeneously clustered routing protocol for wireless sensor networks. IEEE Access,5, 10250–10262.CrossRef
Metadaten
Titel
An Effective Relay Node Selection Technique for Energy Efficient WSN-Assisted IoT
verfasst von
Anurag Shukla
Sarsij Tripathi
Publikationsdatum
29.01.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07167-8

Weitere Artikel der Ausgabe 4/2020

Wireless Personal Communications 4/2020 Zur Ausgabe

OriginalPaper

Power and Delay Efficient Multilevel Offloading Strategies for Mobile Cloud Computing

OriginalPaper

BLE-Based Authentication Protocol for Micropayment Using Wearable Device

OriginalPaper

Secure Key Management System Integrated in Cell-LEACH (SKMSI-CL)

OriginalPaper

Energy Efficient Routing Structure to Avoid Energy Hole Problem in Multi-Layer Network Model

OriginalPaper

Energy Beamforming for Full-Duplex Wireless Powered Cooperative Communications

BriefCommunication

A Swarm Optimization-Enhanced Data Aggregation Tree Based on a Nonuniform Clustering Structure for Long and Linear Wireless Sensor Networks

Neuer Inhalt

    Bildnachweise