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
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Wireless Networks
Erschienen in: Wireless Networks 4/2017

09.02.2016

CASMOC: a novel complex alliance strategy with multi-objective optimization of coverage in wireless sensor networks

verfasst von: Zeyu Sun, Yongsheng Zhang, Yalin Nie, Wei Wei, Jaime Lloret, Houbing Song

Erschienen in: Wireless Networks | Ausgabe 4/2017

Einloggen

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

search-config
loading …

Abstract

Coverage is a significant performance indicator of wireless sensor networks. Data redundancy in k-coverage raises a set of issues including network congestion, coverage reduction, energy inefficiency, among others. To address these issues, this paper proposes a novel algorithm called complex alliance strategy with multi-objective optimization of coverage (CASMOC) which could improve node coverage effectively. This paper also gives the proportional relationship of the energy conversion function between the working node and its neighbors, and applies this relationship in scheduling low energy mobile nodes, thus achieving energy balance of the whole network, and optimizing network resources. The extensive simulation results demonstrate that CASMOC could not only improve the quality of network coverage, but also mitigate rapid node energy consumption effectively, thereby extending the life cycle of the network significantly.
Vorheriger Artikel Narrowband frequency-selective up-link and down-link evaluation of daily personal-exposure induced by wireless operating networks
Nächster Artikel Effective capacity of receive antenna selection MIMO–OSTBC systems in co-channel interference

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

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 "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"

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.
Wei, W., Yang, X., Shen, P., & Zhou, B. (2012). Holes detection in anisotropic sensornets: Topological methods. International Journal of Distributed Sensor Networks, 2012, 1–9.
2.
Xing, X., Wang, G., & Li, J. (2014). Collaborative target tracking in wireless sensor networks. Ad Hoc & Sensor Wireless Networks, 23(8), 117–135.
3.
Sun, Z., Weiguo, W., Wang, H., Chen, H., & Wei, W. (2014). An optimization strategy coverage control algorithm for WSN. International Journal of Distributed Sensor Networks, 2014, 1–17.
4.
Liao, Z., Wang, J., Zhang, S., & Zhang, X. (2013). A deterministic sensor placement scheme for full coverage and connectivity without boundary effect in wireless sensor networks. Ad Hoc & Sensor Wireless Networks, 19(3–4), 327–351.
5.
Dong, M., Ota, K., Laurence, T. Y., Chang, S., Zhu, H., & Zhou, Z. (2014). Mobile agent-based energy-aware and user-centric data collection in wireless sensor networks. Computer Networks, 74(3), 58–70.CrossRef
6.
Tseng, Y., Chen, P., & Chen, W. (2012). k-Angle object coverage problem in a wireless sensor network. IEEE Sensors Journal, 12(12), 3408–3416.CrossRef
7.
Ghaderi, R., Esnaashari, M., & Meybodi, M. (2014). A cellular learning automata-based algorithm for solving the coverage and connectivity problem in wireless sensor networks. Ad hoc & Sensor Wireless Networks, Ad hoc & Sensor Wireless Networks, 22(4), 171–203.
8.
Yanling, H., Dong, M., Ota, K., Liu, A., & Guo, M. (2014). Mobile target detection in wireless sensor networks with adjustable sensing frequency. IEEE Systems, 8(3), 1–12.CrossRef
9.
Yang, C., & Chin, K. (2014). Novel algorithm for complete targets coverage in energy harvesting wireless sensor networks. IEEE Communications Letters, 18(1), 118–121.MathSciNetCrossRef
10.
Wei, W., & Qi, Y. (2011). Information potential fields navigation in wireless ad-hoc sensor network. Sensor, 2011, 4794–4807.CrossRef
11.
Long, J., Dong, M., Ota, K., Liu, A., & Hai, S. (2015). Reliability guaranteed efficient data gathering in wireless sensor networks. IEEE Access, 3(2), 430–444.CrossRef
12.
Wang, Y., & Tseng, Y. (2008). Distributed deployment schemes for mobile wireless sensor networks to ensure multi-level coverage. IEEE Trans. Parallel and Distributed Systems, 19(9), 1280–1294.CrossRef
13.
Akhtar, F., & Rehmani, M. H. (2015). Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review. Elsevier Renewable and Sustainable Energy Reviews, 45(5), 769–784.CrossRef
14.
Yen, L., Changwu, Yu., & Cheng, Y. (2006). Expected k-coverage in wireless sensor networks. Ad Hoc Networks, 5(4), 636–650.CrossRef
15.
Kong, L., Zhao, M., Liu, X., Jialiang, L., Liu, Y., Minyou, W., & Shu, W. (2014). Surface coverage in sensor network. IEEE Transactions on Parallel and Distributed Systems, 25(1), 234–243.CrossRef
16.
Sendra, S., Fernandez, P., Turro, C., & Lloret, J. (2010). IEEE 802.11a/b/g/n indoor coverage and performance comparison. The Sixth International Conference on Wireless and Mobile Communications (ICWMC 2010), Valencia (Spain), September 20–24, 2010.
17.
Garcia, M., Tomás, J., Boronat, F., & Lloret, J. (2009). The development of two systems for indoor wireless sensors self-location. Ad Hoc & Sensor Wireless Networks, 8(3), 235–258.
18.
Sendra, S., Lloret, J., Turro, C., & Agriar, J. M. (2014). IEEE 802.11a/b/g/n short scale indoor wireless sensor placement. International Journal of Ad Hoc and Ubiquitous Computing, 15(2), 68–82.CrossRef
19.
Mohamed, L., Herve, G., & Mohammed, F. (2010). Cluster-based energy-efficient k-coverage for wireless sensor networks. Network Protocols and Algorithms, 2(2), 89–106.
20.
Suárez, A., Santana, J. A., Maciaslopez, E. M., Mena, V. E., Canino, J. M., & Marrero, D. (2014). RSSI prediction in WiFi considering realistic heterogeneous restrictions. Network Protocols and Algorithms, 4(6), 19–40.CrossRef
21.
Matthieu, L., Faicel, H., & Hichem, S. (2011). Multi-objective optimization in wireless sensors networks, 2011 Internation Conference on Microelectronics (ICM 2011), Hammamet, Tunisia, pp. 1–4, 19–22 Dec. 2011.
22.
Meng, F., Wang, H., & He, H. (2011). Connected coverage protocol using cooperative sensing model for wireless sensor network. Acta Elecronica Sinca, 9(4), 772–779.
23.
Mini, S., Udqata, S. K., & Sabat, S. L. (2014). Sensor deployment and scheduling for target coverage problem in wireless sensor networks. IEEE Sensros Journal, 14(3), 636–644.CrossRef
24.
Li, Y., Chinh, V., Ai, C., Chen, G., & Zhao, Y. (2011). Transforming complete coverage algorithms to partial coverage algorithm for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22(4), 695–703.CrossRef
25.
Iqbal, M., Naeem, M., Anpalagan, A., Ahmed, A., & Azam, M. (2015). Wireless sensor network optimization: multi-objective paradigm. Sensors, 7, 17572–17620.CrossRef
26.
Razafindralambo, T., & Simplotryl, D. (2011). Connectivity preservation and coverage schemes for wireless sensor networks. IEEE Transactions on Automatic Control, 56(10), 2418–2428.MathSciNetCrossRef
27.
Ammari, H. M., & Das, S. K. (2012). Centralized and clustered k-coverage protocols for wireless sensor networks. IEEE Transactions on Computers, 61(1), 118–133.MathSciNetCrossRef
28.
Junzhao, D., Wang, K., Liu, H., & Guo, D. (2013). Maximizing the lifetime of k-discrete barrier coverage using mobile sensors. IEEE Sensors Journal, 13(12), 4690–4701.CrossRef
29.
Zhu, C., Zheng, C., Shu, L., & Han, G. (2012). A survey on coverage and connectivity issues in wireless sensor networks. Journal of Network and Computer Applications, 35(2), 619–632.CrossRef
30.
Xing, X., Wang, G., & Li, J. (2014). Polytype target coverage scheme for heterogeneous wireless sensor networks using linear programming. Wireless Communications and Mobile Computing., 14(8), 1397–1408.CrossRef
31.
Sun, Z., Weiguo, W., Wang, H., Chen, H., & Xing, X. (2014). A novel coverage algorithm based on event-probability-driven mechanism in wireless sensor network. EURSIP Journal on Wireless Communications and Networking, 2014(1), 1–17.CrossRef
32.
Wang, H., Meng, F., & Li, Z. (2010). Energy efficient coverage conserving protocol for wireless sensor networks. Journal of Software, 21(12), 3124–3137.CrossRef
33.
Cheng, T. M., & Savkin, A. V. (2009). A distributed self -deployment algorithm for the coverage of mobile wireless sensor networks. IEEE Communications Letters., 13(11), 877–879.CrossRef
34.
Abrar, H., Chakrabarti, S., & Biswas, P. K. (2012). Impact of sensing model on wireless sensor network coverage. IET Wireless Sensor Systems, 2(3), 272–281.CrossRef
35.
Yoon, Y., & Kim, Y. (2013). An efficient genetic algorithm for maximum coverage deployment in wireless sensor network. IEEE Transactions on Cybernetics., 45(5), 1473–1483.CrossRef
36.
Sundhar Ram, S., Manjunath, D., & Lyer, S. K. (2007). On the path coverage properties of random sensor networks. IEEE Transactions on Mobile Computing, 6(5), 1–13.CrossRef
37.
Cardei, M., & Jie, W. (2005). Energy-efficient coverage problems in wireless ad-hoc sensor networks. Computer Communications, 29(4), 413–420.CrossRef
38.
Zhao, Q., & Mohan, G. (2008). Lifetime maximization for connected target coverage in wireless sensor networks. IEEE/ACM Transactions on Networking, 16(6), 1378–1391.CrossRef
39.
Jiang, H., Jin, S., & Wang, C. (2011). Prediction or not? An energy-efficient framework for clustering-based data collection in wireless sensor network. IEEE Transactions on Parallel and Distributed Systems, 22(6), 1064–1071.CrossRef
40.
Zhu, J., & Xiaodong, H. (2008). Improved algorithm for minimum data aggregation time problem in wireless sensor networks. Journal of System Science & Complexity, 21(4), 626–636.MathSciNetCrossRefMATH
41.
Xiaohua, X., Li, X., & Mao, X. (2011). A delay-efficient algorithm for data aggregation in multihop wireless sensor networks. IEEE Transaction on Parallel and Distributed Systems, 22(1), 163–175.CrossRef
42.
Lei, L., Lin, C., Cai, J., & Shen, X. (2009). Rerformance analysis of wireless opportunistic schedulers using stochastic petri nets. IEEE Transactions on Wireless Communications, 8(4), 2076–2087.CrossRef
43.
Yanwei, W., Li, X., & Liu, Y. (2010). Energy-efficient wake-up scheduling for data collection and aggregation. IEEE Transactions on Parallel and Distributed Systems, 21(2), 275–287.CrossRef
44.
Jie, W., Fei, D., & Ming, G. (2002). On calculating power-aware connected dominating sets for efficient routing in ad hoc wireless network. Journal of Communications and Networks, 4(1), 1–12.
45.
Oliveira, T., Raju, M., & Agrawal, D. P. (2012). Accurate distance estimation using fuzzy based combined RSSI/LQI values in an indoor scenario: Experimental verification. Network Protocols and Algorithms, 4(4), 174–199.CrossRef
46.
Elbes, M., Jordan, A., Fuqaha, A. A., & Anan, M. (2013). A precise indoor localization approach based on particle filter and dynamic exclusion techniques. Network Protocols and Algorithms, 5(2), 50–71.CrossRef
47.
Lloret, J., Tomas, J., Garcia, M., & Canovas, A. (2009). Hybrid stochastic approach for self-location of wireless sensors in indoor environments. Sensors, 9(5), 3695–3712.CrossRef
48.
Sendra, S., Lloret, J., García, M., & Toledo, J. F. (2011). Power saving and energy optimization techniques for wireless sensor networks. Journal of Communications, 6(6), 439–459.CrossRef
49.
Wei, W., Qin, X., Wang, L., Hei, X., Shen, P., Shi, W., & Shan, L. (2014). GI/Geom/1 queue based on communication model for mesh networks. International Journal of Communication Systems, 27(11), 3013–3029.
50.
Jameii, S. M., Faez, K., & Dehghan, M. (2015). Multiobjective optimization for topology and coverage control in wireless sensor networks. International Journal of Distributed Sensor Networks, 1, 1–11.
51.
Wei, W., Yang, X., Zhou, B., Feng, J., & Shen, P. (2012). Combined energy minimization for image reconstruction from few views. Mathematical Problems in Engineering., 2012, 1–15.MathSciNetMATH
Metadaten
Titel
CASMOC: a novel complex alliance strategy with multi-objective optimization of coverage in wireless sensor networks
verfasst von
Zeyu Sun
Yongsheng Zhang
Yalin Nie
Wei Wei
Jaime Lloret
Houbing Song
Publikationsdatum
09.02.2016
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 4/2017
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-016-1213-3

Weitere Artikel der Ausgabe 4/2017

Wireless Networks 4/2017 Zur Ausgabe

OriginalPaper

Analytical framework for power saving evaluation in two-tier heterogeneous mobile networks

OriginalPaper

Symptotics: a framework for estimating the scalability of real-world wireless networks

OriginalPaper

Narrowband frequency-selective up-link and down-link evaluation of daily personal-exposure induced by wireless operating networks

OriginalPaper

EMGGR: an energy-efficient multipath grid-based geographic routing protocol for underwater wireless sensor networks

OriginalPaper

Effective capacity of receive antenna selection MIMO–OSTBC systems in co-channel interference

OriginalPaper

Energy efficient secured routing protocol for MANETs