Skip to main content
Log in

Using ambient intelligence to extend network lifetime in wireless sensor networks

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

A wireless sensor network (WSN) consists of sensor nodes and wireless communication. Sensor nodes usually have the features such as tiny size, low cost, low power consumption. They are used for environmental monitoring and transmit sensing data (temperature, humidity, pressure and so on) to sink through wireless networking. To protect sensing data’s confidentiality and integrity has presented an intrusion detection system called patrol intrusion detection system (PIDS), which designate a fraction of sensor nodes as roaming patrol nodes to detect malicious sensor nodes. However, those patrol nodes’ battery energy will consume rapidly and thus makes the whole WSN to have reduced lifetime. In this paper, the system will collect ambient data and utilize a revised artificial bee colony algorithm to find a low power consumption path for transmitting attack feature packets in PIDS in order to extend the lifetime of a WSN.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Asogwa C-O, Zhang X, Xiao D, Hamed A (2012) Experimental analysis of AODV, DSR and DSDV protocols based on wireless body area network. Commun Comput Inf Sci 312:183–191

    Article  Google Scholar 

  • Atmojo UD, Salcic Z, Wang KI-K, Park HJ (2015) System-level approach to the design of ambient intelligence systems based on wireless sensor and actuator networks 6(2):153–169

  • Bajaber F, Awan I (2010) Energy efficient clustering protocol to enhance lifetime of wireless sensor network. J Ambient Intell Humaniz Comput 1(4):239–248

    Article  Google Scholar 

  • Chen RC, Hsieh CF, Huang YF (2010) An isolation intrusion detection system for hierarchical wireless sensor networks. J Netw 5(3):335–342

    Google Scholar 

  • Ding W, Ma Y (2012) The application of wireless sensor in aquaculture water quality monitoring. IFIP Adv Inf Commun Technol 370:502–507

    Article  Google Scholar 

  • Doherty L, Simon J, Watteyne T (2012) Wireless sensor network challenges and solutions. Microw J 55(8):22–34

    Google Scholar 

  • Dorigo M, Birattari M, Stutzle T (2006) Ant colony optimization. IEEE Comput Intell Mag 1(4):28–39

    Article  Google Scholar 

  • Guo W, Zhang W, Lu G (2010) A comprehensive routing protocol in wireless sensor network based on ant colony algorithm. Netw Secur Wirel Commun Trust Comput 1:41–44

    Google Scholar 

  • Haberman BK, Sheppard JW (2012) Overlapping particle swarms for energy-efficient routing in sensor networks. Wirel Netw 18(4):351–363

    Article  Google Scholar 

  • He S, Dai Y, Zhou R, Zhao S (2012) A clustering routing protocol for energy balance of WSN based on genetic clustering algorithm. IERI Procedia 2:788–793

    Article  Google Scholar 

  • Heinzelman W, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. Wirel Commun 1(4):660–670

    Article  Google Scholar 

  • Hornga S-J, Suc M-Y, Chenb Y-H et al (2011) A novel intrusion detection system based on hierarchical clustering and support vector machines. Expert Syst Appl 38(1):306–313

    Article  Google Scholar 

  • Hsieh CF, Huang YF, Chen RC (2011) A light-weight ranger intrusion detection system on wireless sensor networks. In: IEEE the fifth international conference on genetic and evolutionary computing, pp 49–52

  • Johnson D, Hu Y, Maltz D (2007) The dynamic source routing protocol (DSR) for mobile ad hoc networks for Ipv4. RFC 4728. http://tools.ietf.org/html/rfc4728. Accessed 26 Dec 2012

  • Karaboga D, Basturk B (2008) On the performance of artificial bee colony algorithm. Appl Soft Comput 8(1):687–697

    Article  Google Scholar 

  • Karaboga D, Gorkemli B, Ozturk C, Karaboga N (2014) A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artif Intell Rev 42(1):21–57

    Article  Google Scholar 

  • Kennedy J, Eberhart R (1995) Particle swarm optimization. IEEE Int Conf Neural Netw 4:1942–1948

    Google Scholar 

  • Kiani SL, Anjum A, Antonopoulos N, Knappmeyer M (2014) Context-aware service utilisation in the clouds and energy conservation. J Ambient Intell Humaniz Comput 5(1):111–131

    Article  Google Scholar 

  • Kim T-H, Fang W-C, Ramos C et al (2012) Ubiquitous sensor networks and its application. Int J Distrib Sens Netw 2012:1–3

    Google Scholar 

  • Liu CY, Woungang I, Chao HC et al (2011) Message security in multi-path Ad Hoc networks using a neural network-based cipher. IEEE Globecom 2011:1–5

    Google Scholar 

  • Liu Y, Dai W, Xu K, Zheng (2012) A hybrid routing tree to avoid the energy hole problem in wireless sensor network. Adv Intell Soft Comput 143:869–876

    Google Scholar 

  • Nguyen TA, Raspitzu A, Marco Aiello (2014) Ontology-based office activity recognition with applications for energy savings. J Ambient Intell Humaniz Comput 5(5):667–681

    Article  Google Scholar 

  • Perkins C, Beldingroyer E, Das S (2003) Ad hoc on-demand distance vector (AODV) routing. RFC 3561. http://www.faqs.org/rfcs/rfc3561.html. Accessed 26 Dec 2012

  • Saxena A, Prakash V (2012) Simulation study of AODV and DSR routing protocol in wireless Ad-Hoc networks. Int J Eng Sci Res 2:741–748

    Google Scholar 

  • Sunita M, Malik J, Mor S (2012) Comprehensive study of applications of wireless sensor network. Int J Adv Res Comput Sci Softw Eng 2(11):56–60

    Google Scholar 

  • Toosi AN, Kahani M (2007) A new approach to intrusion detection based on an evolutionary soft computing model using neuro-fuzzy classifiers. Comput Commun 30(10):2201–2212

    Article  Google Scholar 

  • Zungeru AM, Ang LM, Seng KP (2012) Classical and swarm intelligence based routing protocols for wireless sensor networks: a survey and comparison. J Netw Comput Appl 35(5):1508–1536

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the Ministry of Science and Technology, Taiwan, ROC, under contract number MOST103-2632-E-324-001-MY3.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rung-Ching Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, RC., Hsieh, CF. & Chang, WL. Using ambient intelligence to extend network lifetime in wireless sensor networks. J Ambient Intell Human Comput 7, 777–788 (2016). https://doi.org/10.1007/s12652-015-0323-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-015-0323-6

Keywords

Navigation