Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

Cooja Based Approach for Estimation and Enhancement of Lifetime of 6LoWPAN Environment

Author(s): Ruchi Garg* and Sanjay Sharma

Volume 10, Issue 2, 2020

Page: [207 - 216] Pages: 10

DOI: 10.2174/2210327909666190409124604

Price: $65

Abstract

Background and Objective: The Scale with which Internet of Things (IoT) is penetrating our day to day life, time is not far away when it would be the Internet of Everything (IoE) that will require billions of devices to communicate with each other in the real world. To cater to the same, Wireless Sensor Network (WSN) is composed of 6LoWPAN sensor-nodes, which are mainly battery operated. One of the major issues, in such network, is nodes’ limited lifetime which is battery dependent.

Methods: In this paper, we have suggested and implemented an approach for ‘Estimation and Enhancement of Lifetime of Wireless Sensor Network’ (E&EL-WSN). The aim of our study is to suggest an approach that helps in power saving of the batteries of sensor-nodes and will result in enhanced life-time of 6LoWPAN environment. Our suggested approach is based on the concept of reduced packet size resulting in saving of power consumption. Packet size is reduced by our Modified and Improved Header Compression (MIHC) method of IPv6 header compression.

Results: The simulation, done in Cooja, shows, in our case, an improvement of approximately 19% saving of power consumption. This results in an enhancement of 70 days in the lifetime of the network, which is almost 23% better than the existing approach.

Keywords: 6LoWPAN, contiki, cooja, estimation of lifetime, IPv6, MIHC, power consumption, wireless sensor network.

Graphical Abstract

[1]
Niu HL, Liu S. Novel positioning service computing method for WSN. Wirel Pers Commun 2017; 92(4): 1747-69.
[http://dx.doi.org/10.1007/s11277-016-3632-y]
[2]
Zhang T, Zhang J. A kind of effective data aggregating method based on compressive sensing for wireless sensor network. EURASIP J Wirel Commun Netw 2018; 2018(159): 1-15.
[http://dx.doi.org/10.1186/s13638-018-1176-4]
[3]
Zhu Y. A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the Internet Of Things (IOT). Comput Math Appl 2012; 64(5): 1044-55.
[http://dx.doi.org/10.1016/j.camwa.2012.03.023]
[4]
Ma Z. A novel compressive sensing method based on SVD sparse random measurement matrix in wireless sensor network. Eng Comput 2016; 33(8): 2448-62.
[http://dx.doi.org/10.1108/EC-09-2015-0269]
[5]
Wang X, Song X. New medical image fusion approach with coding based on SCD in wireless sensor network. J Electr Eng Technol 2015; 10(6): 2384-92.
[http://dx.doi.org/10.5370/JEET.2015.10.6.2384]
[6]
Zhang D, Li W, Liu S, Zhang X. Novel fusion computing method for bio-medical image of WSN based on spherical coordinate. J Vibroeng 2016; 18(1): 522-38.
[7]
Zhang X. Design and implementation of embedded uninterruptible power supply system for web-based mobile application. Enterprise Inf Syst 2012; 6(4): 473-89.
[http://dx.doi.org/10.1080/17517575.2011.626872]
[8]
Chen J, Mao G. Capacity of cooperative vehicular networks with infrastructure support: Multi-user case. IEEE Trans Vehicular Technol 2018; 67(2): 1546-60.
[http://dx.doi.org/10.1109/TVT.2017.2753772]
[9]
Zhang D, Ge H. New multi-hop clustering algorithm for vehicular Ad Hoc networks. IEEE Trans Intell Transp Syst 2018; 2018: 7.
[http://dx.doi.org/10.1109/TITS.2018.2853165]
[10]
Zhao CP. A new medium access control protocol based on perceived data reliability and spatial correlation in wireless sensor network. Comput Electr Eng 2012; 38(3): 694-702.
[http://dx.doi.org/10.1016/j.compeleceng.2012.02.016]
[11]
Kang XJ. A novel image de-noising method based on spherical coordinates system. EURASIP J Adv Signal Process 2012; 2012(110): 1-10.
[http://dx.doi.org/10.1186/1687-6180-2012-110]
[12]
Olsson J. 6LowPAN demystified. Texas Instruments 2014; 1: 2-11.
[13]
Kim E, Kaspar D, Vasseur JP. Design and application spaces for IPv6 over low-power wireless personal area networks. IETF, RFC 2012; 2012: 6568.
[http://dx.doi.org/10.17487/rfc6568]
[14]
Ismail NHA, Hassan R, Ghazali KWM. A study on protocol stack in 6LoWPAN model. Appl Clin Inform 2012; 41(2): 220-9.
[15]
Hinden R, Deering S. Internet Protocol Version 6 (IPv6) Addressing Architecture. RFC 3513 Online Available at http://tools.ietf.org/html/rfc3513[accessed 7 July 2016].
[16]
Chauhan D, Sharma S. A survey on next generation internet protocol: IPv6. Int J Electron Elect Eng 2014; 2(2): 143-6.
[http://dx.doi.org/10.12720/ijeee.2.2.143-146]
[17]
Feller G. The internet of things: In a connected world of smart objects. Accenture & Bankinter Foundation of Innovation 2011; 24-9.
[18]
Own CM, Shin HY, Teng CY. The study and application of the IoT in Pet systems. Adv Internet Things 2013; 3: 1-8.
[http://dx.doi.org/10.4236/ait.2013.31001]
[19]
Ning H, Liu H. Cyber-physicl-social based security architecture for future internet of things. Adv Internet Things 2012; 2(1): 1-7.
[http://dx.doi.org/10.4236/ait.2012.21001]
[20]
Dietrich I, Dressler F. On the lifetime of wireless sensor networks. ACM Trans Sens Netw 2009; 2009: 1-38.
[http://dx.doi.org/10.1145/1464420.1464425]
[21]
Shelby Z. 6LoWPAN: The Wireless Embedded Internet. 1st ed. London: Wiley 2009.
[http://dx.doi.org/10.1002/9780470686218]
[22]
Kushalnagar N, Montenegro G, Schumacher C. IPv6 over Low- Power Wireless Personal Area Networks (6LoWPANs): Overview, assumptions, problem statement, and goals. RFC 4919, IETF network working group 2007.
[23]
Montenegro G, Kushalnagar N, Hui J, Culler D. Transmission of IPv6 Packets over IEEE 802.15.4 Networks. RFC 4944, IETF network working group 2007.
[24]
Garg R, Sharma S. A study on need of adaptation layer in 6LoWPAN protocol stack. IEEE Trans Microw Theory Tech 2017; 7(3): 49-57.
[http://dx.doi.org/10.5815/ijwmt.2017.03.05]]
[25]
Mora-Merchan J, Larios D, Barbancho J. Mtossim: A simulator that estimates battery lifetime in wireless sensor networks. Simul Model Pract Theory 2013; 31: 39-51.
[http://dx.doi.org/10.1016/j.simpat.2012.10.009]
[26]
[27]
NS-2/3. Available from: www.isi.edu/nsnam/ns/[accessed 24 February 2018].
[28]
OMNeT++. Available from: http://www.omnetpp.org/
[30]
Mikhaylov K, Tervonen J. Novel energy consumption model for simulating wireless sensor networks. 2012 IV International Congress on Ultra Modern Telecommunications and Control Systems St. Petersburg, Russia. 2012.
[http://dx.doi.org/10.1109/ICUMT.2012.6459657 ]
[31]
Song XD, Wang X. Extended AODV routing method based on Distributed Minimum Transmission (DMT) for WSN. Int J Electron Commun 2015; 69(1): 371-81.
[http://dx.doi.org/10.1016/j.aeue.2014.10.009]
[32]
Mahmoud MS, Mohamad AAH. A study of efficient power consumption wireless communication techniques/modules for Internet of Things (IoT) applications. Adv Internet Things 2016; 6: 19-29.
[http://dx.doi.org/10.4236/ait.2016.62002]
[33]
Zhang T. Novel optimized link state routing protocol based on quantum genetic strategy for mobile learning. J Netw Comput Appl 2018; 7: 8.
[http://dx.doi.org/10.1016/j.jnca.2018.07.018]
[34]
Ma Z. Shadow detection of moving objects based on multisource information in internet of things. J Exp Theor Artif Intell 2017; 29(3): 649-61.
[http://dx.doi.org/10.1080/0952813X.2016.1212105]
[35]
Song X, Wang X. New agent-based proactive migration method and system for Big Data Environment (BDE). Eng Comput 2015; 32(8): 2443-66.
[http://dx.doi.org/10.1108/EC-03-2015-0050]
[36]
Liang Y. A kind of novel method of service-aware computing for uncertain mobile applications. Math Comput Model 2013; 57(3-4): 344-56.
[http://dx.doi.org/10.1016/j.mcm.2012.06.012]
[37]
Dron W, Duquennoy S, Voigt T, Hachicha K, Garda P. An emulation-based method for lifetime estimation of wireless sensor networks. Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems Marina Del Ray, CA, USA. 2014.
[http://dx.doi.org/10.1109/DCOSS.2014.10 ]
[38]
Liu S, Zhang T. Novel unequal clustering routing protocol considering energy balancing based on network partition & distance for mobile education. J Netw Comput Appl 2017; 88(15): 1-9.
[http://dx.doi.org/10.1016/j.jnca.2017.03.025]
[39]
Zhang Y, Li Y, Zhang R. Energy saving model and simulation test based on 6lowpan wireless sensor network. Open Autom Control Syst J 2014; 6: 1349-58.
[http://dx.doi.org/10.2174/1874444301406011349]
[40]
Sitanayah L, Sreenan CJ, Fedor S. A cooja-based tool for coverage and lifetime evaluation in an in-building sensor network. J Sens Actuator Netw 2016; 5: 4.
[http://dx.doi.org/10.3390/jsan5010004]
[41]
Zhang D, Li G, Zheng K. An energy-balanced routing method based on forward-aware factor for wireless sensor network. IEEE Trans Industr Inform 2014; 10(1): 766-73.
[http://dx.doi.org/10.1109/TII.2013.2250910]
[42]
Zheng K, Zhang T. A novel multicast routing method with minimum transmission for WSN of cloud computing service. Soft Comput 2015; 19(7): 1817-27.
[http://dx.doi.org/10.1007/s00500-014-1366-x]
[43]
Wang X, Song X. New clustering routing method based on pece for WSN. EURASIP J Wirel Commun Netw 2015; 162: 1-13.
[http://dx.doi.org/10.1186/s13638-015-0399-x]
[44]
Zhang D, Chen C, Cui Y, Zhang T. New method of energy efficient subcarrier allocation based on evolutionary game theory. Mob Netw Appl 2018; 2018: 9.
[http://dx.doi.org/10.1007/s11036-018-1123-y]
[45]
Twayej W, Al-Raweshidy HS. M2M energy efficiency routing protocol MLCMS by using 6LoWPAN based on IoE. 2016 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom) Varna, Bulgaria. 2016.
[http://dx.doi.org/10.1109/BlackSeaCom.2016.7901581]
[46]
Ludovici A, Calveras A, Catalan M, Go’mez C, Paradells J. Implementation and evaluation of the enhanced header compression (IPHC) for 6LoWPAN EUNICE 2009, LNCS 5733. Berlin: Springer 2009; pp. 168-77.
[47]
Huiqin W, Yongqiang D. An improved header compression scheme for LoWPAN networks. 9th International Conference on Grid and Cloud Computing Nanjing, China. 2010.
[http://dx.doi.org/10.1109/GCC.2010.74]
[48]
Chauhan D, Sharma S. Network optimization of IPv6 networks using tunnel header compression. Int J Res Eng Technol 2015; 4(3): 113-6.
[http://dx.doi.org/10.15623/ijret.2015.0403019]
[49]
Chauhan D, Sharma S. Enhancing the efficiency of IPv6 tunnelling mechanism by using header compression over IPv6 header. Int J Adv Res Comput Commun Eng 2015; 4(4): 446.
[http://dx.doi.org/10.17148/ijarcce.2015.44102]
[50]
Awwad SAB, Chee NK, Noordin K, Ali BM, Hashim F. Second and subsequent fragments headers compression scheme for IPv6 Header in 6LoWPAN Network. 2013 Seventh International Conference on Sensing Technology (ICST) Wellington, New Zealand 2013.
[http://dx.doi.org/10.1109/ICSensT.2013.6727757]
[51]
Awwad SAB, Ng CK, Noordin K, Ali BM, Hashim F. The integrated versus standalone operation mode for second and subsequent fragments headers compression scheme in 6LoWPAN. Sensing technology: Current status and future trends III. Smart sensors, measurement and instrumentation. 179-99.
[http://dx.doi.org/10.1007/978-3-319-10948-0_9]
[52]
Hui J, Thumbert P. Compression format for IPv6 datagrams over IEEE 802154 based networks RFC 6282, IETF network working group, 2011.
[53]
Garg R, Sharma S. Comparative study on techniques of IPv6 header compression in 6LoWPAN Fourth International Conference on Advances in Information Processing and Communication Technology - IPCT 2016 Rome, Italy.
[http://dx.doi.org/10.15224/978-1-63248-099-6-33]
[54]
Garg R, Sharma S. Modified and improved ipv6 header compression (mihc) scheme for 6lowpan. Wirel Pers Commun 2018; 103: 2019.
[http://dx.doi.org/10.1007/s11277-018-5894-z]
[55]
Dunkels A, Gronvall B, Voigt T. Contiki-A lightweight and flexible operating system for tiny networked sensors. Workshop on Embedded Networked Sensors Tampa, Florida, USA. 2004.
[http://dx.doi.org/10.1109/LCN. 2004.38]
[56]
Contiki. Available from: http://contiki-os.org/
[57]
Gonizzi P, Duquennoy S. Hands on Contiki OS and Cooja Simulator. Internet Things Smart Cities 2013; 2013: 1-15.
[58]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy