International Journal of Wireless and Microwave Technologies (IJWMT)
IJWMT Vol. 7, No. 5, 8 Sep. 2017
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Improvement of ZigBee Using by Thread and Backpressure Algorithm
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Author(s)
Index Terms
ZigBee network, tree routing, reducing the delay, energy balance, performance evaluation
Abstract
In wireless sensor networks, two approaches of tree and mesh routing are introduced to determine the path of packets during the transition process. Tree routing is a simple routing protocol with low overhead that in this protocol father-child bonds for packet transmission from the source to the destination is used. The biggest problem of routing is the increase of the number of mutations in comparison with other routing protocols. In order to improve this problem, protocols have been introduced in recent years to determine a shortcut path on the basis of the tree routing. This study is an attempt to analyse and evaluate the existing routing algorithms, identify and overcome their disadvantages, also in some other protocols, only reducing the number of mutations has been discussed. However, to achieve this goal leads to increased energy consumption and thus reducing the lifetime of the network; reducing the number of mutations is an important parameter and can reduce delays in the network, however, it should be noted the energy consumption in ZigBee networks is a very important debate. Besides that, this study will try—in addition to reducing the average number of mutations—to reduce the traffic load near the root node in the proposed algorithms. As a result, on the one hand, the application of this algorithm in ZigBee networks reduces delays and on the other hand, will also lead to balancing of load and energy in the network. Using this algorithm, the scope and lifetime of the proposed protocol-based networks can be increased.
Cite This Paper
Negar Jadidkar, Hossein Samimi," Improvement of ZigBee Using by Thread and Backpressure Algorithm", International Journal of Wireless and Microwave Technologies(IJWMT), Vol.7, No.5, pp.1-13, 2017. DOI: 10.5815/ijwmt.2017.05.01
Reference
[1]Akbar MAJIDI, Hamid MIRVAZIRI. BDCC: Backpressure routing and dynamic prioritization for congestion control in WMSNs. I.J. Computer Network and Information Security; 2014, 5, 29-34.
[2]Akbar MAJIDI, Hamid MIRVAZIRI. BDCC: Backpressure routing and dynamic prioritization for congestion control in WMSNs. I.J. Computer Network and Information Security; 2014, 5, 29-34.
[3]Ali C. Samuel P. 2014. A distributed energy-efficient clustering protocol for wireless sensor networks. Computers & Electrical Engineering:Elsevier. 36: 303–312.
[4]D. Gislason, Zigbee Wireless Network, Newnes Publication Co., 2008.
[5]Banerjee T. Xie B. Jung HJ. Agrawal BD. 2010. Increasing lifetime of wireless sensor networks using controllable mobile cluster heads. 10: 313-336
[6]Basagni S. Carosi A. Melachrinoudis E. Petrioli C. Wang ZM. 2013. Controlled sink mobility for prolonging wireless sensor networks lifetime. Wireless Networks Jurnal:ACM. 17: 759-778.
[7]Boonsongsrikul A. Kocijancic S. Suppharangsan S. 2013. Effective energy consumption on wireless sensor networks: Survey and challenges .Information & Communication Technology Electronics & Microelectronics (MIPRO). 469-473.
[8]Chirag KR. Trilok CA. 2011. An improved transport layer protocol for wireless sensor networks. Computer Communications: Elsevier. 34: 758-764.
[9]Feng W. Jiangchuan L. 2011. Networked wireless sensor data collection: issues, challenges, and approaches. Communications Surveys & Tutorials, IEEE. 13:673 - 687.
[10]Flora J. Kavitha DF. Muthuselvi V. 2011. A survey on congestion control techniques in Wireless Sensor Networks. Emerging Trends in Electrical and Computer Technology (ICETECT), International Conference on, 1146 - 1149.
[11]Network Simulator version 2.27 (ns-2.27): Available online, http://www.isi.edu/nsnam/ns/, March 2010
[12]J. Jheng, M.J.Lee ,”A comprehensive performance study of IEEE 802.15.4”, Sensor network operations (IEEE Press,Wiley Interscience, 2006), Ch.4, pp. 218-237
[13]http://ees2cy.engr.ccny.cuny.edu/zheng/pub/, last access April 2008
[14]Hussaini M. Bello-Salau AF. Salami F. Anwar AH. Abdalla Md. Rafiqul I. 2012. Enhanced clustering routing protocol for power-efficient gathering in wireless sensor network. International Journal of Communication Network and Information Security(IJCNIS). 4: 18-28.
[15]Jenolin FD. Kavitha V. Muthuselvi M. 2011. A survey on congestion control techniques in Wireless Sensor Networks. Emerging Trends in Electrical and Computer Technology (ICETECT), 2011 International Conference on. 1146-1149.
[16]Jing Z. Lei W. Suran L. Xiaokang L. Zhuxiu Y. Zhengjiu G. 2010. A survey of congestion control mechanisms in wireless sensor networks. Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2010 Sixth International Conference on. 719-722.
[17]Karthik C. Sukumar R.Nageswari M. 2013. Sensors lifetime enhancement techniques in wireless sensor networks - A critical review. IRACST - International Journal of Computer Science and Information Technology & Security.
[18]Kumari J. Prachi . 2015. A comprehensive survey of routing protocols in wireless sensor networks. Computing for Sustainable Global Development (INDIACom). 325-330.
[19]S.K. Singh, MP Singh, and DK Singh. Routing protocols in wireless sensor networks_a survey. International Journal of Computer science and engineering Survey (IJCSES), 1(2):63_83, 2010.
[20]S.C.Ergen, “Zigbee/IEEE 8.201504 Summary”, Technical Report, September 2004.
[21]LIN QM. WANG RC. GUO J. SUN LJ. 2011.Novel congestion control approach in wireless multimedia sensor networks. The Journal of China Universities of Posts and Telecommunications:Elsevier. 18: 1-8.
[22]Lotf JJ. Nazhad, SHH. Alguliev RM. 2011. A survey of wireless sensor networks. Application of Information and Communication Technologies (AICT). 1-6.
[23]S.Ahn, D.Ko, B.Kim, S.Lee, 2013. “Energy-efficient Tree Routing Algorithm-based Destination Family Group in Zigbee Networks”. Fourth International Conference on Sensor Technologies and Applications.
[24]Tashtarian F. Moghaddam MY. Effati S. 2012. Energy efficient data gathering algorithm in hierarchical wireless sensor networks with mobile sink. Computer and Knowledge Engineering (ICCKE). 232-237.
[25]Wei WF. Ji MC. Lei Sh. Tian Ch. De PQ. 2010. Congestion avoidance, detection and alleviation in wireless sensor networks. Journal of Zhejiang University SCIENCE. 11: 63-73.