Login Register Cart 0
Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

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

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Comparative Cluster Based Mobile Routing Approach for Energy Efficiency in Optimization of Node location in WSNs

Author(s): Sanjay Kumar Sahani* and Raghav Yadav

Volume 9, Issue 2, 2019

Page: [179 - 187] Pages: 9

DOI: 10.2174/2210327908666181102122500

Price: $65

conference banner
Abstract

Background & Objective: The Energy efficiency in optimization of node sensor location is considered as a design on Comparatively Cluster Based Mobile Routing Approach (CCBMRA) likewise circle coverage and elliptical coverage. Location of boundary has deployment with CCBMRA distribution of anchor node and un-anchor node or static sensor node.

Methods: This proposed method has applied for distributed by anchor node positioned to measurements of employing received signal strength. So it is important for intermediate processing phase to achieved accurate positioning of SSN (Static Sensor Node). Moreover, ASN (Anchor Sensor Node) transmitted signal accurate computational and energy efficiency in optimization through reduces the number of cost factor, time and utilization of anchor node location. The research has established algorithm and simulation experimental based mobile node localisation routing approached.

Result and Conclusion: The experimental has achieved higher localisation precision in less nodes. This paper suggests algorithm based on CCBMRA.

Keywords: Anchor sensor node, Optimization, positioning, received signal strength, wireless sensor network, sensor node.

« Previous Next »
Graphical Abstract

[1]
Alimpertis E, Fasarakis-Hilliard N, Bletsas A. Community RF sensing for source localization. IEEE Wirel Commun Lett 2014; 3(4): 393-6.
[2]
Santi P. Topology control in wireless ad hoc and sensor networks. ACM Comput Surv 2005; 37(2): 164-94.
[3]
Mahboubi H, Moezzi K, Aghdam AG, Sayrafian-Pour K, Marbukh V. Distributed deployment algorithms for improved coverage in a network of wireless mobile sensors. IEEE T Ind Inform 2014; 10(1): 163-74.
[4]
Rawat P, Singh KD, Chaouchi H, Bonnin JM. Wireless sensor networks: A survey on recent developments and potential synergies. J Supercomput 2014; 68(1): 1-48.
[5]
Sara GS, Sridharan D. Routing in mobile wireless sensor network: A survey. Telecomm Syst 2014; 57(1): 51-79.
[6]
Zhu C, Shu L, Hara T, Wang L, Nishio S, Yang LT. A survey on communication and data management issues in mobile sensor networks. Wirel Commun Mob Comput 2014; 14(1): 19-36.
[7]
Wu X, Chen G, Das SK. Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE T Parall Distr 2008; 19(5): 710-20.
[8]
Mohajerzadeh AH, Yaghmaee MH. An efficient energy aware routing protocol for real time traffic in wireless sensor networks. In: 2009 International conference on ultra-modern telecommunications & workshops, IEEE . 2009; 12 : pp. 1-9.
[9]
Sabbineni H, Chakrabarty K. Location-aided flooding: an energy-efficient data dissemination protocol for wireless-sensor networks. IEEE Trans Comput 2005; 54(1): 36-46.
[10]
Heinzelman WB, Chandrakasan AP, Balakrishnan H. An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 2002; 1(4): 660-70.
[11]
Wang G, Chen H, Li Y, Jin M. On received-signal-strength based localization with unknown transmit power and path loss exponent. IEEE Wirel Commun Lett 2012; 1(5): 536-9.
[12]
Fafoutis X, Di Mauro A, Vithanage MD, Dragoni N. Receiver-initiated medium access control protocols for wireless sensor networks. Comput Netw 2015; 76: 55-74.
[13]
Lai S, Ravindran B. Least-latency routing over time-dependent wireless sensor networks. IEEE Trans Comput 2013; 62(5): 969-83.
[14]
Gu Y, He T. Dynamic switching-based data forwarding for low-duty-cycle wireless sensor networks. IEEE Trans Mobile Comput 2011; 10(12): 1741-54.
[15]
Fan Z. Delay-driven routing for low-duty-cycle sensor networks. Int J Distrib Sens Netw 2013; 9(9)198283
[16]
Li J, Kim SM, He T. Circular pipelining: Minimizing round-trip delay in low-duty-cycle wireless networks. In: 2014 IEEE 22nd International Conference on Network Protocols Raleigh, NC, USA: IEEE . 2014; pp. 421-32.
[17]
Guo S, He L, Gu Y, Jiang B, He T. Opportunistic flooding in low-duty-cycle wireless sensor networks with unreliable links. IEEE Trans Comput 2014; 63(11): 2787-802.
[18]
He S, Chen J, Sun Y. Coverage and connectivity in duty-cycled wireless sensor networks for event monitoring. IEEE T Parall Distr 2012; 23(3): 475-82.
[19]
Fan Z. Minimum delay query in low-duty-cycle sensor networks. Int J Future Gener Commun Netw 2016; 9(6): 351-62.
[20]
Li F, Guo W. An efficient polynomial time algorithm for robust multicast network code construction. IEEE Commun Lett 2015; 19(2): 143-6.
[21]
Di Mauro A, Fafoutis X, Dragoni N. Adaptive security in odmac for multihop energy harvesting wireless sensor networks. Int J Distrib Sens Netw 2015; 11(4)760302

Rights & Permissions Print Cite
Article Metrics
32
1
© 2024 Bentham Science Publishers | Privacy Policy