Prevention of node replication in Wireless Sensor Network using Received Signal Strength Indicator, Link Quality Indicator and Packet Sequence Number

2016 ◽  
Author(s):  
Sudipto Roy ◽  
Manisha J Nene
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Quality Indicator ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Link Quality ◽  
Wireless Sensor ◽  
Received Signal Strength Indicator ◽  
Sequence Number ◽  
Link Quality Indicator

A Localization Algorithm for Wireless Sensor Network Based on the Weighted Correction in Geometric Measurement

2015 ◽  
Vol 740 ◽  
pp. 823-829
Author(s):  
Meng Long Cao ◽  
Chong Xin Yang
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Received Signal Strength Indicator ◽  
Localization Algorithms ◽  
Weighted Centroid Localization ◽  
Geometric Measurement

Firstly, the characteristics of regular Zigbee localization algorithms-the received signal strength indicator algorithm (RSSI) and the weighted centroid localization algorithm are introduced. Then, the factors of the errors existing in the aforementioned algorithms are analyzed. Based on these above, the improved RSSI algorithm-correction geometric measurement based on weighted is proposed. Finally, utilizing this algorithm to design and implement the localization nodes, which have the CC2431 wireless microcontroller on them. The simulation and experimental results show that the accuracy of this localization algorithm improved about 2%, comparing with the regular algorithms.

scholarly journals Research on Wireless Sensor Network Security Location Based on Received Signal Strength Indicator Sybil Attack

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hongbin Wang ◽  
Liping Feng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Transmission Function ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Time Inconsistency ◽  
Wireless Sensor ◽  
Sybil Attack ◽  
Received Signal Strength Indicator ◽  
Sensor Network Security

This paper studies the security location mechanism of the sensor network node under the attack of Sybil and analyzes the safe attacks which are possibly accepted and safe requirement in the location system. Since RSSI (Received Signal Strength Indicator) possesses the energy transmission function, different transmission energy will cause it to produce different RSSI readings. Furthermore, this kind of method cannot increase the burden on Wireless Sensor Network (WSN). It conducts an analysis between two receiving nodes, compares RSSI ratios to tickle the problem of time inconsistency of RSSI, and sets a threshold to detect Sybil by the emulation results. Research shows that the ratio value of different receiving nodes by using RSSI can resolve time difference because of the RSSI or unreliability which results from the asymmetry of transmission ratio. The thesis makes a comparison that the number of receiving nodes has an influence on attack effect. Utilizing the RSSI ratio values can exactly detect the Sybil attack. Emulation findings demonstrate that the detection method put forward by the thesis owns better security.

scholarly journals Studi Jarak Jangkauan X-Bee Pro S3b 900 untuk Aplikasi Node Wireless Sensor Network pada Daerah Gunung Api Berbasis Received Signal Strength Indicator (RSSI)

2019 ◽  
Vol 5 (2) ◽  
pp. 93-102
Author(s):  
Rakhmad Gusta Putra ◽  
Dirvi Eko Juliando Sudirman ◽  
Hanifah Nur Kumala Ningrum ◽  
Nur Asyik Hidayatullah
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Ieee 802.15.4 ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Received Signal Strength Indicator ◽  
Monitoring Area

Indonesia saat ini memiliki 129 gunung berapi yang aktif dan hanya 69 diantaranya yang baru bisa termonitoring dengan baik. Bencana gunung api dapat dihindari dengan melakukan monitoring yang baik terhadap kondisi gunung api secara menyeluruh sebagai mekanisme peringatan dini bencana. Monitoring area gunung api yang cukup luas menjadi kendala tersendiri dikarenakan titik pemantauan yang banyak. Wireless Sensor Network (WSN) merupakan salah satu sistem yang sesuai untuk melakukan pemantauan dengan jumlah titik sensor yang terdistribusi, fleksibel dan terintegrasi. Secara garis besar, sistem WSN terdiri dari receiver dan node sebagai transmiter. Komunikasi dari node menuju receiver dapat dilakukan langsung ataupun melalui node yang lainnya. Standar komunikasi nirkabel dari WSN untuk desain dan aplikasi mengacu pada IEEE 802.15.4. Perangkat yang mendukung standar ini salah satunya adalah X-Bee. X-Bee memiliki keunggulan dalam hal kemudahan penggunaan, relatif murah dan berdaya rendah. Salah satu hal yang menjadi poin penting dalam aplikasi WSN pada gunung api adalah jarak jangkauan. Dalam penelitian ini akan dilakukan studi jarak jangkauan Xbee Pro S3 900 pada area gunung api Kelud menggunakan RSSI. Dalam penelitian ini digunakan tiga buah node dan satu receiver sebagai perangkat pengambilan data. Tiga node transmitter tersebut di tempatkan pada tempat yang sesuai untuk mengamati kondisi gunung api Kelud. Jarak jangkauan XBee Pro S3B 900 LoS dengan konfigurasi yang dilakukan, didapatkan jarak jangkauan 79,2 m, sedangkan pada eksperimen mencapai 3,78 km pada nilai RSSI -60dBm. Jarak jangkauan rata-rata tiga node kondisi non LoS berdasarkan nilai RSSI -80 dBm adalah 50 m sedangkan dalam eksperimen didapatkan 441 m. Nilai RSSI hasil eksperimen didapatkan hasil lebih baik daripada hasil simulasi.

scholarly journals A Research Cluster based Scheme for Node Positioning in Indoor Environment

2019 ◽  
Vol 8 (6S) ◽  
pp. 79-83
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Cluster Head ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Localization Error ◽  
Network Efficiency

Location estimation in Wireless Sensor Network (WSN) is mandatory to achieve high network efficiency. Identifying the positions of sensors is an uphill task as monitoring nodes are involved in estimation and localization. Clustered Positioning for Indoor Environment (CPIE) is proposed for estimating the position of the sensors using a Cluster Head (CH) based mechanism. The CH estimates the number of neighbor nodes in each floor of the indoor environment. It sends the requests to the cluster members and the positions are estimated based on the Received Signal Strength Indicators (RSSIs) from the members of the cluster. The performance of the proposed scheme is analyzed for both stable and mobile conditions by varying the number of floors. Experimental results show that the propounded scheme offers better network efficiency and reduces delay and localization error

scholarly journals An RSSI-based Wireless Sensor Network Localization Algorithm with Error Checking and Correction

2017 ◽  
Vol 13 (12) ◽  
pp. 52 ◽  
Author(s):  
Bo Guan ◽  
Xin Li
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Sensor Network Localization ◽  
Anchor Node ◽  
Network Localization ◽  
Error Checking

<p style="margin: 1em 0px;"><span style="font-family: Times New Roman; font-size: medium;">This paper studies the wireless sensor network localization algorithm based on the received signal strength indicator (RSSI) in detail. Considering the large errors in ranging and localization of nodes made by the algorithm, this paper corrects and compensates the errors of the algorithm to improve the coordinate accuracy of the node. The improved node localization algorithm performs error checking and correction on the anchor node and the node to be measured, respectively so as to make the received signal strength value of the node to be measured closer to the real value. It corrects the weighting factor by using the measured distance between communication nodes to make the coordinate of the node to be measured more accurate. Then, it calculates the mean deviation of localization based on the anchor node close to the node to be measured and compensates the coordinate error. Through the simulation experiment, it is found that the new localization algorithm with error checking and correction proposed in this paper improves the localization accuracy by 5%-6% compared with the weighted centroid algorithm based on RSSI.</span></p>

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