Survey on Data Gathering Approaches in Wireless Sensor Networks

Sujithra, T.; Kumar, N. K. Senthil; Kumar, K. Kishore; Vinayagam, V. M.

doi:10.17485/ijst/2017/v10i25/103208

Cited by 3 publications

(4 citation statements)

References 27 publications

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“…fading channels case. 7 Note that satisfying τ ∈ (E {y N /Z|H 0 } , E {y N /Z|H 1 }) does not require high accuracy when the FC estimates the expectations E {y N /Z|H 0 } , E {y N /Z|H 1 }. We point out that such (and even more complex) learning mechanisms are required in other schemes as well, such as computing a complex rate function that depends on the channel distribution of each sensor node for TBMA [5].…”

Section: The Case Of Fading Channelsmentioning

confidence: 99%

“…When the channel gains are not i.i.d. across sensors we assume that Z satisfies the desired property 7 .…”

Section: The Case Of Fading Channelsmentioning

confidence: 99%

“…Note that letting the sensors transmit a few pilot signals which are coherently aggregated at the FC yields a good estimate of µ h,n under the i.i.d. fading channels case 7. Note that satisfying τ ∈ (E {y N /Z|H 0 } , E {y N /Z|H 1 }) does not require high accuracy when the FC estimates the expectations E {y N /Z|H 0 } , E {y N /Z|H 1 }.…”

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confidence: 99%

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Spectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks

Cohen

Leshem

2018

IEEE Trans. Signal Process.

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We consider a binary hypothesis testing problem using Wireless Sensor Networks (WSNs). The decision is made by a fusion center and is based on received data from the sensors. We focus on a spectrum and energy efficient transmission scheme used to reduce the spectrum usage and energy consumption during the detection task. We propose a Spectrum and Energy Efficient Multiple Access (SEEMA) transmission protocol that performs a censoring-type transmission based on the density of observations using multiple access channels (MAC). Specifically, in SEEMA, only sensors with highly informative observations transmit their data in each data collection. The sensors transmit a common shaping waveform and the fusion center receives a superposition of the analog transmitted signals. SEEMA has important advantages for detection tasks in WSNs. First, it is highly energy and bandwidth efficient due to transmission savings and narrowband transmission over MAC. Second, it can be implemented by simple dumb sensors (oblivious to observation statistics, and local data processing is not required) which simplifies the implementation as compared to existing MAC transmission schemes for detection in WSNs. We establish a finite sample analysis and an asymptotic analysis of the error probability with respect to the network size and provide system design conditions to obtain the exponential decay of the error. Specific performance analysis is developed for common noni.i.d. observation scenarios, including local i.i.d. observations, and Markovian correlated observations. Numerical examples demonstrate SEEMA performance.

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Section: The Case Of Fading Channelsmentioning

confidence: 99%

“…When the channel gains are not i.i.d. across sensors we assume that Z satisfies the desired property 7 .…”

Section: The Case Of Fading Channelsmentioning

confidence: 99%

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Spectrum and Energy Efficient Multiple Access for Detection in Wireless Sensor Networks

Cohen

Leshem

2018

IEEE Trans. Signal Process.

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“…according field in table node A and node B obtain of distance to each other nodes. These fields information is send to sink node and all other nodes for updating information [1][2]. The sink node fields in table as shown in below table 1.1 To obtain characteristics of the sensor node D with distance from nodes such as Node A, Node B and base station are certain amount of a, b, c.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficient Hierarchical Stable Election Protocol

Naik¹,

Ramanaiah²,

Rajan³

2019

IJCA

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In the energy efficient routing protocols clustering is done as uniformly and select as cluster head (CH) based on remaining energy and distance of the nodes. This protocol is modification of SEP protocol. The election of Cluster Head (CH) in EEHSEP protocol is based on remaining energy and best node with respect to distance between other nodes and sink node. The energy consumption of sensor nodes is based on the distance traveled by packet, if node transmits loner distance it consume more energy than shorter distance. In this protocol obtains distance between nodes is using distance equation formula. It is calculate distance between node and obtained average distance from the cluster head, based on best average distance of nodes select cluster head.

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