Abstract
Depending upon sensing attributes, wireless sensor networks (WSNs) are classified as event driven, time driven, and query driven. In a given surveillance area, approximation of query generation process using uniform probability mass function (PMF) model seems to be reasonable in aggregate terms based on observations extracted from lifetime span of WSNs. However, owing to random generation aspects of query and the associated temporal variations, the Poisson distribution-based model appears to be more appropriate to resemble the realistic query generation pattern. Invariably, in all the sensor network architectures, the energy management requires an important consideration owing to limited energy resources. For the optimal utilization of energy resources, we propose fuzzy c-means (FCM) algorithm to form clusters in a hierarchical network configuration. Network performance is measured in terms of key performance measures, namely, average residual energy status, critical residual energy status (CRES), and number of network nodes that attain the CRES mark. These performance measures are estimated and analyzed for three different PMF models of query generation namely Uniform, Gaussian and Poisson. The merit of deploying FCM algorithm in terms of maintaining much better energy profile of the entire network is discussed.
| Original language | English |
|---|---|
| Pages (from-to) | 1439-1450 |
| Number of pages | 12 |
| Journal | International Journal of Communication Systems |
| Volume | 29 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 25-05-2016 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Electrical and Electronic Engineering
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Probabilistic query generation and fuzzy c -means clustering for energy-efficient operation in wireless sensor networks. / Kumar, Pramod; Chaturvedi, Ashvini.
In: International Journal of Communication Systems, Vol. 29, No. 8, 25.05.2016, p. 1439-1450.Research output: Contribution to journal › Article
TY - JOUR
T1 - Probabilistic query generation and fuzzy c -means clustering for energy-efficient operation in wireless sensor networks
AU - Kumar, Pramod
AU - Chaturvedi, Ashvini
PY - 2016/5/25
Y1 - 2016/5/25
N2 - Depending upon sensing attributes, wireless sensor networks (WSNs) are classified as event driven, time driven, and query driven. In a given surveillance area, approximation of query generation process using uniform probability mass function (PMF) model seems to be reasonable in aggregate terms based on observations extracted from lifetime span of WSNs. However, owing to random generation aspects of query and the associated temporal variations, the Poisson distribution-based model appears to be more appropriate to resemble the realistic query generation pattern. Invariably, in all the sensor network architectures, the energy management requires an important consideration owing to limited energy resources. For the optimal utilization of energy resources, we propose fuzzy c-means (FCM) algorithm to form clusters in a hierarchical network configuration. Network performance is measured in terms of key performance measures, namely, average residual energy status, critical residual energy status (CRES), and number of network nodes that attain the CRES mark. These performance measures are estimated and analyzed for three different PMF models of query generation namely Uniform, Gaussian and Poisson. The merit of deploying FCM algorithm in terms of maintaining much better energy profile of the entire network is discussed.
AB - Depending upon sensing attributes, wireless sensor networks (WSNs) are classified as event driven, time driven, and query driven. In a given surveillance area, approximation of query generation process using uniform probability mass function (PMF) model seems to be reasonable in aggregate terms based on observations extracted from lifetime span of WSNs. However, owing to random generation aspects of query and the associated temporal variations, the Poisson distribution-based model appears to be more appropriate to resemble the realistic query generation pattern. Invariably, in all the sensor network architectures, the energy management requires an important consideration owing to limited energy resources. For the optimal utilization of energy resources, we propose fuzzy c-means (FCM) algorithm to form clusters in a hierarchical network configuration. Network performance is measured in terms of key performance measures, namely, average residual energy status, critical residual energy status (CRES), and number of network nodes that attain the CRES mark. These performance measures are estimated and analyzed for three different PMF models of query generation namely Uniform, Gaussian and Poisson. The merit of deploying FCM algorithm in terms of maintaining much better energy profile of the entire network is discussed.
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U2 - 10.1002/dac.3112
DO - 10.1002/dac.3112
M3 - Article
VL - 29
SP - 1439
EP - 1450
JO - International Journal of Communication Systems
JF - International Journal of Communication Systems
SN - 1074-5351
IS - 8
ER -