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A Novel Power-Efficient Data Aggregation Scheme for Cloud-Based Sensor Networks

delete2022-04-22
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OA
AI
A
Abhishek Bajpai *
S
Shashank Yadav
N
Naveen Kumar Tiwari
A
Anita Yadav
M
Mansi Chaurasia
DOI:10.4018/IJMCMC.297964delete
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Abstract

Abstract

En 中文
Sensor nodes are being deployed everywhere as per the applications and real-time data analysis. A major concern of this implementation is the limited battery power and huge data generation. The data redundancy can also be a cause of battery decay. This scheme spends the energy based on priority. This method also uses a mobile agent for the data collection from the sensor nodes. When it is combined with optimal cluster head along with marking of subtle aggregators, it gives a satisfying performance. This approach is divided into three phases: clustering of sensor nodes then computing PEDAS and finally deploy a mobile agent. The approach of PEDAS measures parameters in an optimized manner which develops an energy-efficient system and only spends the energy at the moment when it is needed the most. The proposed model was simulated and verified using network-simulator 3. Implementation and analysis of the algorithm prove that this research study has improved the lifetime of the entire network and also provided a stable and robust network while comparing it with EEDAC and ATL schemes.
Keywords:
Cloud Computing
Data Aggregation
Internet of Things
Sensor Network

Journal

International Journal of Computers Communications and Control cover
International Journal of Computers Communications and Control
IF:
1.9
Papers:
25
Citations:
987

Organization

H
harcourt butler technical university (hbtu)
Scholars:
383
Papers: 333
Citations: 1