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A Novel Power-Efficient Data Aggregation Scheme for Cloud-Based Sensor Networks
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DOI：10.4018/IJMCMC.297964.png)
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摘要
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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.
Keyword:
Cloud Computing
Data Aggregation
Internet of Things
Sensor Network
期刊
IF:
1.9
论文数:
25
被引数:
987
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