Distributed Data Aggregation Scheduling in Multi-Channel and Multi-Power Wireless Sensor Networks

Large amounts of sensor data are frequently generated and streamed from sensors deployed on various buildings, in forests or in other application areas. In many of these areas, one difficulty is managing the velocity and volume of the big sensor data while still providing low time latency support fo...

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Bibliographic Details
Published in:IEEE access 2017, Vol.5, p.27887-27896
Main Authors: Ren, Meirui, Li, Jianzhong, Guo, Longjiang, Li, Xiaokun, Fan, Wenbin
Format: Article
Language:English
Subjects:
Agglomeration
Algorithms
Big sensor data
Clustering algorithms
Clusters
Computer science
Data aggregation
Data analysis
Data management
Distributed algorithms
Electric power distribution
minimize latency
multi-channel
multi-power
Network latency
Packet transmission
Schedules
Scheduling
Sensors
Wireless networks
Wireless sensor networks
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Summary:Large amounts of sensor data are frequently generated and streamed from sensors deployed on various buildings, in forests or in other application areas. In many of these areas, one difficulty is managing the velocity and volume of the big sensor data while still providing low time latency support for data analysis. Data aggregation can reduce the volume of big sensor data. However, data aggregation is a fundamental yet time-consuming operation in wireless sensor networks (WSNs), particularly in high-density WSNs. Therefore, researchers have started focusing on minimizing the latency of data aggregation, which has been proven to be an NP-hard problem. This paper proposes a cluster-based distributed data aggregation scheduling algorithm, distributed multi-power and multi-channel (DMPMC), that can minimize the data aggregation latency in multi-channel and multi-power WSNs. To save energy, low transmission power is used for packet transmissions inside a cluster, and high power is used for packet transmissions among clusters. Simulations are conducted to compare DMPMC with the best centralized algorithm in a single channel, named E-PAS, the best distributed algorithm in a single channel, named CLU-DDAS, and the best algorithm in multi-channels, named multi-channel. The results show that the DMPMC algorithm proposed in this paper achieves the lowest average latency.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2017.2734847