Research on Data Aggregation Algorithms Based on OPT in Wireless Sensor Networks

2013 ◽  
Vol 427-429 ◽  
pp. 1991-1994
Author(s):  
Xue Wen He ◽  
Le Ping Zheng ◽  
Kuan Gang Fan ◽  
Sun Han ◽  
Qing Mei Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Measurement Accuracy ◽  
Wireless Sensor ◽  
Data Traffic ◽  
Fusion Model ◽  
Design Goal ◽  
Improve Measurement ◽  
Battery Energy

Since wireless sensor networks consist of sensors with limited battery energy, a major design goal is to maximize the lifetime of sensor network. To improve measurement accuracy and prolong network lifetime, reducing data traffic is needed. In the clustering-based wireless sensor networks, a novel data aggregation algorithm based on OPT and Layida Method is proposed. In the proposed method, Layida Method preprocesses data and data fusion model for data integration are used. Its availability is proved by comparing with the results of two existing algorithms.

scholarly journals Improved continuous enhancement routing solution for energy-aware data aggregation in wireless sensor networks

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877468 ◽  
Author(s):  
Edson Ticona-Zegarra ◽  
Rafael CS Schouery ◽  
Leandro A Villas ◽  
Flávio K Miyazawa
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Aggregation ◽  
Energy State ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Network Nodes ◽  
Battery Energy ◽  
Routing Tree

Wireless sensor networks consist of hundreds or thousands of nodes with limited energy resources, and thus, efficient use of energy is necessary for these networks. Given that transmissions are the most energy-demanding operation, routing algorithms should consider efficient use of transmissions in their designs in order to extend the network lifetime. To tackle these challenges, a centralized algorithm is proposed, called improved continuous enhancement routing (ICER), for computing routing trees of refined quality, based on data aggregation while being aware of the battery energy state. Comparisons between ICER and other known solutions in the literature are performed. Our experiments show that ICER is able to ensure, on average, the survival of 99.6% and the connectivity of 99.3% of the network nodes compared to 90.2% and 72.4% in relation to the best-compared algorithm. The obtained results show that ICER significantly extends the network lifetime while maintaining the quality of the routing tree.

A Spatial Correlation Based Data Aggregation Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 655-657 ◽  
pp. 655-659 ◽  
Author(s):  
Lei Chun Wang ◽  
Guo Yu Zhou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Spatial Correlation ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Data Detection ◽  
Data Traffic ◽  
Quality Of Data ◽  
Energy Consumption Rate

Data aggregation is the important method to reduce data traffic and lower energy expenditure in wireless sensor networks (WSN). This paper analyzes the characteristics of data sampled by nodes, and gives the method to decide spatial correlation between neighboring nodes and the criteria to classify and decide data in WSN. On the basis of this, this paper proposes a spatial correlation based data aggregation algorithm for WSN, SCBD. SCBD classifies and decides data according to data criteria and spatial correlation among nodes in normal nodes and cluster heads at the same time, and then aggregates different types of data. The results show that SCBD outperforms RAA in terms of energy consumption, rate of data detection and quality of data aggregation.

Energy efficient fixed-cluster architecture for wireless sensor networks

2021 ◽  
Vol 40 (5) ◽  
pp. 8727-8740
Author(s):  
Rajvir Singh ◽  
C. Rama Krishna ◽  
Rajnish Sharma ◽  
Renu Vig
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Search Algorithm ◽  
Cluster Formation ◽  
Wireless Sensor ◽  
Efficient Operation ◽  
Cluster Architecture ◽  
Dynamic Cluster

Dynamic and frequent re-clustering of nodes along with data aggregation is used to achieve energy-efficient operation in wireless sensor networks. But dynamic cluster formation supports data aggregation only when clusters can be formed using any set of nodes that lie in close proximity to each other. Frequent re-clustering makes network management difficult and adversely affects the use of energy efficient TDMA-based scheduling for data collection within the clusters. To circumvent these issues, a centralized Fixed-Cluster Architecture (FCA) has been proposed in this paper. The proposed scheme leads to a simplified network implementation for smart spaces where it makes more sense to aggregate data that belongs to a cluster of sensors located within the confines of a designated area. A comparative study is done with dynamic clusters formed with a distributive Low Energy Adaptive Clustering Hierarchy (LEACH) and a centralized Harmonic Search Algorithm (HSA). Using uniform cluster size for FCA, the results show that it utilizes the available energy efficiently by providing stability period values that are 56% and 41% more as compared to LEACH and HSA respectively.

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