scholarly journals Randomized scheduling algorithm for data aggregation in wireless sensor networks

2010 ◽  
Author(s):  
Mario O. Diaz ◽  
Kin K. Leung
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Scheduling Algorithm ◽  
Wireless Sensor

scholarly journals Layer-Based Data Aggregation and Performance Analysis in Wireless Sensor Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Hongju Cheng ◽  
Yongzhao Chen ◽  
Naixue Xiong ◽  
Feifei Li
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Dimensional Space ◽  
Scheduling Algorithm ◽  
Wireless Sensor ◽  
Efficient Scheme ◽  
Aggregation Tree ◽  
Practical Performance ◽  
And Performance

Due to the similarity and correlation among sensed data in wireless sensor network, it is an important way to reduce the number of packets transmitted with data aggregation technology so as to prolong the network lifetime. However, data aggregation is still a challenging issue since quality-of-service, such as end-to-end delay, is generally considered as a severe criterion required in many applications. We focus on the minimum-latency data aggregation problem and proposed a new efficient scheme for it. The basic idea is that we first build an aggregation tree by ordering nodes into layers, and then we proposed a scheduling algorithm on the basis of the aggregation tree to determine the transmission time slots for all nodes in the network with collision avoiding. We have proved that the upper bound for data aggregation with our proposed scheme is bounded by(15R+Δ-15)for wireless sensor networks in two-dimensional space. Extensive simulation results have demonstrated that the proposed scheme has better practical performance compared with related works.

scholarly journals An Adaptive Aggregation Scheduling Algorithm Based on the Grid Partition in Large-Scale Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Xiaogang Qi ◽  
Lifang Liu ◽  
Gengzhong Zheng ◽  
Mande Xie
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Geographical Information ◽  
Wireless Sensor ◽  
Small Scale ◽  
Grid Partition ◽  
Adaptive Aggregation

Data aggregation algorithm aims to reduce the redundant information by gathering the sensed data, save energy, and prolong the lifetime of the network. However, the data aggregation technology will increase the network transmission delay of wireless sensor networks. Minimum-latency aggregation scheduling is designed to minimize the number of scheduled time slots to perform an aggregation. In this paper, we present an Adaptive Aggregation Scheduling Algorithm based on the Grid Partition (AASA-GP) in large-scale wireless sensor networks. By dividing the network into grids based on the geographical information, we allocate the channels according to the grid coordinates. Nodes with the same grid coordinates use the same channel and the adjacent grids use the different channels, so we can effectively avoid the wireless media transmission interference, increase the parallel transfer rate, and reduce the aggregation latency. Our extensive evaluation results demonstrate the superiority of the AASA-GP. For small-scale networks, the resultant latency is comparable with the best practice, and it is more suitable for large-scale wireless sensor networks.

scholarly journals Aggregation Tree Based Data Aggregation Algorithm in Wireless Sensor Networks

2016 ◽  
Vol 12 (06) ◽  
pp. 10
Author(s):  
Hu Yanhua ◽  
Xincai Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Scheduling Algorithm ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Trade Off ◽  
Redundant Data ◽  
Aggregation Tree

Abstract: In wireless sensor networks, efficient and effective data aggregation algorithms can prolong the network lifecycle by reducing communication of redundant data and improve the security of the networks. Tradition data aggregation algorithms in wireless sensor networks mainly aim to improve the energy utilization, and ignore the security and lifecycle. In order to get a good trade-off between these requirements, we proposed a data aggregation algorithm based on constructing a data aggregation tree. After give a formalism description of the problem, we proposed a data aggregation tree constructing algorithm. By minimize the maximal energy consumption of nodes, the algorithm can prolong the lifecycle. In data aggregation scheduling algorithm, we select the number of communications carefully to get the trade-off between low weighted delay and high network lifecycle. The simulation experiments show that, the proposed data aggregation algorithm consumes less energy while aggregating data from sensor nodes, and thus can prolong the network lifecycle.

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