Energy-Collision Aware Data Aggregation Scheduling for Energy Harvesting Sensor Networks

2018 ◽  
Author(s):  
Quan Chen ◽  
Hong Gao ◽  
Zhipeng Cai ◽  
Lianglun Cheng ◽  
Jianzhong Li
Keyword(s):  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Aggregation ◽  
Energy Collision ◽  
Data Aggregation Scheduling

Energy-collision-aware Minimum Latency Aggregation Scheduling for Energy-harvesting Sensor Networks

2021 ◽  
Vol 17 (4) ◽  
pp. 1-34
Author(s):  
Quan Chen ◽  
Zhipeng Cai ◽  
Lianglun Cheng ◽  
Hong Gao ◽  
Jianzhong Li
Keyword(s):  
Sensor Networks ◽  
Energy Harvesting ◽  
Data Aggregation ◽  
High Performance ◽  
Renewable Energy Sources ◽  
Residual Energy ◽  
Interference Model ◽  
Energy Collision ◽  
Minimum Latency ◽  
Physical Interference Model

The emerging energy-harvesting technology enables charging sensor batteries with renewable energy sources, which has been effectively integrated into Wireless Sensor Networks (EH-WSNs). Due to the limited energy-harvesting capacities of tiny sensors, the captured energy remains scarce and differs greatly among nodes, which makes the data aggregation scheduling problem more challenging than that in energy-abundant WSNs. In this article, we investigate the Minimum Latency Aggregation Scheduling (MLAS) problem in EH-WSNs. First, we identify a new kind of collision in EH-WSNs, named as energy-collision, and design several special structures to avoid it during data aggregation. To reduce the latency, we try to choose the parent adaptively according to nodes’ transmission tasks and energy-harvesting ability, under the consideration of collisions avoidance. By considering transmitting time, residual energy, and energy-collision, three scheduling algorithms are proposed under protocol interference model. Under physical interference model, several approximate algorithms are also designed by taking account of the interference from the nodes several hops away. Finally, the theoretical analysis and simulation results verify that the proposed algorithms have high performance in terms of latency.

CONFLICT-AWARE DATA AGGREGATION SCHEDULING IN WIRELESS SENSOR NETWORKS WITH ADJUSTABLE TRANSMISSION RANGE

2012 ◽  
Vol 04 (03) ◽  
pp. 1250013 ◽  
Author(s):  
YI HONG ◽  
HONGWEI DU ◽  
DEYING LI ◽  
WENPING CHEN
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Base Station ◽  
Sensor Nodes ◽  
Performance Ratio ◽  
Wireless Sensor ◽  
Transmission Range ◽  
Minimum Latency ◽  
Data Aggregation Scheduling

The minimum latency data aggregation schedule is one of the fundamental problems in wireless sensor networks. Most existing works assumed that the transmission ranges of sensor nodes cannot be adjusted. However, sensors with adjustable transmission ranges have advantages in energy saving, reducing transmission interference and latency. In this paper, we study the minimum latency conflict-aware data aggregation scheduling problem with adjustable transmission radii: given locations of sensors along with a base station, all sensors could adjust their transmission radii and each sensor's interference radius is α times of its transmission radius, we try to find a data aggregation schedule in which the data from all sensors can be transmitted to the base station without conflicts, such that the latency is minimized. We first partition the set of all nodes into two parts: the major set and the minor set. Then, we design different scheduling strategies for the two sets, respectively. Finally, we propose an approximation algorithm for the problem and prove the performance ratio of the algorithm is bounded by a nearly constant. Our experimental results evaluate the efficiency of the proposed algorithm.

Distributed Low-Latency Data Aggregation Scheduling in Wireless Sensor Networks

2015 ◽  
Vol 11 (3) ◽  
pp. 1-36 ◽  
Author(s):  
Miloud Bagaa ◽  
Mohamed Younis ◽  
Djamel Djenouri ◽  
Abdelouahid Derhab ◽  
Nadjib Badache
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Low Latency ◽  
Latency Data ◽  
Data Aggregation Scheduling
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