DST: Delay Sensitive Transport in Wireless Sensor Networks

2006 ◽  
Author(s):  
V.C. Gungor ◽  
O.B. Akan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Delay Sensitive

scholarly journals Delay-sensitive flooding based on expected path quality in low duty-cycled wireless sensor networks

2016 ◽  
Vol 12 (8) ◽  
pp. 155014771666425 ◽  
Author(s):  
Dung Tien Nguyen ◽  
Junseong Choe ◽  
Thang Le Duc ◽  
Duc Tai Le ◽  
Vyacheslav V Zalyubovskiy ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Delay Sensitive ◽  
Path Quality

scholarly journals A Flexible Framework for Assessing the Quality of Information in Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Hao Guo ◽  
Zhongming Pan ◽  
Zhiping Huang ◽  
Jing Zhou
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Measurement Data ◽  
Information Aggregation ◽  
Wireless Sensor ◽  
Acquisition Time ◽  
Quality Of Information ◽  
Delay Sensitive ◽  
Flexible Framework

As wireless sensor networks (WSNs) often provide incorrect and outdated information about the events in a monitored environment, quality of information (QoI) assessment is invaluable for users to manage and use the information in particular applications. In this paper, we propose a flexible framework to dynamically assess the QoI in different WSN applications, with focus on accuracy and timeliness. Our framework is constructed on the infrastructure of an information aggregation procedure under some assumptions about the network. Based on information fusion theory, two processing models are adopted to assess the accuracy of low-level measurement data and high-level decision information without the need for Ground Truth (GT). Meanwhile, our framework generally exploits two respective models according to the specific category of the information timeliness in different delay-sensitive applications. To quantify the timeliness, we utilize a practical measurement method by means of timestamp to determine the information acquisition time. The framework is evaluated by simulations, including accuracy assessment in two environmental monitoring application scenarios, and timeliness assessment in two delay-sensitive application scenarios. The simulation results show that our framework is effective and flexible for quantitative assessment of the QoI in different WSN applications.

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