scholarly journals Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling

2011 ◽  
Vol 7 (1) ◽  
pp. 928958
Author(s):  
Qi Qi ◽  
Yi Shang
Keyword(s):  
Gaussian Process ◽  
Graphical Model ◽  
Wireless Sensor ◽  
Sensor Scheduling ◽  
Model Based

A Probabilistic-Graphical-Model Based Approach for Representing Lineages in Uncertain Data

2011 ◽  
Vol 34 (10) ◽  
pp. 1897-1906 ◽  
Author(s):  
Kun YUE ◽  
Wei-Yi LIU ◽  
Yun-Lei ZHU ◽  
Wei ZHANG
Keyword(s):  
Graphical Model ◽  
Uncertain Data ◽  
Probabilistic Graphical Model ◽  
Model Based

A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints

2015 ◽  
Vol 43 (1) ◽  
pp. 267-281 ◽  
Author(s):  
Nikita Mishra ◽  
Huazhe Zhang ◽  
John D. Lafferty ◽  
Henry Hoffmann
Keyword(s):  
Graphical Model ◽  
Probabilistic Graphical Model ◽  
Performance Constraints ◽  
Model Based

scholarly journals A Model-Based Approach for Adaptable Middleware Evolution in WSN Platforms

2021 ◽  
Vol 10 (1) ◽  
pp. 20
Author(s):  
Walter Tiberti ◽  
Dajana Cassioli ◽  
Antinisca Di Marco ◽  
Luigi Pomante ◽  
Marco Santic
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Embedded System ◽  
Operating Systems ◽  
Parallel Evolution ◽  
Wireless Sensor ◽  
New Techniques ◽  
Model Based ◽  
And Performance ◽  
Hardware Platforms

Advances in technology call for a parallel evolution in the software. New techniques are needed to support this dynamism, to track and guide its evolution process. This applies especially in the field of embedded systems, and certainly in Wireless Sensor Networks (WSNs), where hardware platforms and software environments change very quickly. Commonly, operating systems play a key role in the development process of any application. The most used operating system in WSNs is TinyOS, currently at its TinyOS 2.1.2 version. The evolution from TinyOS 1.x and TinyOS 2.x made the applications developed on TinyOS 1.x obsolete. In other words, these applications are not compatible out-of-the-box with TinyOS 2.x and require a porting action. In this paper, we discuss on the porting of embedded system (i.e., Wireless Sensor Networks) applications in response to operating systems’ evolution. In particular, using a model-based approach, we report the porting we did of Agilla, a Mobile-Agent Middleware (MAMW) for WSNs, on TinyOS 2.x, which we refer to as Agilla 2. We also provide a comparative analysis about the characteristics of Agilla 2 versus Agilla. The proposed Agilla 2 is compatible with TinyOS 2.x, has full capabilities and provides new features, as shown by the maintainability and performance measurement presented in this paper. An additional valuable result is the architectural modeling of Agilla and Agilla 2, missing before, which extends its documentation and improves its maintainability.

scholarly journals An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks

2017 ◽  
Vol 13 (3) ◽  
pp. 155014771769896 ◽  
Author(s):  
Pengcheng Fu ◽  
Hongying Tang ◽  
Yongbo Cheng ◽  
Baoqing Li ◽  
Hanwang Qian ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Wireless Sensor ◽  
Sensor Scheduling ◽  
Scheduling Scheme
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