Intelligent Task Scheduling of Distributed Wireless Sensor Network to Monitor Building Environment

2021 ◽  
Author(s):  
Yifei Wang
2014 ◽  
Vol 536-537 ◽  
pp. 731-734
Author(s):  
Kang Hong Duan ◽  
Li Ting Zhang ◽  
Long Ma ◽  
Hong Xin Zhang

Event-driven systems and thread-driven systems are two major design philosophies of operating system in wireless sensor networks. Systems based on multi-threaded are more timeliness than the event-driven systems, which can meet the requirements of time-critical tasks by means of task preemption, while systems based on event-driven are more energy efficient.The article introduces a task scheduling module in event-driven system. The module takes a kind of priority table query method to choose the most important task with highest priority to schedule.It is seen that the module is suitable wireless sensor network.


2013 ◽  
Vol 479-480 ◽  
pp. 646-650
Author(s):  
Rong Shue Hsiao ◽  
Ding Bing Lin ◽  
Hsin Piao Lin ◽  
Chen Hua Chung

Wireless sensor networks have the advantages of low cost installation and flexibility, which make them an excellent mechanism for capturing environmental data and interacting with the physical environment for the application of building automation. However, radio propagation suffers from multi-path, shadowing and other radio interference problems in building environments. Therefore, deployment of sensor nodes in a dynamic in-building environment is a complex operation that requires expert knowledge and experience. In this paper, we present a deployment planning tool that can provide a set of useful tools for deploying a wireless sensor network in the building environment. The proposed deployment planning tool provides design tools that can assist users to develop a network infrastructure in order to support reliable communication. In addition, a network evaluation tool is provided to measure the index of network quality in order to ensure a reliable network quality. In order to evaluate the effectiveness of this tool, we designed a sensor network and simulated the network quality using this tool. The simulation results matched the experimental results of realistic deployment very well.


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