Big program code dissemination scheme for emergency software-define wireless sensor networks

Liu, Xiao; Li, Gao‐xiang; Zhang, Shigeng; Liu, Anfeng

doi:10.1007/s12083-017-0565-5

Cited by 42 publications

(75 citation statements)

References 34 publications

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“…Reference [33] introduced IOT and WSN in a mine and described the mine production, monitoring, and prewarning system based on big data technology, but it did not explain how to use sensor nodes and how to build the prewarning model. References [34][35][36][37][38][39][40][41][42][43][44] designed an architecture of monitoring system based on WSN and discussed a data aggregation strategy but did not consider using big data. Our paper focuses on how to design the monitoring and prewarning system suitable for coal mine industry, how to use data aggregation strategy to decrease energy consumption, and how to build a prewarning model to prevent the accident happening in advance.…”

Section: Related Studiesmentioning

confidence: 99%

“…The Coalmining tunnels in China usually are categorized with their functions, including development tunnels, preparation tunnels, and mining tunnels [23,30,[35][36][37][38][39][40][41][42][43][44]. The development tunnels are served for the whole mine, including the horizontal mining area, such as the main haulage roadways and the main return airways.…”

Section: Structure Of Monitoring Networkmentioning

confidence: 99%

“…For example, the sensor nodes Scientific Programming characteristics (transmission, processor, radio range, etc.) are determined according to the specification of [31,35,39,42]. Table 2 resumes the values of importance factor , , , and .…”

Section: Simulationsmentioning

confidence: 99%

“…We define the energy consumption as the average value of the energy consumed by each sensor node during their transmit, receive, and process data. We use the classical energy consumption model [39][40][41] for simulation. Figure 10 shows the comparison between PCEB-MS and our strategy.…”

Section: Performance Analysismentioning

confidence: 99%

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Research on Monitoring and Prewarning System of Accident in the Coal Mine Based on Big Data

Chen

Wei

2018

Scientific Programming

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More and more big data come from sensor nodes. There are many sensor nodes placed in the monitoring and prewarning system of the coal mine in China for the purpose of monitoring the state of the environment. It works every day and forms the coal mine big data. Traditional coal mine monitoring and prewarning systems are mainly based on mine communication cable, but they are difficult to place at coal working face tunnels. We use WSN to replace mine communication cable and build the monitoring and prewarning system. The sensor nodes in WSN are energy limited and the sensor data are complicated so it is very difficult to use these data directly to prewarn the accident. To solve these problems, in this paper, a new data aggregation strategy and fuzzy comprehensive assessment model are proposed. Simulations compared the energy consumption, delay time, cooperation cost, and prewarning time with our previous work. The result shows our method is reasonable.

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Section: Related Studiesmentioning

confidence: 99%

Section: Structure Of Monitoring Networkmentioning

confidence: 99%

Section: Simulationsmentioning

confidence: 99%

Section: Performance Analysismentioning

confidence: 99%

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Research on Monitoring and Prewarning System of Accident in the Coal Mine Based on Big Data

Chen

Wei

2018

Scientific Programming

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“…The Internet of Things (IoT) [1][2][3][4] uses smart equipment such as sensor-based devices [5][6][7][8][9][10][11], smartphones [12] and vehicle sensor devices [13] to gathering information and give a different method for carrying out complex data-sensing-based tasks to satisfy the significant demands of critical infrastructures [14][15][16][17][18], such as environmental and weather monitoring systems [19][20][21][22][23]. Wireless Sensor Networks (WSNs) has large numbers of sensor nodes, it has huge potential to solve military and civilian domains [24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Reliability Improved Cooperative Communication over Wireless Sensor Networks

Chen

Liu

et al. 2017

Symmetry

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Abstract:With the development of smart devices and connection technologies, Wireless Sensor Networks (WSNs) are becoming increasingly intelligent. New or special functions can be obtained by receiving new versions of program codes to upgrade their software systems, forming the so-called smart Internet of Things (IoT). Due to the lossy property of wireless channels, data collection in WSNs still suffers from a long delay, high energy consumption, and many retransmissions. Thanks to wireless software-defined networks (WSDNs), software in sensors can now be updated to help them transmit data cooperatively, thereby achieving more reliable communication. In this paper, a Reliability Improved Cooperative Communication (RICC) data collection scheme is proposed to improve the reliability of random-network-coding-based cooperative communications in multi-hop relay WSNs without reducing the network lifetime. In WSNs, sensors in different positions can have different numbers of packets to handle, resulting in the unbalanced energy consumption of the network. In particular, nodes in non-hotspot areas have up to 90% of their original energy remaining when the network dies. To efficiently use the residual energy, in RICC, high data transmission power is adopted in non-hotspot areas to achieve a higher reliability at the cost of large energy consumption, and relatively low transmission power is adopted in hotspot areas to maintain the long network lifetime. Therefore, high reliability and a long network lifetime can be obtained simultaneously. The simulation results show that compared with other scheme, RICC can reduce the end-to-end Message Fail delivering Ratio (MFR) by 59.4%-62.8% under the same lifetime with a more balanced energy utilization.

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