- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Xiamen, China (2019.12.17-2019.12.20)] 2019 Photonics & Electromagnetics Research Symposium - Fall (PIERS - Fall) - Adjustable Dual-frequency FSS-amplifier Metasurface
摘要： Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.
关键词： wireless sensor networks,queue capacity,best effort,queueing analysis,Network coding
更新于2025-09-23 15:19:57
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Resonant Beam Communications with Photovoltaic Receiver for Optical Data and Power Transfer
摘要： Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.
关键词： queueing analysis,queue capacity,Network coding,wireless sensor networks,best effort
更新于2025-09-23 15:19:57
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Compact Three Phase Multilevel Inverter for Low and Medium Power Photovoltaic Systems
摘要： Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.
关键词： wireless sensor networks,queue capacity,best effort,queueing analysis,Network coding
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) - Kuala Lumpur, Malaysia (2019.9.17-2019.9.19)] 2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) - Real-time Motion Detection in Extremely Subsampled Compressive Sensing Video
摘要： Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.
关键词： wireless sensor networks,queue capacity,best effort,queueing analysis,Network coding
更新于2025-09-19 17:13:59
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[IEEE 2018 International Conference on Computational Science and Computational Intelligence (CSCI) - Las Vegas, NV, USA (2018.12.12-2018.12.14)] 2018 International Conference on Computational Science and Computational Intelligence (CSCI) - Combining LIDAR, Passive Infrared, and Markov Chain Prediction for Flexible, Portable Occupancy Monitoring
摘要： Asynchronous network coding has the potential to improve wireless network performance compared with simple routing. However, to achieve the maximum network coding gain, the encoding node consumes a few computing and storage resources that may be unaffordable for wireless sensor networks such as CubeSats. An analogous threshold strategy, called best effort network coding (BENC), which requires only minimal storage resources and no computing resources, is investigated in this paper as an efficient and convenient method of network coding. In this strategy, a new packet arrival evicts the head packet when the queue is full to avoid excessively long waits. Moreover, in contrast to other methods that require a queue for each flow, the BENC uses only one queue for the two coded flows. In addition, the problem of time interval distribution for the output flow, which combines two independent flows, is investigated, and the network coding gain is then analyzed. While the maximum coding gain requires infinite buffer capacity under two independent Poisson arrivals with the same transmission rates, the calculation results show that the BENC needs only 4 buffers to achieve 90% of the maximum coding gain and can reach 99% of the maximum coding gain using 50 buffers. These results are verified by numerical simulations.
关键词： wireless sensor networks,queue capacity,best effort,queueing analysis,Network coding
更新于2025-09-16 10:30:52