Adaptive and Radio-Agnostic QoS for Body Sensor Networks

Zhou, Gang; Li, Qiang; Li, Jingyuan; Wu, Yafeng; Lin, Shan; Lu, Joan; Wan, Chieh-Yih; Yarvis, Mark; Stankovic, John A.

doi:10.1145/2043662.2043672

Cited by 28 publications

(36 citation statements)

References 17 publications

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“…Latre et al in [24] evaluated the reliability of the Cascading Information retrieval by Controlling Access with Distributed slot Assignment (CIADIA) protocol, and proposed the improved mechanism based on CIADIA to further improve transmission reliability. Zhou et al in [25] studied the adaptive resource scheduling mechanism in WBAN to ensure reliable data transmission. Wu et al in [26] proposed a channel reservation mechanism that can improve the reliability of transmission in a non-ideal WBAN channel environment.…”

Section: Network Modelmentioning

confidence: 99%

An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

et al. 2017

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Abstract:As a key technology in smart healthcare monitoring systems, wireless body area networks (WBANs) can pre-embed sensors and sinks on body surface or inside bodies for collecting different vital signs parameters, such as human Electrocardiograph (ECG), Electroencephalograph (EEG), Electromyogram (EMG), body temperature, blood pressure, blood sugar, blood oxygen, etc. Using real-time online healthcare, patients can be tracked and monitored in normal or emergency conditions at their homes, hospital rooms, and in Intensive Care Units (ICUs). In particular, the reliability and effectiveness of the packets transmission will be directly related to the timely rescue of critically ill patients with life-threatening injuries. However, traditional fault-tolerant schemes either have the deficiency of underutilised resources or react too slowly to failures. In future healthcare systems, the medical Internet of Things (IoT) for real-time monitoring can integrate sensor networks, cloud computing, and big data techniques to address these problems. It can collect and send patient's vital parameter signal and safety monitoring information to intelligent terminals and enhance transmission reliability and efficiency. Therefore, this paper presents a design in healthcare monitoring systems for a proactive reliable data transmission mechanism with resilience requirements in a many-to-one stream model. This Network Coding-based Fault-tolerant Mechanism (NCFM) first proposes a greedy grouping algorithm to divide the topology into small logical units; it then constructs a spanning tree based on random linear network coding to generate linearly independent coding combinations. Numerical results indicate that this transmission scheme works better than traditional methods in reducing the probability of packet loss, the resource redundant rate, and average delay, and can increase the effective throughput rate.

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Section: Network Modelmentioning

confidence: 99%

An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

et al. 2017

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“…Let S cs and S ds be the control segment and the data segment of the response frame, and the time when the sub-node sends a response frame to the master node is T ts [30,31].…”

Section: Tdmamentioning

confidence: 99%

Channel modeling and power consumption analysis for galvanic coupling intra-body communication

Gao

Vai³

et al. 2016

J Wireless Com Network

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Intra-body communication (IBC), using the human body as the channel to transmit data, has lower power consumption, less radiation, and easier linking than common wireless communication technologies such as Bluetooth, ZigBee, and ANT + . As a result, IBC is greatly suitable for body area network (BAN) applications, such as the medical and health care field. Furthermore, IBC can be implemented in wearable devices, including smart watches, sports bracelets, somatic game devices, and multimedia devices. However, due to the limited battery capacity of sensor nodes in a BAN, especially implanted sensor nodes, it is not convenient to charge or change the batteries. Thus, the energy effectiveness of the media access control (MAC) layer strongly affects the life span of the nodes and of the entire system. Certainly, analyzing MAC layer performance in a galvanic coupling IBC is of great importance for the overall system. To obtain the attenuation properties of IBC, in vivo experiments with seven volunteers were performed. Meanwhile, an equalizer was used to compensate the frequency distortion in consideration of frequency-selective fading characteristics of intra-body channels. In addition, a comparison of the bit error rates (BER) of different modulation methods was carried out to obtain the best modulation method. Then, the attenuation characteristics of intra-body channels were applied in a multi-node physiological signal monitor and transmission system. Finally, TDMA and CSMA/CA protocols were introduced to calculate the bit energy consumption of IBC in the practical scenario. With stable characteristics of the intra-body channels, QPSK with an equalizer had a better performance than the tests without an equalizer. As a result, the modulation method of FSK could achieve a lower BER in lower signal-to-noise ratio situations and an FSK method with TDMA for the IBC had the lowest energy consumption under different practical scenarios.

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“…Otherwise, it backs off again. Therefore, the expected backoff time period for a packet transmission is t cw = cw/2×min{M − 1/2, R} [32], where M −1 is the number of potential contenders sharing the same AP with the aggregator and R is the maximum number of backoff retries.…”

Section: Wifi Transmissionmentioning

confidence: 99%

Towards Energy Optimization Using Joint Data Rate Adaptation for BSN and WiFi Networks

et al. 2012

2012 IEEE Seventh International Conference on Networking, Architecture, and Storage

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Abstract-Body sensor networks (BSNs) and WiFi networks have been widely investigated due to the availability of sensor motes and WiFi devices, but they are commonly deployed separately. In this paper we propose to optimize the total communication energy consumption of BSN and WiFi (BSN-WiFi) networks using joint data rate adaptation. More specifically, we first elaborate the BSN-WiFi network system in four consecutive phases. Then based on the system, we analyze the communication energy consumption, throughput and time delay, and provide a signal-to-noise ratio and packet delivery ratio (SNR-PDR) mappings of BSN and WiFi networks. Next, we build an energy optimization model with constraints of SNR-PDR mappings, throughput, and time delay to minimize the total communication energy consumption in BSN-WiFi networks. With the input of SNR values, we solve this model by cvx to obtain the output of optimal data rates associated with SNR values, which are then tabulated for online data rate adaptation. Finally, we collect 20-minute traces from a specific BSN-WiFi network system for performance evaluation, and the results demonstrate that our optimal data rate solution achieves up to 86% energy savings comparing with the solutions using fixed data rates.

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Adaptive and Radio-Agnostic QoS for Body Sensor Networks

Cited by 28 publications

References 17 publications

An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

Channel modeling and power consumption analysis for galvanic coupling intra-body communication

Towards Energy Optimization Using Joint Data Rate Adaptation for BSN and WiFi Networks

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