Hybrid Relaying in Ultra-wideband Body Area Networks

Rout, Deepak Kumar; Das, Susmita

doi:10.1007/s11277-015-2938-5

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…28 In wireless body area networks, biomedical sensors can be broadly divided into two categories: on-body sensors and off-body sensors. 29 Onbody sensors are sewed to the cloth or attached on the skin of a person's body (e.g. smart watch) and off-body sensors are kept away few centimeters from a person's body (e.g.…”

Section: The Proposed Architecturementioning

confidence: 99%

An edge cloud–based body data sensing architecture for artificial intelligence computation

Kim

Lim

2019

International Journal of Distributed Sensor Networks

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As various applications and workloads move to the cloud computing system, traditional approaches of processing sensor data cannot be applied. Specifically, tenants may experience incompatibility and unpredictable performance variation due to inefficient implementations. In this article, we present an edge cloud-based body data sensing architecture for artificial intelligence computation. The main rationale for designing the edge cloud-based sensing architecture is as follows. By analyzing physical body data on the edge cloud computing system, we can identify the relationship between body activities and health conditions for persons. In addition, we can support real-time applications without catastrophic failures by our efficient and stable implementation of the sensing architecture. Our cloud storage architecture is designed to support both stateful and stateless applications, which are compatible with traditional infrastructures and provide server consolidation with a CPU-aware scheduling of virtual machines. Performance results show that our edge cloud-based architecture outperforms the previous architecture in terms of failures, processing time, and scalability.

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Section: The Proposed Architecturementioning

confidence: 99%

An edge cloud–based body data sensing architecture for artificial intelligence computation

Kim

Lim

2019

International Journal of Distributed Sensor Networks

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“…Further, WBAN communication is real-time, wireless, and short-range [12], [13]. Biomedical sensors can be widely divided into three categories, namely, in-body, on-body, and off-body sensors [14]. In-body sensors are implanted inside the patient's body to transmit monitored data to the sink node, whereas on-body sensors are placed on the patient's body surface to monitor health data and send them to a sink node, and off-body sensors are located several centimeters away from a patient's body to obtain monitored data [15].…”

Section: Introductionmentioning

confidence: 99%

Simplified Energy-Balanced Alternative-Aware Routing Algorithm for Wireless Body Area Networks

Liu

2019

IEEE Access

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Nowadays, the needs of healthcare for the elderly are growing rapidly. To provide continuous all-day medical monitoring and diagnoses at low cost, wireless body area networks (WBANs) have become a forward-looking technology since it is regarded as a potential solution for the remote collecting of physical and symptoms information. Because of its application characteristics, reliability and delay are the most important, as the energy consumption also needs to be considered. However, due to the limitation of the large propagation loss and the complicated channel conditions, the existing routing algorithms cannot completely address the above problems. To balance the node energy consumption and reduce the transmission delay, a simplified energy-balanced alternative-aware routing algorithm (SEAR) for WBANs is proposed in this paper. The residual energy and the current load of a candidate of the next hop destination are considered during the routing request forwarding procedures. The required information is exchanged during the improved routing request and routing request response procedures, and the routing cost is modified accordingly. To improve the compatibility and robustness, the added path is introduced as an alternative path in our algorithm. The simulation results show that SEAR achieves significantly higher network residual energy and network throughput, and end-to-end delay is also reduced. Therefore, the lifetime of the network is extended effectively.INDEX TERMS Wireless body area networks (WBANs), routing request, residual energy, routing algorithm, simplified, NS2.

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“…WBAN comprises of small BMSs that are wirelessly connected to a Body Area Network Coordinator (BANC) [6]. BMSs can be broadly divided into three categories, namely; in-body, on-body and off-body sensors [7]. In-body sensors are implanted inside the patient's body, whereas on-body sensors are sewed to the shirt or attached on the skin of a patient's body, and off-body sensors are kept away few centimeters from a patient's body [8].…”

mentioning

confidence: 99%

Medium Access Control (MAC) for Wireless Body Area Network (WBAN): Superframe structure, multiple access technique, taxonomy, and challenges

Ullah

Abdullah

Kaiwartya

et al. 2017

Hum. Cent. Comput. Inf. Sci.

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Health monitoring using biomedical sensors has witnessed significant attention in recent past due to the evolution of a new research area in sensor network known as Wireless Body Area Networks (WBANs). In WBANs, a number of implantable, wearable, and off-body biomedical sensors are utilized to monitor various vital signs of patient’s body for early detection, and medication of grave diseases. In literature, a number of Medium Access Control (MAC) protocols for WBANs have been suggested for addressing the unique challenges related to reliability, delay, collision and energy in the new research area. The design of MAC protocols is based on multiple access techniques. Understanding the basis of MAC protocol designs for identifying their design objectives in broader perspective, is a quite challenging task. In this context, this paper qualitatively reviews MAC protocols for WBANs. Firstly, 802.15.4 and 802.15.6 based MAC Superframe structures are investigated focusing on design objectives. Secondly, different multiple access techniques such as TDMA, CSMA/CA, Slotted Aloha and Hybrid are explored in terms of design goals. Thirdly, a two-layered taxonomy is presented for MAC protocols. First layer classification is based on multiple access techniques, whereas second layer classification is based on design objectives and characteristics of MAC protocols. Critical and qualitative analysis is carried out for each considered MAC protocol. Comparative study of different MAC protocols is also performed. Finally, some open research challenges in the area are identified with initial research directions.

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Hybrid Relaying in Ultra-wideband Body Area Networks

Cited by 5 publications

References 23 publications

An edge cloud–based body data sensing architecture for artificial intelligence computation

An edge cloud–based body data sensing architecture for artificial intelligence computation

Simplified Energy-Balanced Alternative-Aware Routing Algorithm for Wireless Body Area Networks

Medium Access Control (MAC) for Wireless Body Area Network (WBAN): Superframe structure, multiple access technique, taxonomy, and challenges

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