Communication minimization for in-network processing in body sensor networks: A buffer assignment technique

Ghasemzadeh,; Jain, Alok; Sgroi, Giovanni; Jafari, Roozbeh

doi:10.1109/date.2009.5090688

Cited by 14 publications

(7 citation statements)

References 15 publications

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“…To prevent inference between two or adjacent people, all messages of a body sensor network can be encrypted using encryption mechanism (i.e., public/private key) [37]. Same mechanism is used in connection between Mobile node and Master node.…”

Section: Nodes Discovery Mechanismmentioning

confidence: 99%

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Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing

2015

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Advancements in computers and electronic technologies have led to the emergence of a new generation of efficient small intelligent systems. The products of such technologies might include Smartphones and wearable devices, which have attracted the attention of medical applications. These products are used less in critical medical applications because of their resource constraint and failure sensitivity. This is due to the fact that without safety considerations, small-integrated hardware will endanger patients' lives. Therefore, proposing some principals is required to construct wearable systems in healthcare so that the existing concerns are dealt with. Accordingly, this paper proposes an architecture for constructing wearable systems in critical medical applications. The proposed architecture is a three-tier one, supporting data flow from body sensors to cloud. The tiers of this architecture include wearable computers, mobile computing, and mobile cloud computing. One of the features of this architecture is its high possible fault tolerance due to the nature of its components. Moreover, the required protocols are presented to coordinate the components of this architecture. Finally, the reliability of this architecture is assessed by simulating the architecture and its components, and other aspects of the proposed architecture are discussed.

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Section: Nodes Discovery Mechanismmentioning

confidence: 99%

“…Whether data transmission is discrete or continuous is important in medical data rate management. In order to reduce energy consumption, in [37], the pieces of information are stored in buffers and then get transmitted discretely in specific time periods.…”

Section: Information Transfer and Communication Processesmentioning

confidence: 99%

Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing

2015

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“…Another protocol called Distributed Queuing Body Area Network (DQBAN) is proposed for better QoS support in BAN [ 25 ]. Ghasemzadeh et al proposed a power consumption technique that utilizes buffer information to reduce the number of transmissions among the nodes [ 26 ]. They further introduced compatibility graphs and described its importance in the power optimization [ 27 ].…”

Section: Related Workmentioning

confidence: 99%

MAC-Bridging for Multi-PHYs Communication in BAN

Ullah

Khan

Ullah

et al. 2010

Sensors

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Body Area Network (BAN) is a collection of low-power, miniaturised, and intelligent sensor nodes that are used for unobtrusive and ambulatory health monitoring of a patient without any additional constraints. These nodes operate on different frequency bands or Multiple Physical Layers (Multi-PHYs). Additionally, some BAN applications demand a logical connection between different nodes working on different Multi-PHYs. In this paper, the idea of controlling Multi-PHYs using one MAC protocol is introduced. Unlike existing procedures where different nodes working on different channels are connected at the link layer bridging/switching, the proposed procedure called bridging logically connects them at the MAC layer. In other words, the bridge is used to relay or filter packets between different PHYs in the same BAN. Numerical approximations are presented to analyze the stochastic behaviour of the bridges, all of them having Multi-PHYs interfaces. The MICS and the ISM bands are regarded as PHY1 and PHY2, respectively. The performance results are presented for PHY2 (given that data is already received from PHY1) in terms of probability of successful transmission, number of failed requests, power consumption, and delay. Simulations are conducted to validate the analytical results. It can be seen that the deployment of multiple bridges along with the corresponding nodes allows Multi-PHYs communication with high transmission probability, low power consumption, and tolerable delay.

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“…Likewise, the relay nodes also measure the same event and aggregate the data packets into a single packet. The proposed approaches are not suitable for WBANs prototype because to make any decision in WBAN, the measured data packets of the sensor nodes should be complementary (Ghasemzadeh et al, 2009). In this paper, however, the goal is to decrease the energy of the transmitted packet by using relatively low energy Wi-Fi technology.…”

Section: Related Workmentioning

confidence: 99%

Cloud-assisted data management in wireless body area networks

Quwaider

Jararweh

2017

IJCSE

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This paper presents an efficient large-scale data collection in wireless body area network (WBAN) in the presence of cloudlet-based prototype system. The key contribution of this paper is to collect the observed data of WBANs in a large-scale and convey it in consistent manner to the other end of service providers. A model of WBANs is proposed in this work including virtualised machines and cloudlet in order to characterise the efficient WBANs data collection. A scalable storage and processing infrastructure is proposed to support large-scale WBANs system, which is efficiently capable to handle the big data generated by large number of WBANs users. The proposed model supports effective cost communication technologies through Wi-Fi technology. Performance results of the proposed prototype are evaluated using advanced CloudSim simulator. The performance results show that the consumed power and packet delay of the collected data are decreased by increasing the number of virtualised machines and cloudlets in the monitored area. The results show also that the performance depends on the method of the virtualised cloudlet distribution in the target area for a given number of users.

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Communication minimization for in-network processing in body sensor networks: A buffer assignment technique

Cited by 14 publications

References 15 publications

Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing

Toward a Fault Tolerant Architecture for Vital Medical-Based Wearable Computing

MAC-Bridging for Multi-PHYs Communication in BAN

Cloud-assisted data management in wireless body area networks

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