Modeling on Body Delay Tolerant Network Sink Locality of Wireless Body Area Networks for Different Body Postures

Anthony M Mile

Modeling on Body Delay Tolerant Network Sink Locality of Wireless Body Area Networks for Different Body Postures

Anthony M Mile *

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Modeling on Body Delay Tolerant Network Sink Locality of Wireless Body Area Networks for Different Body Postures

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Abstract

Due to the recent advancements in the field of wireless communication and Wireless Sensor Networks, the Wireless Body Area Networks (WBANs) have become an area of concern for researchers. In military operations, patient monitoring, sports field, among other wireless body area networks is used for real time monitoring and smart sensing for eHealth operations. In these WBAN, disconnections between the body sensors occur quite often and sometimes of significant duration due to the postural mobility nature of the human. These consequently affects the efficiency of the entire network hence the need for Delay Tolerant Network (DTN). The DTN minimizes delays and adapts itself to cope with long delays if they occur. One of the vital mechanisms that can be employed to enhance the efficiency of the network is to determine the optimal postural locality of the sink node.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Anthony M Mile. 2020. "Modeling on Body Delay Tolerant Network Sink Locality of Wireless Body Area Networks for Different Body Postures". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 20 (GJCST Volume 20 Issue E1).

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GJCST Volume 20 Issue E1

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-E Classification J.m

Submission ReceivedDecember 13, 2019
Peer Review Double Blind
Handling Editor
Accepted December 31, 2019
Published January 15, 2020

Version of record

v1.2

Issue date

May 12, 2020

Language

English

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