Evidence map›Paper›PMID 31067763›Full record

ArticleSensors (Basel, Switzerland)2019

Fuzzy-Based Dynamic Time Slot Allocation forWireless Body Area Networks.

Sangeetha Pushpan, Bhanumathi Velusamy

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Sangeetha PushpanDepartment of Electronics and Communication Engineering, Anna University Regional Campus, Coimbatore, India. cpsangis@gmail.com.ORCID 0000-0002-9506-0107
Bhanumathi VelusamyDepartment of Electronics and Communication Engineering, Anna University Regional Campus, Coimbatore, India. vbhanu_02@yahoo.com.ORCID 0000-0001-5661-347X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the advancement in networking, information and communication technologies,wireless body area networks (WBANs) are becoming more popular in the field of medical andnon-medical applications. Real-time patient monitoring applications generate periodic data in a shorttime period. In the case of life-critical applications, the data may be bursty. Hence the system needsa reliable energy efficient communication technique which has a limited delay. In such cases thefixed time slot assignment in medium access control standards results in low system performance.This paper deals with a dynamic time slot allocation scheme in a fog-assisted network for a real-timeremote patient monitoring system. Fog computing is an extended version of the cloud computingparadigm, which is suitable for reliable, delay-sensitive life-critical applications. In addition, toenhance the performance of the network, an energy-efficient minimum cost parent selection algorithmhas been proposed for routing data packets. The dynamic time slot allocation uses fuzzy logic withinput variables as energy ratio, buffer ratio, and packet arrival rate. Dynamic slot allocation eliminatesthe time slot wastage, excess delay in the network and attributes a high level of reliability to thenetwork with maximum channel utilization. The efficacy of the proposed scheme is proved in termsof packet delivery ratio, average end to end delay, and average energy consumption when comparedwith the conventional IEEE 802.15.4 standard and the tele-medicine protocol.

Indexed as

fog computingfuzzyhealthcaremedium accessslot allocationwireless body area networks

Identifiers

PMID31067763
PMCPMC6540075

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.