Evidence map›Paper›PMID 34201100›Full record

ArticleSensors (Basel, Switzerland)2021

Grouping and Sponsoring Centric Green Coverage Model for Internet of Things.

Vinod Kumar, Sushil Kumar, Rabah AlShboul, Geetika Aggarwal, Omprakash Kaiwartya, Ahmad M Khasawneh, Jaime Lloret, Mahmoud Ahmad Al-Khasawneh

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Vinod KumarSchool of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi 110067, India.
Sushil KumarSchool of Computer and Systems Sciences, Jawaharlal Nehru University (JNU), New Delhi 110067, India.ORCID 0000-0001-9113-2890
Rabah AlShboulComputer Science Department, Faculty of Information Technology, Al al-Bayt University, Mafraq 25113, Jordan.
Geetika AggarwalSchool of Science & Technology, Clifton Campus, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0002-8338-2504
Omprakash KaiwartyaSchool of Science & Technology, Clifton Campus, Nottingham Trent University, Nottingham NG11 8NS, UK.ORCID 0000-0001-9669-8244
Ahmad M KhasawnehDepartment of Mobile Computing, Amman Arab University, Amman 11953, Jordan.ORCID 0000-0002-1850-3269
Jaime LloretIntegrated Management Coastal Research Institue, Universitat Politecnica de Valencia, 46022 Valencia, Spain.ORCID 0000-0002-0862-0533
Mahmoud Ahmad Al-KhasawnehFaculty of Computer & Information Technology, Al-Madinah International University, Kuala Lumpur 57100, Malaysia.ORCID 0000-0003-1698-0237

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, green computing has received significant attention for Internet of Things (IoT) environments due to the growing computing demands under tiny sensor enabled smart services. The related literature on green computing majorly focuses on a cover set approach that works efficiently for target coverage, but it is not applicable in case of area coverage. In this paper, we present a new variant of a cover set approach called a grouping and sponsoring aware IoT framework (GS-IoT) that is suitable for area coverage. We achieve non-overlapping coverage for an entire sensing region employing sectorial sensing. Non-overlapping coverage not only guarantees a sufficiently good coverage in case of large number of sensors deployed randomly, but also maximizes the life span of the whole network with appropriate scheduling of sensors. A deployment model for distribution of sensors is developed to ensure a minimum threshold density of sensors in the sensing region. In particular, a fast converging grouping (FCG) algorithm is developed to group sensors in order to ensure minimal overlapping. A sponsoring aware sectorial coverage (SSC) algorithm is developed to set off redundant sensors and to balance the overall network energy consumption. GS-IoT framework effectively combines both the algorithms for smart services. The simulation experimental results attest to the benefit of the proposed framework as compared to the state-of-the-art techniques in terms of various metrics for smart IoT environments including rate of overlapping, response time, coverage, active sensors, and life span of the overall network.

Indexed as

Internet of ThingsAlgorithmsComputer SimulationConfidentialityenergy efficiencygreen computinginternet of thingslifetime maximization

Identifiers

PMID34201100
PMCPMC8226805

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.