An ACO and Mobile Sink based Algorithm for Improvement of ML-MAC for Wsns using Compressive Sensing

Sandeep Sharma; Neha Sharma

An ACO and Mobile Sink based Algorithm for Improvement of ML-MAC for Wsns using Compressive Sensing

Sandeep Sharma *

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Neha Sharma

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An ACO and Mobile Sink based Algorithm for Improvement of ML-MAC for Wsns using Compressive Sensing

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Abstract

WSN is becoming key subject of research in computational basic principle because of its great deal of applications. ACO( Ant Colony Optimization) constructs the redirecting or routing tree via a method by which, for every single circular or round, Base Station (BS) chooses the root node in addition to shows the following substitute for every node. In order to prevail over the actual constraints with the sooner work a new increased method proposed in this research work. The proposed method has the capacity to prevail over the constraints of ACO routing protocol using the principle with reactivity, mobile sink and also the compressive sensing technique. In this paper we measure the main parameters that affect the wsn that are network lifetime, packets dropped, throughput, end to end delay and remaining energy for proposed algorithm and simulation results have shown that the proposed algorithm is highly effective.

References

14 Cites in Article

Reference Format

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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

Sandeep Sharma, Neha Sharma. 2018. "An ACO and Mobile Sink based Algorithm for Improvement of ML-MAC for Wsns using Compressive Sensing". Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 18 (GJCST Volume 18 Issue E2).

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GJCST Volume 18 Issue E2

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

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Classification

GJCST-E Classification C.1.3

F.2.0

Submission ReceivedDecember 12, 2017
Peer Review Double Blind
Handling Editor
Accepted January 4, 2018
Published January 15, 2018

Version of record

v1.2

Issue date

May 2, 2018

Language

English

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Article Matrices

Total Score: 142

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Neha Sharma, Sandeep Sharma (PhD/Dr. count: 0)

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Publish Date: 2018 01, Mon

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