Cost Efficient Scheduling Using Smart Contract Cognizant Ethereum for IoMT

G. Ravikumar, K. Venkatachalam, Mehedi Masud, Mohamed Abouhawwash*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Recently internet of medical things (IoMT) act as a smart doctor using sensor wearable’s device in human body. This smart doctor device senses neces-sary medical data from human and transfer via network immediately to physician. It is important to transfer sensitive data very securely. Blockchain becomes trend-ing technology to provide high security to both end users in the network. Tradi-tionally security structure is relying on cryptographic techniques which is very expensive and takes more time in securely transmitting data. To overcome this issue, this paper builds a cost effective, blockchain with IoMT using fog-cloud computing. The aim of research is to provide cost effective healthcare services in the present system. This study develops an IoMT systems using fusion of scheduling techniques in blockchain. We propose a Smart Contract with Function Based Cost Efficient Task Scheduling (FTS-SCON) algorithm in blockchain fra-mework. The proposed algorithm uses functions to schedule the task in the block-chain which is cost effective. With the help of cryptography based Blockchain schemes with smart contracts enables consistency and validation of data with symmetric cryptography. Simulation results shows the proposed outperform all existing elements regarding data security, validation by 10%, and cost of application execution by 30% in IoMT.

Original languageEnglish
Pages (from-to)865-877
Number of pages13
JournalIntelligent Automation and Soft Computing
Volume33
Issue number2
DOIs
StatePublished - 2022
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2022, Tech Science Press. All rights reserved.

Keywords

  • Blockchain
  • Health care sensor
  • IOMT
  • Security
  • Smart contract
  • Task scheduling algorithm

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Artificial Intelligence

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