{"title":"A cluster based energy efficient trust management mechanism for medical wireless sensor networks (MWSNs)","authors":"S. Hussain, I. Raza, Muhammad Mohsin Mehdi","doi":"10.1109/ICEEE2.2018.8391377","DOIUrl":null,"url":null,"abstract":"This paper presents an energy efficient trust management model for securing life-saving information with optimal power/energy consumption by sensor nodes. The proposed model is a cluster based three tier-architecture where first tier records the first-run configuration of the nodes. The second tier secures the data between the nodes, and the third tier ensures energy efficiency by calculating energy consumption at every level and rotates cluster head among the nodes. The difficult task of energy efficiency is achieved through a robust algorithm, which configures the nodes and train the network using a machine learning technique. The simulation results show smooth functioning of the network with less energy consumption. The proposed scheme performs better than Anonymous Authentication for Wireless Body Area Networks with Provable Security (AAWBAN) in terms of computational overhead, energy consumption, throughput and data drop rate.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"16 1","pages":"433-439"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE2.2018.8391377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper presents an energy efficient trust management model for securing life-saving information with optimal power/energy consumption by sensor nodes. The proposed model is a cluster based three tier-architecture where first tier records the first-run configuration of the nodes. The second tier secures the data between the nodes, and the third tier ensures energy efficiency by calculating energy consumption at every level and rotates cluster head among the nodes. The difficult task of energy efficiency is achieved through a robust algorithm, which configures the nodes and train the network using a machine learning technique. The simulation results show smooth functioning of the network with less energy consumption. The proposed scheme performs better than Anonymous Authentication for Wireless Body Area Networks with Provable Security (AAWBAN) in terms of computational overhead, energy consumption, throughput and data drop rate.