Modelling an Adaptive Cluster Head Positioning Based Map Reducing Strategy for Data Transmission in Medical IoT
Gameil S. H. Ali1, A. Nithya2
1Gameil S. H. Ali , Research Scholar, Department of Computer Science, Rathnavel Subramaniam College of Arts & Science, Coimbatore, (Tamil Nadu), India.
2Dr. A. Nithya, Associate Professor, Department of Computer Science, Rathnavel Subramaniam College of Arts & Science, Coimbatore, (Tamil Nadu), India.
Manuscript received on September 20, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 78-89 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1049109119/2019©BEIESP | DOI: 10.35940/ijeat.A1049.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Internet-of-things (IoT) based health monitoring systems have turned out to be an interesting topic to enhance quality of health care services. Moreover, there is no advanced IoT based continuous monitoring of glucose systems in real time and some prevailing techniques have numerous limitations. Here, a continuous and invasive glucose monitoring system for transmitting the condition of individuals simultaneously utilizing IoT is modelled and a general system architectural design for processing back end systems to provide body temperature, real time glucose and contextual data in human readable and graphical forms to the physicians or patients is anticipated. As well, a protocol designs for monitoring the continuous data from IoT devices in order to overcome the short comings of existing methods is provided. The design of an energy efficient routing algorithm is a hot topic in the research of IoT based Data mining. Cluster Heads (CH) form backbone of inter-cluster communication. The selection of reliable and efficient cluster head is another important issue. In most of the clustering process, failure of CH occurs due to energy depletion and if the distance between sink and CH is more, it ultimately leads to failure in transmission. During transmission, nodes may fail that means sudden energy loss or node gets out of coverage. Due to relaying high data traffic, some of nodes quickly exhaust their energy and increase the risk of node failure. As a baseline to node failure, data packet loss also occurs in a CH due to congestion and poor link quality. Hence, one of the most crucial feature in designing a protocol is to minimize energy consumption for betterment of network functioning. Here, a clustering routing protocol based on data mining techniques is applied for sensor nodes in medical field called Adaptive Positioning of Cluster Head based Map reducing (APCH-MR) is proposed. Routing table based code book is generated for privacy concern, in which the process of mapping and reducing the data for dissemination is performed. The simulated outcomes depicts that the total number of packets transmitted in round 500 is 11200, total number of dead nodes during round 500 is 58, and time consumed by nodes at 500 rounds is 0.3751s respectively. The proposed method shows better trade off in contrast to conventional techniques.
Keywords: IoT, Sensor data, Adaptive Positioning of Cluster Head based Map reducing protocol, Data traffic, Energy consumption.