Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal Journal of Robotics and Control (JRC)
Shreyas, J.
Unknown Affiliation
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Establishing Self-Healing and Seamless Connectivity among IoT Networks Using Kalman Filter Srinidhi, N. N.; Shreyas, J.; Naresh, E.
Journal of Robotics and Control (JRC) Vol 3, No 5 (2022): September
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i5.11622

Abstract

The Internet of Things (IoT) is the extension of Internet connectivity into physical devices and to everyday objects. Efficient mobility support in IoT provides seamless connectivity to mobile nodes having restrained resources in terms of energy, memory and link capacity. Existing routing algorithms have less reactivity to mobility. So, in this work, a new proactive mobility support algorithm based on the Kalman Filter has been proposed. Mobile nodes are provided with a seamless connectivity by minimizing the switching numbers between point of attachment which helps in reducing signaling overhead and power consumption. The handoff trigger scheme which makes use of mobility information in order to predict handoff event occurrence is used.  Mobile nodes new attachment points and its trajectory is predicted using the Kalman-Filter. Kalman-Filter is a predictor-estimator method used for movement prediction is used in this approach. Kalman Filtering is carried out in two steps: i) Predicting and ii) Updating. Each step is investigated and coded as a function with matrix input and output. Self-healing characteristics is being considered in the proposed algorithm to prevent the network from failing and to help in efficient routing of data. Proposed approach achieves high efficiency in terms of movement prediction, energy efficiency, handoff delay and fault tolerance when compared to existing approach.
Co-Authors Naresh, E. Srinidhi, N. N.