Hybrid energy-efficient and QoS-aware algorithm for intelligent transportation system in IoT

Srinidhi, N. N.; Sunitha, G.P.; Raghavendra, S.; Kumar, Sharad; Chang, Victor

doi:10.1504/ijguc.2020.110897

Cited by 4 publications

(1 citation statement)

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“…Evolution of next generation technologies has resulted in a huge scope for Internet of Things (IoT) and its application across a myriad range of domains [1][2][3]. The IoT establishes a communication network among the various physical devices which are integrated with actuators and sensors and the cyber world constrained under some communication protocol.…”

Section: Introductionmentioning

confidence: 99%

Establishing Self-Healing and Seamless Connectivity among IoT Networks Using Kalman Filter

Srinidhi

Shreyas²,

Naresh

2022

Journal of Robotics and Control

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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.

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Section: Introductionmentioning

confidence: 99%