Present years have realised the expansion of computing settings for internet of things (IoTs) amenities, which switch huge amounts of data using several devices that are continuously associated to networks. Since the information communication and amenities arise on an assortment of devices, such as household appliances, embedded devices, and sensor nodes, the dynamic provision of IoT cloud benefactors' necessities are progressively important at this juncture. This work is based on IoT for home automation which is a collection of sensors controlled by microcontroller. Through microcontroller, we direct data to the cloud server for sharing the sensor data to the cloud server and accessed through mobile app. We used cloud server as Ubidots for monitoring the sensors like gas, flame, sound, and temperature. The main inspiration of this work is to alert communication through smartphone and e-mail on any abnormal constraint. This work is intended to decrease data transmit, decrease time, cost operative and easy to use. Copyright © 2017 Inderscience Enterprises Ltd.

Viswanathan P

School of Computer Science and Engineering

Chennai Campus

Sanjeevi P

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

International Journal of Critical Computer-Based Systems

The Internet of things concept is based on data from sensor devices. The conservation of sensor data in the cloud has become a well-known challenge with respect to the sensor-cloud network. There is an enormous quantity of sensed data, including missed and unimportant data due to unavailability of the node, low link quality, node deficiency or latency in path communication. In order to address this issue, it is necessary to develop an accurate sensor selection approach, precisely for the purpose of reducing the quantity of unimportant data (missed and noisy data). In this paper, we formulate an innovative and efficient bi-level node energy assessment algorithm, named BNSA, which uses a belief propagation protocol for optimal energy-efficient sensor selection. On the first level, the equilibrium transmission energy function is applied to all nodes to evaluate the transmission rate and link quality, together with the residual energy of the node, to predict the energy consumption, providing an accurate prediction of the energy level of the nodes. On the second level, optimal nodes are selected based on the prediction of the energy level. Belief propagation draws inferences for revealing missed sensor data. This approach improves the lifespan of the network and reduces the energy utilization rate by more than 32.3% with a delay rate of 77%. This is reflected in an enhancement of the quality of service with 85% of the energy consumption over the network, compared with existing models. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Wireless Personal Communications

Equilibrium Transmission Bi-level Energy Efficient Node Selection Approach for Internet of Things

The cloud data center is accommodated with many servers for cloud-based services which cause more consumption of energy and menace cost factors in computing tasks. Many existing scheduling techniques hinge on allocating task where scheduling algorithm is not based on assigning tasks through urgent and non-urgent task scheduling using dynamic voltage frequency scaling (DVFS) controller. In demand to reduce energy consumption and to maintain the quality of services, this paper proposes non-urgent and urgent task scheduling (NUTS) algorithm using DVFS, to restraint and scheduling of task in the more efficient way for minimizing the power consumption of the IT equipment. To increase the energy efficiency, we proposed scheduling queue and non-completed task queue for scheduling urgent, non-urgent and non-completed tasks to ally utilization of resources efficiently and to decrease the consumption of energy in the data center. In this paper, we compared proposed algorithm with two existing standard scheduling algorithms. The experimental results boast that NUTS algorithm performs better than the existing algorithms and can centrist energy efficiency in cloud data center. © 2017, Springer-Verlag Wien.

Journal	International Journal of Critical Computer-Based Systems
Publisher	Inderscience Publishers
ISSN	1757-8779
Open Access	No