Research Article
Hybrid Energy Efficient and QoS Aware Algorithm to Prolong IoT Network Lifetime
@INPROCEEDINGS{10.1007/978-3-030-20615-4_6, author={N. Srinidhi and Jyothi Lakshmi and S. Dilip Kumar}, title={Hybrid Energy Efficient and QoS Aware Algorithm to Prolong IoT Network Lifetime}, proceedings={Ubiquitous Communications and Network Computing. Second EAI International Conference, Bangalore, India, February 8--10, 2019, Proceedings}, proceedings_a={UBICNET}, year={2019}, month={5}, keywords={Energy efficiency IoT Network lifetime QoS}, doi={10.1007/978-3-030-20615-4_6} }- N. Srinidhi
Jyothi Lakshmi
S. Dilip Kumar
Year: 2019
Hybrid Energy Efficient and QoS Aware Algorithm to Prolong IoT Network Lifetime
UBICNET
Springer
DOI: 10.1007/978-3-030-20615-4_6
Abstract
The Internet of Things (IoT) consists of large amount of energy compel devices which are prefigured to progress the effective competence of several industrial applications. It is very much essential to bring down the energy utilization of every device deployed in IoT network without compromising the quality of service (QoS). Here, the difficulty of providing the operation between the QoS allocation and the energy competence for the industrial IoT application is deliberate. To achieve this objective, the multi-objective optimization problem to accomplish the aim of estimating the outage performance and the network lifetime is devised. Subsequently, proposed Hybrid Energy Efficient and QoS Aware (HEEQA) algorithm is a combination of quantum particle swarm optimization (QPSO) along with improved non dominated sorting genetic algorithm (NGSA) to achieve energy balance among the devices is proposed and later the MAC layer parameters are tuned to reduce the further energy consumption of the devices. NSGA is applied to solve the problem of multi-objective optimization and the QPSO algorithm is used to gain the finest cooperative combination. The simulation outcome has put forward that the HEEQA algorithm has attained better operation balance between the energy competence and the QoS provisioning by minimizing the energy consumption, delay, transmission overhead and maximizing network lifetime, throughput and delivery ratio.
