Next Article in Journal
Digital Generator Control Unit Design for a Variable Frequency Synchronous Generator in MEA
Previous Article in Journal
Circuit Breaker Rate-of-Rise Recovery Voltage in Ultra-High Voltage Lines with Hybrid Reactive Power Compensation
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Energies 2018, 11(1), 97; doi:10.3390/en11010097

The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia
*
Author to whom correspondence should be addressed.
Received: 7 November 2017 / Revised: 29 December 2017 / Accepted: 31 December 2017 / Published: 2 January 2018
View Full-Text   |   Download PDF [9472 KB, uploaded 8 January 2018]   |  

Abstract

Prior studies in Wireless Sensor Network (WSN) optimization mostly concentrate on maximizing network coverage and minimizing network energy consumption. However, there are other factors that could affect the WSN Quality of Service (QoS). In this paper, four objective functions that affect WSN QoS, namely end-to-end delay, end-to-end latency, network throughput and energy efficiency are studied. Optimal value of packet payload size that is able to minimize the end-to-end delay and end-to-end latency, while also maximizing the network throughput and energy efficiency is sought. To do this, a smart grid application case study together with a WSN QoS model is used to find the optimal value of the packet payload size. Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-the-art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. Different packet payload sizes are supplied to the algorithms and their optimal value is derived. From the experiments, the knee point and the intersection point of all the obtained Pareto fronts for all the algorithms show that the optimal packet payload size that manages the trade-offs between the four objective functions is equal to 45 bytes. The results also show that the performance of our proposed MOSFP method is highly competitive and found to have the best average value compared to the other three algorithms. Furthermore, the overall performance of MOSFP on four objective functions outperformed OMOPSO, NSGA-II and SPEA2 by 3%, 6% and 51%, respectively. View Full-Text
Keywords: network modeling; smart grid; multi-objective optimization; quality of services (QoS); optimality network modeling; smart grid; multi-objective optimization; quality of services (QoS); optimality
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Shehadeh, H.A.; Idna Idris, M.Y.; Ahmedy, I.; Ramli, R.; Mohamed Noor, N. The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications. Energies 2018, 11, 97.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top