Abstract
Wireless (smart) sensor networks (WSNs) comprise a myriad of embedded wireless smart sensors. They play a cardinal role in the functioning of many applications, such as the Internet of Things, smart grids, smart production systems, and smart homes, which ultimately render them paramount instruments in the modern age. Recent advances in WSNs have resulted in the rapid development of sensors. However, WSNs will only able to achieve better execution efficiencies if their energy consumption - owing to limited battery life and difficulty of recharging - can be better controlled. Moreover, signal transmission quality determines WSN performance. Hence, two main concerns - energy consumption and signal transmission quality - should be addressed to improve the performance of WSNs. Thus, a new bi-objective simplified swarm optimization algorithm (bSSO) is proposed by employing the concepts of simple routing, SSO, and crowd distance. The performance and applicability of the proposed bSSO using eight different parameter settings are demonstrated through an experiment involving ten WSN benchmarks ranging from 100 to 1000 sensors. The proposed algorithm is then compared with NSGA-II, which is an algorithm widely used to solve multi-objective problems. The results show that the proposed bSSO can successfully achieve the aim of this work.
Highlights
Wireless sensor networks (WSN) comprise devices embedded with wireless smart sensors and play a crucial role in the networking of many objects in real-world and daily life applications
A nascent bi-objective Wireless (smart) sensor networks (WSNs) problem focusing on energy consumption and service quality in terms of routing reliability has been propounded in this study to find non-dominated routings for the purpose of ameliorating the service quality issues of WSNs
Both the objectives considered are some of the major concerns for users of the service provided by WSNs
Summary
Wireless (smart) sensor networks (WSN) comprise devices embedded with wireless smart sensors and play a crucial role in the networking of many objects in real-world and daily life applications. Derived from real-life applications, this context sets up a bi-objective problem to find one routing from all available routings in a WSN to minimize energy consumption and increase service quality, which depends on the system’s reliability. BSSO is evaluated in terms of solution quality; these are the major contributions of the proposed bSSO This problem-solving approach is based on simplified swarm optimization (SSO), which was originally developed by Yeh [24] and is a technique for finding and ordering nondominated solutions. The novelty of the proposed bSSO in this study complements and strengthens the problem that reported approaches in the literature lack the ability to find an optimal routing path based on more than one objective [3], [17]–[23].
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
