English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Wireless (smart) sensor networks (WSNs), networks made up of embedded wireless smart sensors, are an important paradigm with a wide range of applications, including the internet of things (IoT), smart grids, smart production systems, smart buildings and many others. WSNs achieve better execution efficiency if their energy consumption can be better controlled, because their component sensors are either difficult or impossible to recharge, and have a finite battery life. In addition, transmission cost must be minimized, and signal transmission quantity must be maximized to improve WSN performance. Thus, a multi-objective involving energy consumption, cost and signal transmission quantity in WSNs needs to be studied. Energy consumption, cost and signal transmission quantity usually have uncertain characteristics, and can often be represented by fuzzy numbers. Therefore, this work suggests a fuzzy simplified swarm optimization algorithm (fSSO) to resolve the multi-objective optimization problem consisting of energy consumption, cost and signal transmission quantity of the transmission process in WSNs under uncertainty. Finally, an experiment of ten benchmarks from smaller to larger scale WSNs is conducted to demonstrate the effectiveness and efficiency of the proposed fSSO algorithm.

Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm