Recent Studies Utilizing Artificial Intelligence Techniques for Solving Data Collection, Aggregation and Dissemination Challenges in Wireless Sensor Networks: A Review

Abstract

The growing importance and widespread adoption of Wireless Sensor Network (WSN) technologies have helped the enhancement of smart environments in numerous sectors such as manufacturing, smart cities, transportation and Internet of Things by providing pervasive real-time applications. In this survey, we analyze the existing research trends with respect to Artificial Intelligence (AI) methods in WSN and the possible use of these methods for WSN enhancement. The main goal of data collection, aggregation and dissemination algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. In this paper, we highlight data collection, aggregation and dissemination challenges in WSN and present a comprehensive discussion on the recent studies that utilized various AI methods to meet specific objectives of WSN, during the span of 2010 to 2021. We compare and contrast different algorithms on the basis of optimization criteria, simulation/real deployment, centralized/distributed kind, mobility and performance parameters. We conclude with possible future research directions. This would guide the reader towards an understanding of up-to-date applications of AI methods with respect to data collection, aggregation and dissemination challenges in WSN. Then, we provide a general evaluation and comparison of different AI methods used in WSNs, which will be a guide for the research community in identifying the mostly adapted methods and the benefits of using various AI methods for solving the challenges related to WSNs. Finally, we conclude the paper stating the open research issues and new possibilities for future studies.

A review on recent studies utilizing artificial intelligence methods for solving routing challenges in wireless sensor networks

“…In this section, we follow the same research methodology presented by Osamy et al (2022a , 2022b) . As indicated in Fig.…”

“…The research in the area of WSN has become more active over the years, and a wide range of works has been executed to enhance WSN. To address the challenges of WSN, different surveys have been conducted based on different factors ( e.g ., Osamy et al (2022a) , Majid et al (2022) , Sridhar et al (2022) and Osamy et al (2022b) ). A survey for solving various WSN challenges using computational intelligence (CI) techniques is proposed by Kulkarni, Forster & Venayagamoorthy (2010) .…”

Recent Advances and Future Prospects of Using AI Solutions for Security, Fault Tolerance, and QoS Challenges in WSNs

“…In this section, we follow the same research methodology presented by [9,10]. As indicated in Figure 1, the research methodology used here is separated into four phases.…”

Survey: Self-Empowered Wireless Sensor Networks Security Taxonomy, Challenges, and Future Research Directions

“…Description and contribution of a paper Limitations Osamy et al [34] In [34], the author presents a comprehensive survey regarding the different challenges of WSN by particularly taking into account AIenabled techniques. In this paper, the authors considered a generalized structure of the network with different parameters such as QoS, security, interoperability, and routing protocols, etc.…”