A bio-inspired adaptive model for search and selection in the Internet of Things environment

Abstract

The Internet of Things (IoT) is a paradigm that can connect an enormous number of intelligent objects, share large amounts of data, and produce new services. However, it is a challenge to select the proper sensors for a given request due to the number of devices in use, the available resources, the restrictions on resource utilization, the nature of IoT networks, and the number of similar services. Previous studies have suggested how to best address this challenge, but suffer from low accuracy and high execution times. We propose a new distributed model to efficiently deal with heterogeneous sensors and select accurate ones in a dynamic IoT environment. The model’s server uses and manages multiple gateways to respond to the request requirements. First, sensors were grouped into three semantic categories and several semantic sensor network types in order to define the space of interest. Second, each type’s sensors were clustered using the Whale-based Sensor Clustering (WhaleCLUST) algorithm according to the context properties. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was improved to search and select the most adequate sensor matching users’ requirements. Experimental results from real data sets demonstrate that our proposal outperforms state-of-the-art approaches in terms of accuracy (96%), execution time, quality of clustering, and scalability of clustering.

Case Studies with the Contiki-NG Simulator to Design Strategies for Sensors’ Communication Optimization in an IoT-Fog Ecosystem

“…The TOPSIS algorithm can be successfully applied for decision-making in different study areas, including complex network analysis [ 44 , 45 ], Internet of Things [ 46 , 47 , 48 ], neural networks [ 49 , 50 , 51 ], reverse logistics [ 52 , 53 ], and sensor selection [ 54 , 55 , 56 ]. According to [ 57 ], the mathematical formulation of the TOPSIS algorithm is composed of the steps: The decision matrix D is represented as The elements of the ordered decision matrix are calculated according to Equation (4).…”

Bio-Inspired Internet of Things: Current Status, Benefits, Challenges, and Future Directions

“… Power and energy requirements Many IoT devices are small, battery-powered devices designed to operate for extended periods without human intervention. However, maintaining constant connectivity, data transmission, and processing can drain device batteries quickly [10][11][12][13]. Thus, energy efficiency becomes a crucial factor, especially for IoT deployments that involve a massive number of devices or remote locations (e.g., in agricultural lands, mines etc.)…”

“…Day by day, IoT solutions are becoming more closely integrated into our daily lives, and such IoT solutions are being introduced to the market at a rapid rate. In general, the IoT has the capability to connect digital devices/objects all around the world and allow them to communicate with each other, creating a larger ubiquitous network [ 10 , 11 , 12 ].…”

“…IoT generates vast amounts of data from multiple sources and sensors, where effectively managing, storing, analyzing, and deriving actionable insights from these data can be a daunting task [ 10 , 11 , 12 , 13 ]. Thus, organizations need robust data management strategies, including data storage, processing, and analytics capabilities, to make sense of the information generated by IoT devices.…”

Dynamic coefficient symmetric polynomial-based secure key management scheme for Internet of Things (IoT) networks

“…In the network architecture of the Internet of Things (IoT), some new distributed models ( Bouarourou, Boulaalam & Nfaoui, 2021 ; Labib et al, 2021 ) and multi-hop clustering scheme ( Muthukkumar et al, 2022 ) for heterogeneous wireless sensor networks (WSNs) to efficiently deal with heterogeneous sensors in a dynamic IoT environment, it greatly increases the service life and communication efficiency of node networkst. In the security architecture of the IoT, ( Alansari et al, 2023 ) presents a novel lightweight system for anomaly detection of grayhole, blackhole, and selective forwarding attacks, and a survey ( Osamy et al, 2022 ) reviews and analyzes the research trends related to the utilized artificial intelligence (AI) methods for IoT and the potential enhancement of IoT.…”