QoS-Attentive Learning-based Routing for Scalable WSNs

Singh, Onkar; Yadav, Mano; Yadav, Preeti; Rishiwal, Vinay; Jat, Dharm Singh; Thakur, Preeti

doi:10.1145/3484824.3484906

Cited by 2 publications

(2 citation statements)

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“…Some researchers propose to solve the problem directly which optimizes the network performance. The Computational Intelligence method to perform this feat includes DPSO (discrete particle swarm optimization) and GA (genetic algorithm) [204], chicken swarm-based genetic algorithm [205], Fuzzy System [206]- [209], CNN [210], ACO (Ant Colony Optimization) [211] and FFA (FireFly Algorithm) [212]. However, some researchers hope to use indirect methods to solve IoT WSN communication problems such as environmental modeling for wireless data transmission (radio propagation modeling) [213], [214].…”

Section: Communicationmentioning

confidence: 99%

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Survey Paper Artificial and Computational Intelligence in the Internet of Things and Wireless Sensor Network

Hakim

Septiyana

Suwarno

2022

Journal of Robotics and Control

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In this modern age, Internet of Things (IoT) and Wireless Sensor Network (WSN) as its derivatives have become one of the most popular and important technological advancements. In IoT, all things and services in the real world are digitalized and it continues to grow exponentially every year. This growth in number of IoT device in the end has created a tremendous amount of data and new data services such as big data systems. These new technologies can be managed to produce additional value to the existing business model. It also can provide a forecasting service and is capable to produce decision-making support using computational intelligence methods. In this survey paper, we provide detailed research activities concerning Computational Intelligence methods application in IoT WSN. To build a good understanding, in this paper we also present various challenges and issues for Computational Intelligence in IoT WSN. In the last presentation, we discuss the future direction of Computational Intelligence applications in IoT WSN such as Self-Organizing Network (dynamic network) concept.

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Section: Communicationmentioning

confidence: 99%

“…Communication PSO [217], DPSO [204], GA [204], Fuzzy [206]- [209], CNN [210] [215], ACO [211], FFA [212], ANFIS [105], Random Forest [216], Markov Chain [218].…”

Section: Functionality Computational Intelligencementioning

confidence: 99%