State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems

ZM Fadlullah, F Tang, B Mao, N Kato… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …

Machine learning in wireless sensor networks: Algorithms, strategies, and applications

MA Alsheikh, S Lin, D Niyato… - … Surveys & Tutorials, 2014 - ieeexplore.ieee.org
Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over
time. This dynamic behavior is either caused by external factors or initiated by the system …

Recursive principal component analysis-based data outlier detection and sensor data aggregation in IoT systems

T Yu, X Wang, A Shami - IEEE Internet of Things Journal, 2017 - ieeexplore.ieee.org
Internet of Things (IoT) is emerging as the underlying technology of our connected society,
which enables many advanced applications. In IoT-enabled applications, information of …

A survey of machine learning-based solutions to protect privacy in the Internet of Things

M Amiri-Zarandi, RA Dara, E Fraser - Computers & Security, 2020 - Elsevier
Abstract The Internet of things (IoT) aims to connect everything and everyone around the
world to provide diverse applications that improve quality of life. In this technology, the …

Large-scale indexing, discovery, and ranking for the Internet of Things (IoT)

Y Fathy, P Barnaghi, R Tafazolli - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
Network-enabled sensing and actuation devices are key enablers to connect real-world
objects to the cyber world. The Internet of Things (IoT) consists of the network-enabled …

Rate-distortion balanced data compression for wireless sensor networks

MA Alsheikh, S Lin, D Niyato, HP Tan - IEEE Sensors Journal, 2016 - ieeexplore.ieee.org
This paper presents a data compression algorithm with error bound guarantee for wireless
sensor networks (WSNs) using compressing neural networks. The proposed algorithm …

Context-aware intelligence in resource-constrained IoT nodes: Opportunities and challenges

B Chatterjee, N Cao, A Raychowdhury… - IEEE Design & …, 2019 - ieeexplore.ieee.org
Editor's note: This article provides an academic perspective of the problem, starting with a
survey of recent advances in intelligent sensing, computation, communication, and energy …

Privacy preservation using machine learning in the internet of things

S El-Gendy, MS Elsayed, A Jurcut, MA Azer - Mathematics, 2023 - mdpi.com
The internet of things (IoT) has prepared the way for a highly linked world, in which
everything is interconnected, and information exchange has become more easily accessible …

Data aggregation and principal component analysis in WSNs

A Morell, A Correa, M Barceló… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Data aggregation plays an important role in wireless sensor networks (WSNs) as far as it
reduces power consumption and boosts the scalability of the network, especially in …

An efficient data prediction model using hybrid Harris Hawk Optimization with random forest algorithm in wireless sensor network

S Ramalingam, K Baskaran - Journal of Intelligent & Fuzzy …, 2021 - content.iospress.com
Abstract Wireless Sensor Networks (WSNs) are consistently gathering environmental
weather data from sensor nodes on a random basis. The wireless sensor node sends the …