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2. Edge Computing for IoT

Author

Hasan, Balqees Talal and Idrees, Ali Kadhum

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Over the past few years, The idea of edge computing has seen substantial expansion in both academic and industrial circles. This computing approach has garnered attention due to its integrating role in advancing various state-of-the-art technologies such as Internet of Things (IoT) , 5G, artificial intelligence, and augmented reality. In this chapter, we introduce computing paradigms for IoT, offering an overview of the current cutting-edge computing approaches that can be used with IoT. Furthermore, we go deeper into edge computing paradigms, specifically focusing on cloudlet and mobile edge computing. After that, we investigate the architecture of edge computing-based IoT, its advantages, and the technologies that make Edge computing-based IoT possible, including artificial intelligence and lightweight virtualization. Additionally, we review real-life case studies of how edge computing is applied in IoT-based Intelligent Systems, including areas like healthcare, manufacturing, agriculture, and transportation. Finally, we discuss current research obstacles and outline potential future directions for further investigation in this domain., Comment: 19 pages, 5 figures, Book Chapter In: Donta, P.K., Hazra, A., Lov\'en, L. (eds) Learning Techniques for the Internet of Things. Springer, Cham

Published
2024
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3. Federated Learning for Iot/Edge/Fog Computing Systems

Author

Hasan, Balqees Talal and Idrees, Ali Kadhum

Subjects
Computer Science - Networking and Internet Architecture
Abstract

With the help of a new architecture called Edge/Fog (E/F) computing, cloud computing services can now be extended nearer to data generator devices. E/F computing in combination with Deep Learning (DL) is a promisedtechnique that is vastly applied in numerous fields. To train their models, data producers in conventional DL architectures with E/F computing enable them to repeatedly transmit and communicate data with third-party servers, like Edge/Fog or cloud servers. Due to the extensive bandwidth needs, legal issues, and privacy risks, this architecture is frequently impractical. Through a centralized server, the models can be co-trained by FL through distributed clients, including cars, hospitals, and mobile phones, while preserving data localization. As it facilitates group learning and model optimization, FL can therefore be seen as a motivating element in the E/F computing paradigm. Although FL applications in E/F computing environments have been considered in previous studies, FL execution and hurdles in the E/F computing framework have not been thoroughly covered. In order to identify advanced solutions, this chapter will provide a review of the application of FL in E/F computing systems. We think that by doing this chapter, researchers will learn more about how E/F computing and FL enable related concepts and technologies. Some case studies about the implementation of federated learning in E/F computing are being investigated. The open issues and future research directions are introduced., Comment: 21 pages, 4 figures, Book chapter

Published
2024

7. EDiTOK: Energy-Efficient Distributed Transmission Optimization-Based Kalman–Zlib Approaches for Monitoring Smart Farming Irrigation in Internet of Things Networks

Author

Hasan, Zahraa Yaseen, Idrees, Ali Kadhum, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Sharma, Harish, editor, Shrivastava, Vivek, editor, Tripathi, Ashish Kumar, editor, and Wang, Lipo, editor

Published
2024
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20. Distributed video transmission reduction approach for energy saving in WMSNs.

Author

Abbood, Iman Kadhum and Idrees, Ali Kadhum

Subjects
*WIRELESS sensor networks, *PRINCIPAL components analysis, *FEATURE extraction, *ENERGY consumption, *DATA integrity
Abstract

Summary: Wireless Multimedia Sensor Networks (WMSNs) are composed of a large number of sensor nodes that are distributed in a region to collect and transmit data. Video transmission is one of the most important applications of WMSNs because it can provide critical information about monitored areas. WMSNs face challenges related to energy consumption, bandwidth usage, and network congestion related to huge amounts of data collected by sensors. To tackle this problem, this paper proposes the Distributed Video Transmission Reduction Approach for Energy Saving in WMSN (DiViTRA). The method involves two phases: sensing and transmission phases. DiViTRA achieves frame rate adaptation to reduce the number of captured video frames and save energy during the sensing phase. In the transmission phase, three effective techniques, ORB (Oriented FAST and Rotated BRIEF), Brute‐Force (BF) Matcher, and Grid‐based Motion Statistics (GMS) are applied to decide whether to transmit the current captured frame or remove it and adjust the frame capturing rate of the video sensor accordingly. In the case of frame transmission, the DiViTRA approach compresses the frame using two data reduction approaches: PCA (Principal Component Analysis) and Huffman encoding. Through simulations, DiViTRA demonstrates a 12% reduction in energy consumption, and 71% is a ratio of reduction in sent frames while preserving stream quality. The approach has been validated in scenarios involving critical events, showcasing its efficacy in maintaining data integrity during transmission. [ABSTRACT FROM AUTHOR]

Published
2024
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21. ETOP: Energy-Efficient Transmission Optimization Protocol in Sensor Networks of IoT

Author

Idrees, Ali Kadhum, Al-Mamory, Safaa O., Idrees, Sara Kadhum, Couturier, Raphael, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Al-Bakry, Abbas M., editor, Al-Mamory, Safaa O., editor, Sahib, Mouayad A., editor, George, Loay E., editor, Aldhaibani, Jaafar A., editor, Hasan, Haitham S., editor, and Oreku, George S., editor

Published
2021
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22. Energy-Saving Adaptive Sampling Mechanism for Patient Health Monitoring Based IoT Networks

Author

Alhussein, Duaa Abd, Idrees, Ali Kadhum, Harb, Hassan, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Al-Bakry, Abbas M., editor, Al-Mamory, Safaa O., editor, Sahib, Mouayad A., editor, George, Loay E., editor, Aldhaibani, Jaafar A., editor, Hasan, Haitham S., editor, and Oreku, George S., editor

Published
2021
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23. Distributed DBSCAN Protocol for Energy Saving in IoT Networks

Author

Hameed, Mazin Kadhum, Idrees, Ali Kadhum, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Bindhu, V., editor, Tavares, João Manuel R. S., editor, Boulogeorgos, Alexandros-Apostolos A., editor, and Vuppalapati, Chandrasekar, editor

Published
2021
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24. Cuckoo Scheduling Algorithm for Lifetime Optimization in Sensor Networks of IoT

Author

Hameed, Mazin Kadhum, Idrees, Ali Kadhum, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Suma, V., editor, Chen, Joy Iong-Zong, editor, Baig, Zubair, editor, and Wang, Haoxiang, editor

Published
2021
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26. Energy-Efficient Particle Swarm Optimization for Lifetime Coverage Prolongation in Wireless Sensor Networks

Author

Idrees, Ali Kadhum, Al-Mamory, Safaa O., Couturier, Raphael, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Al-Bakry, Abbas M., editor, Al-Mamory, Safaa O., editor, Sahib, Mouayad A., editor, Hasan, Haitham S., editor, Oreku, George S., editor, Nayl, Thaker M., editor, and Al-Dhaibani, Jaafar A., editor

Published
2020
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31. A Comprehensive Review for RPL Routing Protocol in Low Power and Lossy Networks

Author

Witwit, Athraa J. H., Idrees, Ali Kadhum, Barbosa, Simone Diniz Junqueira, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Al-mamory, Safaa O., editor, Alwan, Jwan K., editor, and Hussein, Ali D., editor

Published
2018
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32. Data Transmission Protocol for Reducing the Energy Consumption in Wireless Sensor Networks

Author

Alhussaini, Rafal, Idrees, Ali Kadhum, Salman, Mahdi Abed, Barbosa, Simone Diniz Junqueira, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Al-mamory, Safaa O., editor, Alwan, Jwan K., editor, and Hussein, Ali D., editor

Published
2018
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44. DaTOS: Data Transmission Optimization Scheme in Tactile Internet-based Fog Computing Applications

Author

Idrees, Ali Kadhum, Ali-Yahiya, Tara, Idrees, Sara, Couturier, Raphael, University of Babylon, Réseaux & Optimisation Combinatoire et Stochastique (ROCS), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Science des Données (SDD), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Franche-Comté Électronique Mécanique, Thermique et Optique - Sciences et Technologies (UMR 6174) (FEMTO-ST), Université de Technologie de Belfort-Montbeliard (UTBM)-Ecole Nationale Supérieure de Mécanique et des Microtechniques (ENSMM)-Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), and Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)

Subjects
[INFO]Computer Science [cs]
Abstract

In the Tactile Internet-based fog computing architecture, the sensor devices represent the basic elements for sensing the surrounding environment. They gather a large amount of data due to their use in various real-world Tactile Internet applications. The huge amount of transmitted data from sensor devices to the fog gateway then to the cloud would lead to high data traffic over the network, increased consumed energy, and increased delay to provide the decision at the Fog gateway. These challenges represent a hurdle in the Tactile Internet-based fog system. This paper suggests a Data Transmission Optimization Scheme (DaTOS) in Tactile Internet-based Fog Computing Applications. The protocol works on two-level devices in the Tactile Internet-based fog computing architecture: sensor devices and fog gateway. The DaTOS implements a Lightweight Redundant Data Removing (LiReDaR) Algorithm at the sensor devices level to lower the gathered data before sending them to the fog gateway. In fog gateway, it executes a Data Set Redundancy Elimination (DaSeRE) approach to discard the repetitive data set resulting from the spatial correlation among the data readings sets of sensor nodes. To evaluate the performance of the DaTOS, it was compared to its counterpart methods in the literature like ATP, PFF and Harb. Simulation results indicate that DaTOS outperforms these methods in terms of transmitted data, energy consumption, and data accuracy.

Published
2022

49. Energy-efficient scheduling based clustering approach for wireless sensor networks of IoT.

Author

Jawad, Lina Waleed and Idrees, Ali Kadhum

Subjects
*WIRELESS sensor networks, *INTERNET of things, *SENSOR networks, *SCHEDULING, *ENERGY consumption
Abstract

Several Internet of Things (IoT) applications employ Wireless Sensor Networks (WSNs) in monitoring such as health-care, environment, transportation, agriculture, etc. These applications will produce a significant amount of data, which will pose a big challenge in the Big Data age. Scheduling is one of the energy-efficient mechanisms that can be used to deal with such a large volume of data. In this paper, an Energy-efficient Scheduling based Clustering Approach (ESCA) for Wireless Sensor Networks (WSNs) of IoT is proposed. ESCA works into rounds. each round composed of two periods. The first period consists of three steps: data collection, compressed transmission, and scheduling-based clustering. The scheduling algorithm plans the schedule for the WSN in the first period of each round for all the periods in the round. The second period consists of collection and compressed transmission. The active sensor nodes will only collect and transmit compressed data to the sink in the second period of each round. The simulation results based on real sensed data of the sensor network show that the proposed ESCA technique can reduce transmitted data up to 78.65% and decrease the energy consumption up to 98.13% in comparison with another method. [ABSTRACT FROM AUTHOR]

Published
2022
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50. Energy-efficient fog computing-enabled data transmission protocol in tactile internet-based applications

Author

Idrees, Ali Kadhum, Ali-Yahiya, Tara, Idrees, Sara Kadhum, Couturier, Raphael, and Femto-st, DISC

Subjects
[INFO.INFO-ET] Computer Science [cs]/Emerging Technologies [cs.ET], [INFO.INFO-SE] Computer Science [cs]/Software Engineering [cs.SE], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-IU] Computer Science [cs]/Ubiquitous Computing, [INFO.INFO-MA] Computer Science [cs]/Multiagent Systems [cs.MA], [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
Abstract

Sensor nodes are one of the basic elements in the Tactile Internetbased fog computing architecture. They provide a huge amount of data to the network due to the widespread real-world applications that use these types of wireless devices. This huge number of data, transmitted by the sensor devices to the fog gateway and then to the cloud, leads to high communication costs, increased power consumption, and high latency at the fog gateway. These challenges would be considered as a hurdle in the Tactile Internetbased fog system. To tackle these challenges, this paper proposes an Energy-efficient Fo g Co mputing-enabled Da ta Transmission (EFoCoD) protocol in Tactile Internet-based Applications. The protocol works on sensor devices level in the Tactile Internet-based fog computing architecture. EFoCoD protocol executes a Lightweight Data Redundancy Elimination (LiDaRE) Algorithm at the sensor level to reduce the collected data before transferring them to the smart fog gateway. To study the performance of the EFoCoD, it was compared to its counterpart protocols in the literature just like ATP and PFF. Simulation results show that EFoCoD outperforms these protocols in terms of energy consumption, transmitted data, and data accuracy.

Published
2022

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