Log in

Relevant bibliographies by topics / Intelligent Edge Networks / Journal articles

To see the other types of publications on this topic, follow the link: Intelligent Edge Networks.

Journal articles on the topic 'Intelligent Edge Networks'

Author: Grafiati

Published: 25 May 2024

Last updated: 19 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Intelligent Edge Networks.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Li, Qian, Heng Liu, and Xiaoming Zhao. "IoT Networks-Aided Perception Vocal Music Singing Learning System and Piano Teaching with Edge Computing." Mobile Information Systems 2023 (April 28, 2023): 1–9. http://dx.doi.org/10.1155/2023/2074890.

Full text

Abstract:

The research on Internet of Things (IoT) network and edge computing has been a research hotspot in both industry and academia in recent years, especially for the ambient intelligence and massive communication. As a typical form of IoT network and edge computing, the intelligent perception vocal music singing learning system has attracted the attention of researchers in education and academia. Piano teaching is an important course for music majors in higher education. Strengthening piano teaching can cultivate outstanding piano talents for the country and promote the development of music art. T

APA, Harvard, Vancouver, ISO, and other styles

2

Zhang, Jiaxin, Xing Zhang, Peng Wang, Liangjingrong Liu, and Yuanjun Wang. "Double-edge intelligent integrated satellite terrestrial networks." China Communications 17, no. 9 (2020): 128–46. http://dx.doi.org/10.23919/jcc.2020.09.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Zeydan, Engin, Josep Mangues-Bafalluy, and Yekta Turk. "Intelligent Service Orchestration in Edge Cloud Networks." IEEE Network 35, no. 6 (2021): 126–32. http://dx.doi.org/10.1109/mnet.101.2100214.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Engin, Zeydan, Mangues Josep, and Turk Yekta. "Intelligent Service Orchestration in Edge Cloud Networks." IEEE Netw. 35, no. 6 (2021): 126–32. https://doi.org/10.1109/MNET.101.2100214.

Full text

Abstract:

The surge in data traffic is challenging for network infrastructure owners coping with stringent service requirements (e.g., high bandwidth, ultralow latency) as well as shrinking per-gigabyte revenues. Network softwarization and edge computing are powerful candidates to mitigate these issues. In parallel, there is an increasing demand for network virtualization and container-based services. In this study, we investigate the management of software defined networking (SDN)-based transport network and edge cloud service orchestration. To this end, we use a machine learning (ML)-based design to m

APA, Harvard, Vancouver, ISO, and other styles

5

Musa, Salahadin Seid, Marco Zennaro, Mulugeta Libsie, and Ermanno Pietrosemoli. "Convergence of Information-Centric Networks and Edge Intelligence for IoV: Challenges and Future Directions." Future Internet 14, no. 7 (2022): 192. http://dx.doi.org/10.3390/fi14070192.

Full text

Abstract:

Recently the Internet of Vehicles (IoV) has become a promising research area in the field of the Internet of Things (IoT), which enables vehicles to communicate and exchange real-time information with each other, as well as with infrastructure, people, and other sensors and actuators through various communication interfaces. The realization of IoV networks faces various communication and networking challenges to meet stringent requirements of low latency, dynamic topology, high data-rate connectivity, resource allocation, multiple access, and QoS. Advances in information-centric networks (ICN)

APA, Harvard, Vancouver, ISO, and other styles

6

Mani Sai Kamal Darla. "Edge AI: Revolutionizing IoT Data Processing." Journal of Computer Science and Technology Studies 7, no. 7 (2025): 258–64. https://doi.org/10.32996/jcsts.2025.7.7.26.

Full text

Abstract:

Edge AI represents a transformative computational paradigm that embeds artificial intelligence algorithms directly within Internet of effects bias, barring reliance on remote pall structure for real- time decision- making processes. The distributed intelligence frame unnaturally alters traditional IoT infrastructures by incorporating cognitive capabilities at network boundaries, enabling independent data processing and immediate response generation at the point of data origin. Edge AI infrastructures address critical challenges in wireless hindrance networks through deep learning optimization

APA, Harvard, Vancouver, ISO, and other styles

7

Rahmadika, Sandi, Muhammad Firdaus, Seolah Jang, and Kyung-Hyune Rhee. "Blockchain-Enabled 5G Edge Networks and Beyond: An Intelligent Cross-Silo Federated Learning Approach." Security and Communication Networks 2021 (March 27, 2021): 1–14. http://dx.doi.org/10.1155/2021/5550153.

Full text

Abstract:

Edge networks (ENs) in 5G have the capability to protect traffic between edge entry points (edge-to-edge), enabling the design of various flexible and customizable applications. The advantage of edge networks is their pioneering integration of other prominent technologies such as blockchain and federated learning (FL) to produce better services on wireless networks. In this paper, we propose an intelligent system integrating blockchain technologies, 5G ENs, and FL to create an efficient and secure framework for transactions. FL enables user equipment (UE) to train the artificial intelligence m

APA, Harvard, Vancouver, ISO, and other styles

8

Guo, Hongzhi, Jiajia Liu, Ju Ren, and Yanning Zhang. "Intelligent Task Offloading in Vehicular Edge Computing Networks." IEEE Wireless Communications 27, no. 4 (2020): 126–32. http://dx.doi.org/10.1109/mwc.001.1900489.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Yang, Yang, Rui Lyu, Zhipeng Gao, Lanlan Rui, and Yu Yan. "Semisupervised Graph Neural Networks for Traffic Classification in Edge Networks." Discrete Dynamics in Nature and Society 2023 (July 3, 2023): 1–13. http://dx.doi.org/10.1155/2023/2879563.

Full text

Abstract:

Edge networking brings computation and data storage as close to the point of request as possible. Various intelligent devices are connected to the edge nodes where traffic packets flow. Traffic classification tasks are thought to be a keystone for network management; researchers can analyze packets captured to understand the traffic as it hits their network. However, the existing traffic classification framework needs to conduct a unified analysis, which leads to the huge bandwidth resources required in the process of transferring all captured packet files to train a global classifier. In this

APA, Harvard, Vancouver, ISO, and other styles

10

Alam, Tanweer, Baha Rababah, Arshad Ali, and Shamimul Qamar. "Distributed Intelligence at the Edge on IoT Networks." Annals of Emerging Technologies in Computing 4, no. 5 (2020): 1–18. http://dx.doi.org/10.33166/aetic.2020.05.001.

Full text

Abstract:

The Internet of Things (IoT) has revolutionized innovation to collect and store the information received from physical objects or sensors. The smart devices are linked to a repository that stores intelligent information executed by sensors on IoT-based smart objects. Now, the IoT is shifted from knowledge-based technologies to operational-based technologies. The IoT integrates sensors, smart devices, and a smart grid of implementations to deliver smart strategies. Nowadays, the IoT has been pondered to be an essential technology. The transmission of information to or from the cloud has recentl

APA, Harvard, Vancouver, ISO, and other styles

11

Liu, Jun, Yuwei Zhang, Jing Wang, et al. "Intelligent Bi-directional Relaying Communication for Edge Intelligence based Industrial IoT Networks." EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 9, no. 32 (2022): e4. http://dx.doi.org/10.4108/eetinis.v9i32.1909.

Full text

Abstract:

Within this specific record, our group study the two-way interact body (TWRN) that has a number of amplify-and-forward (AF) relays. In that, the best one is actually really got to help the info communication among sources. A interact option is actually really according to the obsolete channel problem information (CSI) in addition to our group analyze its own very personal effect on the system effectiveness in the Rayleigh fading atmospheres. Especially, we extremely preliminary acquire a restricted decreased connected for the outage opportunity and afterward current an asymptotic assessment fo

APA, Harvard, Vancouver, ISO, and other styles

12

Lalapura, Varsha S., J. Amudha, and Hariramn Selvamuruga Satheesh. "Recurrent Neural Networks for Edge Intelligence." ACM Computing Surveys 54, no. 4 (2021): 1–38. http://dx.doi.org/10.1145/3448974.

Full text

Abstract:

Recurrent Neural Networks are ubiquitous and pervasive in many artificial intelligence applications such as speech recognition, predictive healthcare, creative art, and so on. Although they provide accurate superior solutions, they pose a massive challenge “training havoc.” Current expansion of IoT demands intelligent models to be deployed at the edge. This is precisely to handle increasing model sizes and complex network architectures. Design efforts to meet these for greater performance have had inverse effects on portability on edge devices with real-time constraints of memory, latency, and

APA, Harvard, Vancouver, ISO, and other styles

13

Fernando, Xavier, and George Lăzăroiu. "Energy-Efficient Industrial Internet of Things in Green 6G Networks." Applied Sciences 14, no. 18 (2024): 8558. http://dx.doi.org/10.3390/app14188558.

Full text

Abstract:

The research problem of this systematic review was whether green 6G networks can integrate energy-efficient Industrial Internet of Things (IIoT) in terms of distributed artificial intelligence, green 6G pervasive edge computing communication networks and big-data-based intelligent decision algorithms. We show that sensor data fusion can be carried out in energy-efficient IoT smart industrial urban environments by cooperative perception and inference tasks. Our analyses debate on 6G wireless communication, vehicular IoT intelligent and autonomous networks, and energy-efficient algorithm and gre

APA, Harvard, Vancouver, ISO, and other styles

14

Han, Yibo, Weiwei Zhang, and Zheng Zhang. "Security Analysis of Intelligent System Based on Edge Computing." Security and Communication Networks 2021 (August 16, 2021): 1–10. http://dx.doi.org/10.1155/2021/1224333.

Full text

Abstract:

At present, artificial intelligence technology is widely used in society, and various intelligent systems emerge as the times require. Due to the uniqueness of biometrics, most intelligent systems use biometric-based recognition technology, among which face recognition is the most widely used. To improve the security of intelligent system, this paper proposes a face authentication system based on edge computing and innovatively extracts the features of face image by convolution neural network, verifies the face by cosine similarity, and introduces a user privacy protection scheme based on secu

APA, Harvard, Vancouver, ISO, and other styles

15

Chen, Chen, Ze Sun, Jiale Zhang, Junwei Dong, Peng Zhang, and Jie Guo. "Enhanced Collaborative Edge Intelligence for Explainable and Transferable Image Recognition in 6G-Aided IIoT." Sensors 25, no. 14 (2025): 4365. https://doi.org/10.3390/s25144365.

Full text

Abstract:

The Industrial Internet of Things (IIoT) has revolutionized industry through interconnected devices and intelligent applications. Leveraging the advancements in sixth-generation cellular networks (6G), the 6G-aided IIoT has demonstrated a superior performance across applications requiring low latency and high reliability, with image recognition being among the most pivotal. However, the existing algorithms often neglect the explainability of image recognition processes and fail to address the collaborative potential between edge computing servers. This paper proposes a novel method, IRCE (Inte

APA, Harvard, Vancouver, ISO, and other styles

16

Chen, Liming, Xiaoyun Kuang, Fusheng Zhu, and Junjuan Xia. "Intelligent Mobile Edge Computing Networks for Internet of Things." IEEE Access 9 (2021): 95665–74. http://dx.doi.org/10.1109/access.2021.3093886.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Deng, Dan, and Junjuan Xia. "Cache-Enabled Cooperative Edge Networks for Intelligent Connected Vehicles." IEEE Access 7 (2019): 166939–49. http://dx.doi.org/10.1109/access.2019.2952172.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Gallyamov, D., V. Kisel, R. Kirichek, A. Borodin, and A. Koucheryavy. "NETWORK LATENCY COMPENSATION APPROACHES FOR APPLICATIONS IN 2030 COMMUNICATIONS NETWORKS." Telecom IT 7, no. 2 (2019): 1–11. http://dx.doi.org/10.31854/2307-1303-2019-7-2-1-11.

Full text

Abstract:

Research subject. Communication network architecture 2030, delay compensation mechanisms. Objective. Consider the architecture of communication networks with intelligent edge computing, propose mechanisms for compensating network latency for tactile Internet applications based on predictive analytics. Core results. Scientific publications and specifications from open sources were analyzed, on tactile Internet topics, delay compensation mechanisms, intelligent boundary computing. A model of 2030 network architecture and a method of minimizing delay based on machine learning are proposed. Main c

APA, Harvard, Vancouver, ISO, and other styles

19

Wang, Pin, Zhijian Gao, Yimin Li, Lingyu Zeng, and Hongmei Zhong. "Design and Implementation of a Radioactive Source Intelligent Search Robot Based on Artificial Intelligence Edge Computing." Wireless Communications and Mobile Computing 2022 (May 17, 2022): 1–12. http://dx.doi.org/10.1155/2022/3940348.

Full text

Abstract:

Artificial intelligence is a very broad science, which consists of different fields, such as machine learning, and computer vision. In recent years, the world nuclear industry has developed vigorously. At the same time, incidents of loss of radioactive sources also occur from time to time. At present, most of the search for radioactive sources adopt manual search, which is inefficient, and the searchers are vulnerable to radiation damage. Sending a robot to the search an area where there may be an uncontrolled radioactive source is different. Not only does it improve efficiency, it also protec

APA, Harvard, Vancouver, ISO, and other styles

20

Pencheva, Evelina, Ivaylo Atanasov, and Ventsislav Trifonov. "Towards Intelligent, Programmable, and Open Railway Networks." Applied Sciences 12, no. 8 (2022): 4062. http://dx.doi.org/10.3390/app12084062.

Full text

Abstract:

The virtualization and automation of network functions will be key features of future high-speed railway networks, which have to provide dependable, safe, and secure services. The virtualization of railway network functions will enable functions such as train control, train integrity protection, shunting control, and trackside monitoring and maintenance to be virtualized and to be run on general-purpose hardware. Network function virtualization combined with edge computing can deliver dynamic, low-latency, and reliable services. The automation of railway operations can be achieved by embedding

APA, Harvard, Vancouver, ISO, and other styles

21

Moreno-Vozmediano, Rafael, Rubén S. Montero, Eduardo Huedo, and Ignacio M. Llorente. "Intelligent Resource Orchestration for 5G Edge Infrastructures." Future Internet 16, no. 3 (2024): 103. http://dx.doi.org/10.3390/fi16030103.

Full text

Abstract:

The adoption of edge infrastructure in 5G environments stands out as a transformative technology aimed at meeting the increasing demands of latency-sensitive and data-intensive applications. This research paper presents a comprehensive study on the intelligent orchestration of 5G edge computing infrastructures. The proposed Smart 5G Edge-Cloud Management Architecture, built upon an OpenNebula foundation, incorporates a ONEedge5G experimental component, which offers intelligent workload forecasting and infrastructure orchestration and automation capabilities, for optimal allocation of virtual r

APA, Harvard, Vancouver, ISO, and other styles

22

R, Anuvidhya. "RANFO: An Intelligent Anomaly Detection in IoT Edge Devices." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 2900–2907. http://dx.doi.org/10.22214/ijraset.2021.35622.

Full text

Abstract:

As devices, applications, and communication networks become more connected and integrated, computer attacks on the Internet of Things (IoT) become more sophisticated. When attacks on IoT networks cause long-term outages, it affects the availability of critical end-user programmers, increases the number of data breaches and fraud, raises prices, and reduces revenue. In this paper we present the RANFO (IDS), prepared to protect inherently linked Iot systems. The proposed entry-level system can successfully enter real-world entrance, according to our experimental results. We'll illustrate how RAN

APA, Harvard, Vancouver, ISO, and other styles

23

Researcher. "EVALUATION OF PRIVACY-PRESERVING AI USING EDGE COMPUTING IN V2X FRAMEWORK." International Journal of Cyber Warfare and Terrorism (IJCWT) 2, no. 2 (2024): 1–11. https://doi.org/10.5281/zenodo.13841539.

Full text

Abstract:

The advent of Vehicle-to-Everything (V2X) communication has ushered in a new era of intelligent urban transportation systems, promising enhanced safety, efficiency, and connectivity. However, the extensive data sharing inherent in V2X networks poses significant privacy challenges. This review paper explores the integration of privacy-preserving Artificial Intelligence (AI) within the V2X framework, emphasizing the role of edge computing as a pivotal enabler. We systematically examine state-of-the-art techniques in privacy-preserving AI, including federated learning, differential privacy, and h

APA, Harvard, Vancouver, ISO, and other styles

24

Tang, Yajuan, Shiwei Lai, Yanyi Rao, et al. "Intelligent Distributed Data Storage for Wireless Communications in B5G Networks." ICST Transactions on Mobile Communications and Applications 7, no. 2 (2022): e2. http://dx.doi.org/10.4108/eetmca.v7i2.2415.

Full text

Abstract:

With the deployment and commercialization of the fifth-generation (5G) mobile communication network, the access nodes and data volume of wireless network show a massive and blowout growth trend. Taking beyond 5G (B5G) edge intelligent network as the research object, based on the deep integration of storage / computing and communication, this paper focuses on the theory and key technology of system intelligent transmission, so as to effectively support the related applications of B5G edge intelligent network in the future. This paper analyzes the research status of data storage, studies the rea

APA, Harvard, Vancouver, ISO, and other styles

25

Dong, Chao, Yun Shen, Yuben Qu, et al. "UAVs as an Intelligent Service: Boosting Edge Intelligence for Air-Ground Integrated Networks." IEEE Network 35, no. 4 (2021): 167–75. http://dx.doi.org/10.1109/mnet.011.2000651.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Tassiulas, Leandros. "Enabling Intelligent Services at the Network Edge." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (2022): 69–70. http://dx.doi.org/10.1145/3543516.3453912.

Full text

Abstract:

The proliferation of novel mobile applications and the associated AI services necessitates a fresh view on the architecture, algorithms and services at the network edge in order to meet stringent performance requirements. Some recent work addressing these challenges is presented. In order to meet the requirement for low-latency, the execution of computing tasks moves form the cloud to the network edge, closer to the end-users. The joint optimization of service placement and request routing in dense mobile edge computing networks is considered. Multidimensional constraints are introduced to cap

APA, Harvard, Vancouver, ISO, and other styles

27

Liu, Xun. "Blockchain-Enabled Collaborative Edge Computing for Intelligent Education Systems Using Social IoT." International Journal of Distributed Systems and Technologies 13, no. 7 (2022): 1–19. http://dx.doi.org/10.4018/ijdst.307958.

Full text

Abstract:

As new technologies such as the internet of things, big data analysis, artificial intelligence, and cloud computing are widely used, intelligent learning platforms and web-based educational platforms are gaining popularity. Social internet of things (SIoT) uses mobile edge computing and interpersonal interactions among SIoT users to take advantage of the benefits that collaborative edge computing (CEC) offers, even while posing new challenges. The communication efficiency and the security of intelligent education systems must be considerably developed to ensure real-time services. Therefore, t

APA, Harvard, Vancouver, ISO, and other styles

28

Liu, Xiao, Jiong Jin, and Fang Dong. "Edge-Computing-Based Intelligent IoT: Architectures, Algorithms and Applications." Sensors 22, no. 12 (2022): 4464. http://dx.doi.org/10.3390/s22124464.

Full text

Abstract:

With the rapid growth of the Internet of Things (IoT), 5G networks and beyond, the computing paradigm for intelligent IoT systems is shifting from conventional centralized-cloud computing to distributed edge computing [...]

APA, Harvard, Vancouver, ISO, and other styles

29

Huo, Yiming, Xingqin Lin, Boya Di, et al. "Technology Trends for Massive MIMO towards 6G." Sensors 23, no. 13 (2023): 6062. http://dx.doi.org/10.3390/s23136062.

Full text

Abstract:

At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its successful integration and scalability within 5G and beyond, massive MIMO has proven its merits and adaptability. Notably, a series of evolutionary advancements and revolutionary trends have begun to materialize in recent years, envisioned to redefine the landscape of future 6G wireless systems and networks. In particular, the capabilities and

APA, Harvard, Vancouver, ISO, and other styles

30

Hussein, Nawroz, and Ahmad B. Al-Khalil. "Intelligent Resource Management for Vehicular Networks in Cloud-Edge Architectures." Zanin Journal of Science and Engineering 1, no. 1 (2025): 1–19. https://doi.org/10.64362/zjse.43.

Full text

Abstract:

Nowadays, resource management for vehicular networks is crucial for enhancing the efficiency, scalability, and reliability of connected vehicle systems. Through leveraging AI-driven resource allocation across cloud and edge environments, this approach optimizes latency-sensitive applications, improves network performance, and supports real-time decision-making in autonomous and smart transportation systems. This article discusses employing distributed machine learning algorithms at the network edge, resource optimization, and pathfinding/optimization of vehicular communication networks. Integr

APA, Harvard, Vancouver, ISO, and other styles

31

Wan, Xijun. "Research Overview of Intelligent Computing Platform Technology." Applied and Computational Engineering 151, no. 1 (2025): 41–50. https://doi.org/10.54254/2755-2721/2025.22841.

Full text

Abstract:

With the explosive growth of data and the increasing complexity of computing tasks, traditional computing models can no longer meet the demands. Parallel and distributed processing technologies have become key forces driving innovation in information technology. This paper reviews the research progress of intelligent computing platform technologies, focusing on parallel processing and distributed processing technologies. It primarily examines the basic principles and applications of multi-core processor technology, large-scale parallel algorithms, parallel programming, industrial computer netw

APA, Harvard, Vancouver, ISO, and other styles

32

Kashyap, Meenakshi, Ravirajsinh Chauhan, Dhruvil Patel, and Kishan Prajapati. "Towards a Sustainable Future: Enabling Industry with Green Web 3.0, Decentralized AI, and Edge Intelligence." ITM Web of Conferences 65 (2024): 03015. http://dx.doi.org/10.1051/itmconf/20246503015.

Full text

Abstract:

Our world is, at a point in terms of the environment. The fashioned industrial approach, which heavily relies on centralized systems and resource-intensive computing is no longer sustainable. This document delves into a way to embrace Green Web 3.0, Decentralized AI and Edge Intelligence to drive the industry to-ward a more sustainable future. Green Web 3.0 challenges the energy nature of blockchain technology by utilizing eco-friendly protocols such as Proof of Stake which reduces energy consumption and lessens environmental impact. Similarly, Decentralized AI empowers distributed systems dec

APA, Harvard, Vancouver, ISO, and other styles

33

Aravind Guduru. "The intelligent warehouse: Where AI and Human Intelligence Converge." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 679–86. https://doi.org/10.30574/wjarr.2025.26.2.1635.

Full text

Abstract:

The modern fulfillment center is experiencing a technological transformation at the intersection of artificial intelligence and human capabilities. This article explores how cutting-edge AI accelerators, neural networks, and humanoid robotics are revolutionizing warehouse operations. The emergence of flexible humanoid systems that learn through observation, the computing architecture enabling real-time decision-making, and the development of dynamic spatial intelligence that continuously optimizes operations. The piece investigates how these technologies enhance rather than replace human worke

APA, Harvard, Vancouver, ISO, and other styles

34

Lai, Shiwei, Rui Zhao, Shunpu Tang, Junjuan Xia, Fasheng Zhou, and Liseng Fan. "Intelligent secure mobile edge computing for beyond 5G wireless networks." Physical Communication 45 (April 2021): 101283. http://dx.doi.org/10.1016/j.phycom.2021.101283.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Hazra, Abhishek, Mainak Adhikari, Sudarshan Nandy, Khushbu Doulani, and Varun G. Menon. "Federated-Learning-Aided Next-Generation Edge Networks for Intelligent Services." IEEE Network 36, no. 3 (2022): 56–64. http://dx.doi.org/10.1109/mnet.007.2100549.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Math, Sa, Prohim Tam, and Seokhoon Kim. "Intelligent Real-Time IoT Traffic Steering in 5G Edge Networks." Computers, Materials & Continua 67, no. 3 (2021): 3433–50. http://dx.doi.org/10.32604/cmc.2021.015490.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Guo, Yinghao, Zichao Zhao, Rui Zhao, et al. "Intelligent Offloading Strategy Design for Relaying Mobile Edge Computing Networks." IEEE Access 8 (2020): 35127–35. http://dx.doi.org/10.1109/access.2020.2972106.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Karimi, Elham, Yuanzhu Chen, and Behzad Akbari. "Intelligent and Decentralized Resource Allocation in Vehicular Edge Computing Networks." IEEE Internet of Things Magazine 6, no. 4 (2023): 112–17. http://dx.doi.org/10.1109/iotm.001.2200268.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Jin, Wenquan, Rongxu Xu, Sunhwan Lim, Dong-Hwan Park, Chanwon Park, and Dohyeun Kim. "Dynamic Inference Approach Based on Rules Engine in Intelligent Edge Computing for Building Environment Control." Sensors 21, no. 2 (2021): 630. http://dx.doi.org/10.3390/s21020630.

Full text

Abstract:

Computation offloading enables intensive computational tasks in edge computing to be separated into multiple computing resources of the server to overcome hardware limitations. Deep learning derives the inference approach based on the learning approach with a volume of data using a sufficient computing resource. However, deploying the domain-specific inference approaches to edge computing provides intelligent services close to the edge of the networks. In this paper, we propose intelligent edge computing by providing a dynamic inference approach for building environment control. The dynamic in

APA, Harvard, Vancouver, ISO, and other styles

40

Jebari, Hakim, Meriem Hayani Mechkouri, Siham Rekiek, and Kamal Reklaoui. "Poultry-Edge-AI-IoT System for Real-Time Monitoring and Predicting by Using Artificial Intelligence." International Journal of Interactive Mobile Technologies (iJIM) 17, no. 12 (2023): 149–70. http://dx.doi.org/10.3991/ijim.v17i12.38095.

Full text

Abstract:

Poultry farms have played a significant role throughout human history, in feeding the growing population. A good environment is a perfect condition for the growth of poultry, preventing disease, and effective production. The temperature higher and the humidity favor the growth of bacteria and hence the production of ammonia (NH3) by the decomposition of organic matter. Ammonia (NH3), carbon monoxide (CO), and carbon dioxide (CO2), Methane (CH4), hydrogen sulfide (H2S) are poisonous gases that can cause poultry diseases and mortality. The combination of Artificial Intelligence (AI), Internet of

APA, Harvard, Vancouver, ISO, and other styles

41

Bourechak, Amira, Ouarda Zedadra, Mohamed Nadjib Kouahla, Antonio Guerrieri, Hamid Seridi, and Giancarlo Fortino. "At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives." Sensors 23, no. 3 (2023): 1639. http://dx.doi.org/10.3390/s23031639.

Full text

Abstract:

Given its advantages in low latency, fast response, context-aware services, mobility, and privacy preservation, edge computing has emerged as the key support for intelligent applications and 5G/6G Internet of things (IoT) networks. This technology extends the cloud by providing intermediate services at the edge of the network and improving the quality of service for latency-sensitive applications. Many AI-based solutions with machine learning, deep learning, and swarm intelligence have exhibited the high potential to perform intelligent cognitive sensing, intelligent network management, big da

APA, Harvard, Vancouver, ISO, and other styles

42

Alladi, Tejasvi, Ayush Agrawal, Bhavya Gera, Vinay Chamola, and F. Richard Yu. "Ambient Intelligence for Securing Intelligent Vehicular Networks: Edge-Enabled Intrusion and Anomaly Detection Strategies." IEEE Internet of Things Magazine 6, no. 1 (2023): 128–32. http://dx.doi.org/10.1109/iotm.001.2200197.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Islam, Shafkat, Shahriar Badsha, Shamik Sengupta, Hung La, Ibrahim Khalil, and Mohammed Atiquzzaman. "Blockchain-Enabled Intelligent Vehicular Edge Computing." IEEE Network 35, no. 3 (2021): 125–31. http://dx.doi.org/10.1109/mnet.011.2000554.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Cheng, Yangbo. "Study on Smart Telematics Cache Optimization Strategy Based on Edge Computing." Journal of Electronic Research and Application 9, no. 3 (2025): 111–18. https://doi.org/10.26689/jera.v9i3.10601.

Full text

Abstract:

With the rapid development of intelligent transportation systems, vehicular networks (VANETs) have become an essential part of the intelligent transportation infrastructure. Due to the high dynamics of efficient vehicular network nodes and the low latency requirement of data interaction, the traditional cloud computing model makes it difficult to meet the real-time and performance criteria, and the storage optimization strategy based on edge computing can effectively improve the data access efficiency and system response. This paper explores optimizing the data caching mechanism of intelligent

APA, Harvard, Vancouver, ISO, and other styles

45

Wu, Dingcheng, Xueyong Xu, Chang Lu, and Dapeng Mu. "Energy-Efficient Connectivity Algorithm for Directional Sensor Networks in Edge Intelligence Systems." Symmetry 17, no. 1 (2024): 20. https://doi.org/10.3390/sym17010020.

Full text

Abstract:

The proliferation of edge intelligence systems necessitates efficient and reliable connectivity for sensor networks deployed at the edge. This paper proposes a novel energy-efficient connectivity algorithm called Constrained Angle-aware Connectivity Optimization (CA-Opt), designed for directional sensor networks to address the challenges of limited resources and asymmetric network constraints in edge environments. CA-Opt constructs a hop-constrained, degree-bounded network topology while considering the directional coverage of sensor nodes. The algorithm incorporates an angle-aware child selec

APA, Harvard, Vancouver, ISO, and other styles

46

Shyh-Wei Chen, Shyh-Wei Chen, Chun-Ju Tsai Shyh-Wei Chen, Chia-Hui Liu Chun-Ju Tsai, William Cheng-Chung Chu Chia-Hui Liu, and Ching-Tsorng Tsai William Cheng-Chung Chu. "Development of an Intelligent Defect Detection System for Gummy Candy under Edge Computing." 網際網路技術學刊 23, no. 5 (2022): 981–88. http://dx.doi.org/10.53106/160792642022092305006.

Full text

Abstract:

<p>Gummy candies are one of the products of the food industry. It has invested more resources in all aspects of the food production chain to improve production processes. The defective candies cause the unevenness of the product that will cause the appearance, taste and flavor poor. That will lead to economic losses for the company. Most traditional candy companies set up product inspection personnel to eliminate defective product. In this paper, an intelligent defect detection system for gummy candy industry under edge computing environment is proposed. It can replace manual visual insp

APA, Harvard, Vancouver, ISO, and other styles

47

Tuli, Shreshth. "SplitPlace." ACM SIGMETRICS Performance Evaluation Review 49, no. 2 (2022): 63–65. http://dx.doi.org/10.1145/3512798.3512821.

Full text

Abstract:

In recent years, deep learning models have become ubiquitous in industry and academia alike. Modern deep neural networks can solve one of the most complex problems today, but coming with the price of massive compute and storage requirements. This makes deploying such massive neural networks challenging in the mobile edge computing paradigm, where edge nodes are resource-constrained, hence limiting the input analysis power of such frameworks. Semantic and layer-wise splitting of neural networks for distributed processing show some hope in this direction. However, there are no intelligent algori

APA, Harvard, Vancouver, ISO, and other styles

48

Huang, Ying, Yongmei Su, and Shuanggui Lu. "Intelligent IoT Surveillance and Instantaneous Management." Electronics ETF 29, no. 1 (2025): 3–13. https://doi.org/10.53314/els2529003h.

Full text

Abstract:

Unmanned Vehicles (UVs) and the Industry Internet of Things (IoT) are two examples of new technology being incorporated into manufacturing processes during the fourth industrial revolution. IT networks must be machine-compatible to integrate these technologies; this includes addressing problems with connectivity, fog, and cloud-based computing security, lowering latency, and improving data reliability and standard of service. Regarding IoT, AI techniques must handle resource management, network deployment, and these problems. The significant issues are unstable and high-latency communications

APA, Harvard, Vancouver, ISO, and other styles

49

Alrowaili, Dalal, Zohaib Zahid, Muhammad Ahsan, Sohail Zafar, and Imran Siddique. "Edge Metric Dimension of Some Classes of Toeplitz Networks." Journal of Mathematics 2021 (December 17, 2021): 1–11. http://dx.doi.org/10.1155/2021/3402275.

Full text

Abstract:

Toeplitz networks are used as interconnection networks due to their smaller diameter, symmetry, simpler routing, high connectivity, and reliability. The edge metric dimension of a network is recently introduced, and its applications can be seen in several areas including robot navigation, intelligent systems, network designing, and image processing. For a vertex s and an edge g = s 1 s 2 of a connected graph G , the minimum number from distances of s with s 1 and s 2 is called the distance between s and g . If for every two distinct edges s 1 , s 2 ∈ E G , there always exists w 1 ɛ W E ⊆ V G ,

APA, Harvard, Vancouver, ISO, and other styles

50

Buchenko, Ihor. "INTELLIGENT ENERGY CONSUMPTION MANAGEMENT IN EDGE COMPUTING NETWORKS BASED ON GAME THEORY." Cybersecurity: Education, Science, Technique 3, no. 27 (2025): 180–92. https://doi.org/10.28925/2663-4023.2025.27.732.

Full text

Abstract:

With the development of edge computing and the Internet of Things (IoT) technologies, the relevance of optimizing energy consumption in distributed networks is increasing. Traditional energy management methods are often inefficient due to the lack of adaptation to dynamic load conditions and limited coordination capabilities between nodes. This paper presents a cooperative dynamic energy management model in edge computing networks based on game theory principles. The introduction identifies the main problems of modern edge computing systems, including high energy consumption, uneven load distr

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!