![](https://scdn.x-mol.com/css/images/icon-new-link.png)
样式: 排序: IF: - GO 导出 标记为已读
-
Attenuating majority attack class bias using hybrid deep learning based IDS framework J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-07-03 K.G. Raghavendra Narayan, Rakesh Ganesula, Tamminaina Sai Somasekhar, Srijanee Mookherji, Vanga Odelu, Rajendra Prasath, Alavalapati Goutham Reddy
In real-time application domains, like finance, healthcare and defence, delay in service or stealing information may lead to unrecoverable consequences. So, early detection of intrusion is important to prevent security breaches. In recent days, anomaly-based intrusion detection using Hybrid Deep Learning approaches are becoming more popular. The most used benchmark datasets in the literature are NSL-KDD
-
Uncovering phishing attacks using principles of persuasion analysis J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-07-03 Lázaro Bustio-Martínez, Vitali Herrera-Semenets, Juan Luis García-Mendoza, Miguel Ángel Álvarez-Carmona, Jorge Ángel González-Ordiano, Luis Zúñiga-Morales, J. Emilio Quiróz-Ibarra, Pedro Antonio Santander-Molina, Jan van den Berg
With the rising of Internet in early ’90s, many fraudulent activities have migrated from physical to digital: one of them is phishing. Phishing is a deceptive practice focused on exploiting the human factor, which is the most vulnerable aspect of any security process. In this scam, social engineering techniques are extensively utilized, specifically focusing on the principles of persuasion, to deceive
-
On designing a profitable system model to harmonize the tripartite dissension in content delivery applications J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-07-02 Libin Yang, Wei Lou
The popularity of commercial content delivery applications has led to dissension among three embroiled parties: Content Service Providers (CSPs), Internet Service Providers (ISPs), and End Users (EUs). This dissension is not only a technical problem but an economic problem. To harmonize this dissension, this paper takes live streaming as a typical content delivery application. It proposes a profitable
-
Satellite synergy: Navigating resource allocation and energy efficiency in IoT networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-07-02 Muhammad Abdullah, Humayun Zubair Khan, Umair Fakhar, Ahmad Naeem Akhtar, Shuja Ansari
Satellite-assisted internet of things (IoT) networks have emerged as a beacon of promise, offering global coverage and uninterrupted connectivity. However, the challenges of resource allocation and task offloading in such networks are intricate due to the unique characteristics of satellite communication systems. This research’s findings enrich the landscape of energy-efficient and dependable satellite-assisted
-
Privacy-preserving generation and publication of synthetic trajectory microdata: A comprehensive survey J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-07-01 Jong Wook Kim, Beakcheol Jang
The generation of trajectory data has increased dramatically with the advent and widespread use of GPS-enabled devices. This rich source of data provides invaluable insights for various applications such as traffic optimization, urban planning, crowd management, and public safety. However, the increasing demand for the publication and sharing of trajectory data for big data analytics raises significant
-
A Contextual Multi-Armed Bandit approach for NDN forwarding J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-29 Yakoub Mordjana, Badis Djamaa, Mustapha Reda Senouci, Aymen Herzallah
Named Data Networking (NDN) is a promising Internet architecture that aims to supersede the current IP-based architecture and shift the host-centric model to a data-centric one. Within NDN, forwarding Interest packets remains a significant challenge and has attracted considerable recent research attention. The momentum behind machine learning techniques, especially reinforcement learning, is steadily
-
JamholeHunter: On detecting new wormhole attack in Opportunistic Mobile Networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-28 Ala Altaweel, Sidra Aslam, Ibrahim Kamel
This paper first shows that Prophet, Spray and Wait, Epidemic, and First Contact routing protocols in Opportunistic Mobile Networks (OMNs) are vulnerable to the Jamhole attack. In Jamhole attack, an attacker, Eve, compromises two different locations in OMNs by (i) jamming the GPS signal of victim nodes in these locations and (ii) by establishing a pair-wise hidden wormhole tunnel among these locations
-
Multi-UAV aided energy-aware transmissions in mmWave communication network: Action-branching QMIX network J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-26 Quang Tuan Do, Thien Duc Hua, Anh-Tien Tran, Dongwook Won, Geeranuch Woraphonbenjakul, Wonjong Noh, Sungrae Cho
Advancements in drone technology and high-frequency millimeter-wave communications are transforming unmanned-aerial-vehicles (UAV)-aided networks, expanding their potential across diverse applications. Despite the advantages of broad frequency bandwidth and enhanced line of sight connectivity in the UAV-aided millimeter-wave networks, it is challenging to provide high network performance because of
-
Leveraging application permissions and network traffic attributes for Android ransomware detection J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-26 Sekione Reward Jeremiah, Haotian Chen, Stefanos Gritzalis, Jong Hyuk Park
The increase in ransomware threats targeting Android devices necessitates the development of advanced techniques to strengthen the effectiveness of detection and prevention methods. Existing studies use Machine Learning (ML) techniques to detect and classify ransomware attacks, however, the ransomware landscape's rapid evolution hinders the effectiveness of these approaches. Moreover, the potential
-
SDN-based reliable emergency message routing schema using Digital Twins for adjusting beacon transmission in VANET J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-25 Zainab H. Ali, Nora El-Rashidy, Mostafa A. Elhosseini, Sarah M. Ayyad
Digital Twin (DT) has revolutionized the contextualized digital environment. This advancement enables real-time monitoring and simulation of events, leading to more effective decision-making. In smart transportation, DT plays a crucial role in enhancing various aspects of road decision-making, including optimizing routing decisions for Emergency Message (EM) forwarding in Vehicular Ad hoc Networks
-
Towards zero-energy: Navigating the future with 6G in Cellular Internet of Things J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-25 Muhammad Tahir Abbas, Karl-Johan Grinnemo, Guillaume Ferré, Philippe Laurent, Stefan Alfredsson, Mohammad Rajiullah, Johan Eklund
The Cellular Internet of Things (CIoT) has seen significant growth in recent years. With the deployment of 5G, it has become essential to reduce the power consumption of these devices for long-term sustainability. The upcoming 6G cellular network introduces the concept of zero-energy CIoT devices, which do not require batteries or manual charging. This paper focuses on these devices, providing insight
-
Detecting DDoS based on attention mechanism for Software-Defined Networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-25 Namkyung Yoon, Hwangnam Kim
-
Quick service during DDoS attacks in the container-based cloud environment J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-25 Anmol Kumar, Mayank Agarwal
-
Federated deep reinforcement learning for task offloading and resource allocation in mobile edge computing-assisted vehicular networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-25 Xu Zhao, Yichuan Wu, Tianhao Zhao, Feiyu Wang, Maozhen Li
Mobile edge computing (MEC) enables computation intensive applications in the Internet of Vehicles (IoV) to no longer be limited by device resources. However, the lack of an effective task scheduling strategy will seriously affect users’ quality of experience (QoE). In this paper, a task type-based task offloading and resource allocation strategy is proposed to reduce delay and energy consumption during
-
Virtual reality traffic prioritization for Wi-Fi quality of service improvement using machine learning classification techniques J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-24 Seyedeh Soheila Shaabanzadeh, Marc Carrascosa-Zamacois, Juan Sánchez-González, Costas Michaelides, Boris Bellalta
The increase in the demand for eXtended Reality (XR)/Virtual Reality (VR) services in the recent years, poses a great challenge for Wi-Fi networks to maintain the strict latency requirements. In VR over Wi-Fi, latency is a significant issue. In fact, VR users expect instantaneous responses to their interactions, and any noticeable delay can disrupt user experience. Such disruptions can cause motion
-
Constrained routing in multi-partite graph to solve VNF placement and chaining problem J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-24 Mohand Yazid Saidi, Issam Abdeldjalil Ikhelef, Shuopeng Li, Ken Chen
Network Functions Virtualization (NFV) and Software-Defined Networks (SDN) empower IT professionals and service providers to strategically deploy Virtual Network Functions (VNFs), resulting in enhanced services and security while minimizing costs. Network services are dynamically provided through the deployment of Service Function Chains (SFCs), which involve selecting and interconnecting physical
-
Metarouting with automatic tunneling in multilayer networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-24 Noureddine Mouhoub, Maria Moloney, Damien Magoni
Metarouting allows for the modeling of routing protocols using an algebraic structure called routing algebra. Routing protocols requiring design or validation can easily be modeled using this approach. To date, however, existing research on routing algebras has mainly focused on applying this approach to routing protocols that are generally used in networks which have a single addressing and forwarding
-
A robust PID and RLS controller for TCP/AQM system J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-24 Junyong Tang, Hui Li, Jiankang Zhang, Kangqian Guan, Qiqi Shan, Xiangyang Liang
Transmission Control Protocol (TCP) controlling congestion by peer-to-peer is challenging to handle communication with numerous concurrent TCP flows and heavy traffic loads. Therefore, TCP requires the active queue management (AQM) to assist in avoiding buffer bloat in intermediate devices. Thus, Some AQM controllers, such as Red, Codel, and Pie, have been proposed to control congestion better. However
-
GROM: A generalized routing optimization method with graph neural network and deep reinforcement learning J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-24 Mingjie Ding, Yingya Guo, Zebo Huang, Bin Lin, Huan Luo
Routing optimization, as a significant part of Traffic Engineering (TE), plays an important role in balancing network traffic and improving quality of service. With the application of Machine Learning (ML) in various fields, many neural network-based routing optimization solutions have been proposed. However, most existing ML-based methods need to retrain the model when confronted with a network unseen
-
An agnostic and secure interoperability protocol for seamless asset movement J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 El-hacen Diallo, Mohameden Dieye, Omar Dib, Pierre Valiorgue
As blockchain technology continues to evolve, it has fostered an extensive ecosystem of applications and platforms. This dynamic landscape is characterized by a myriad of innovative solutions, ranging from decentralized finance and supply chain management to digital identity and voting systems, each contributing to the ongoing advancement and adoption of blockchain technology across various sectors
-
Dynamic Charging Scheduling and Path Planning Scheme for Multiple MC-enabled On-demand Wireless Rechargeable Sensor Networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Riya Goyal, Abhinav Tomar
With the advancement of wireless energy transfer, Wireless Rechargeable Sensor Networks (WRSNs) have become increasingly popular for efficiently charging sensor nodes. In WRSNs, determining the charging schedule for Mobile Chargers (MCs) is critical for reducing maintenance costs and improving charging efficiency. This is termed the Charging Scheduling Problem (CSP), which is proven to be NP-hard in
-
RECAR: Robust and efficient collision-avoiding routing for 3D underwater named data networking J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Yue Li, Yingjian Liu, Haoyu Yin, Zhongwen Guo, Yu Wang
Internet of Underwater Things (IoUT) has important application prospects in fields of both scientific research and commercial business. As a future network architecture, Named Data Networking (NDN) is starting to be applied to IoUT. Although Underwater Named Data Networking (UNDN) has unique advantages in dealing with bandwidth usage, multi-path forwarding, and node mobility, there is still no specific
-
Broadcast/multicast delivery integration in B5G/6G environments J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Orlando Landrove, Rufino Cabrera, Eneko Iradier, Erick Jimenez, Pablo Angueira, Jon Montalban
This paper describes the design of a Broadcast Core Network (BCN). The BCN is intended to enable the integration of existing terrestrial broadcast systems into a 5G/6G ecosystem. The existing multimedia content distribution architecture in current broadcast networks and the capabilities of 5G access and core networks (5GC) are analyzed to dissect their limitations. We show, inter alia, how the lack
-
Multi-agent reinforcement learning for privacy-aware distributed CNN in heterogeneous IoT surveillance systems J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Emna Baccour, Aiman Erbad, Amr Mohamed, Mounir Hamdi, Mohsen Guizani
Although Deep Neural Networks (DNN) have become the backbone technology of several Internet of Things (IoT) applications, their execution in resource-constrained devices remains challenging. To cater for these challenges, collaborative deep inference conducted by IoT devices was introduced. However, the prevalence of DNN computation suffers from severe privacy problems, e.g. data-reverse and model
-
AI for AI-based intrusion detection as a service: Reinforcement learning to configure models, tasks, and capacities J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Ying-Dar Lin, Hao-Xuan Huang, Didik Sudyana, Yuan-Cheng Lai
Intrusion Detection Systems (IDS) increasingly leverage machine learning (ML) to enhance the detection of zero-day attacks. As operational complexities increase, enterprises are turning to Intrusion Detection as a Service (IDaS), requiring advanced solutions for efficient ML model selection and resource allocation. Existing research often focuses primarily on accuracy and computational efficiency,
-
The universal federator: A third-party authentication solution to federated cloud, edge, and fog J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Asad Ali, Ying-Dar Lin, Jian Liu, Chin-Tser Huang
Cloud, Edge, and Fog computing provide computational services to different end users. A federation among these computing paradigms is beneficial, as it enhances the capability, capacity, coverage, and services of cloud, edge, and fog. An authentication method is needed to realize such a federation among cloud, edge, and fog so that a user belonging to one of these computing paradigms can use the services
-
Caching or not: An online cost optimization algorithm for geodistributed data analysis in cloud environments J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-22 Weitao Yang, Li Pan, Shijun Liu
With the wide application of big data technology, a large number of data geographically stored in data centers across various regions are generated everyday, waiting to be analyzed by big data tasks. Examples of such data analysis tasks include weather prediction and intelligent healthcare applications. Clouds are being used by more and more enterprises due to their nearly infinite resources, ease
-
Troubleshooting solution for traffic congestion control J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-21 Van Tong, Sami Souihi, Hai Anh Tran, Abdelhamid Mellouk
The Internet has existed since the 1970s as a means of data exchange between network devices in small networks. In the early stage, there was a small number of devices, but today there is an ever-increasing number of devices, leading to congestion in the network. Therefore, congestion control has attracted so much attention in the academic community and the industry for the past 30 years. Recently
-
MCTE-RPL: A multi-context trust-based efficient RPL for IoT J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-21 Javad Mohajerani, Mokhtar Mohammadi Ghanatghestani, Malihe Hashemipour
The Internet of things (IoT) is highly exposed to various attacks due to its sensitive applications, but it is very vulnerable in dealing with these attacks. So, various studies have been introduced to improve IoT security. Most of methods have focused on improving the security of the RPL protocol (Low-Power and Lossy Networks routing protocol) based on the development of trust models. However, most
-
Seraph: Towards secure and efficient multi-controller authentication with [formula omitted]-threshold signature in multi-domain SDWAN J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-21 Wendi Feng, Ke Liu, Shuo Sun, Bo Cheng, Wei Zhang
The multi-controller scheme is widely adopted in Software-Defined Wide Area Networks (SDWANs), where a WAN is segmented into multiple domains, each controlled by one controller. These controllers communicate with each other in-band, necessitating authentication before exchanging control messages. However, relying solely on identification of a single node for authentication exposes the network to spoofing
-
Advanced optimization-based weighted features for ensemble deep learning smart occupancy detection network for road traffic parking J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 B. Padmavathi, Vanaja Selvaraj
In day-to-day activities, the advanced technology like Internet of Things (IoT) emerges to improve the lifestyle of people. In metropolitan cities, real-time parking is the long-lasting problem that we face in our daily life activities. Urban parking regulation gained more attention because of its capability to diminish energy consumption, congested traffic, and manifestation. The parking space detection
-
Hybrid kitchen safety guarding with stove fire recognition based on the Internet of Things J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Lien-Wu Chen, Hsing-Fu Tseng, Chun-Yu Cho, Ming-Fong Tsai
In this paper, we design a hybrid kitchen safety guarding framework using embedded devices and onboard sensors to detect abnormal events and block gas sources in time through the Internet of Things (IoT). According to the relevant literature we studied, this is the first framework for kitchen safety guarding that provides the following features: (1) the deep learning based model integrating densely
-
CDT: Cross-interface Data Transfer scheme for bandwidth-efficient LoRa communications in energy harvesting multi-hop wireless networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Hua Qin, Ni Li, Tao Wang, Gelan Yang, Yang Peng
With the capability of generating sustainable energy by exploiting the ambient environment (e.g., light, heat, vibrations, etc.), the energy harvesting (EH) technology is increasingly used on low-power smart objects, forming self-powered green Internet of Things (IoTs). Despite targeting different application domains, many of these green IoT systems adopt the distributed network paradigm by forming
-
Synthetic and privacy-preserving traffic trace generation using generative AI models for training Network Intrusion Detection Systems J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Giuseppe Aceto, Fabio Giampaolo, Ciro Guida, Stefano Izzo, Antonio Pescapè, Francesco Piccialli, Edoardo Prezioso
-
Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 D. Manivannan
The significant advancements in sensors and other resource-constrained devices, capable of collecting data and communicating wirelessly, are poised to revolutionize numerous industries through the Internet of Things (IoT). Sectors such as healthcare, energy, education, transportation, manufacturing, military, and agriculture stand to benefit. IoT is expected to play a crucial role in implementing both
-
A multi-UAV assisted task offloading and path optimization for mobile edge computing via multi-agent deep reinforcement learning J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-20 Tao Ju, Linjuan Li, Shuai Liu, Yu Zhang
To tackle task offloading and path planning challenges in multi-UAV-assisted mobile edge computing, this paper proposes a task offloading and path optimization approach via multi-agent deep reinforcement learning. The primary goal is to minimize the overall energy consumption of the system and improve computational performance. Initially, we established a model for a multi-UAV-assisted mobile edge
-
Parallel path selection mechanism for DDoS attack detection J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-19 Man Li, Huachun Zhou, Shuangxing Deng
DDoS attack have always been a popular topic in the field of network security. As an emerging networking paradigm, SDN’s characteristics such as centralized control and management and monitoring flow-based traffic make it an ideal platform to detect DDoS attacks. NFV can reduce equipment costs, simplify operation complexity, and improve operation performance, which provides a major opportunity for
-
Synchronizing real-time and high-precision LDoS defense of learning model-based in AIoT with programmable data plane, SDN J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-19 Jie Ma, Wei Su, Yikun Li, Yuan Yuan, Ziqing Zhang
The availability of SD-AIoT is currently under complicated and serious cyber threats, especially Low-rate Denial-of-Service attacks. However, traditional defense schemes for such attacks with characteristics of high concealability and periodicity suffer from serious challenges with high detection difficulty, low accuracy of detection models, and inefficiency of mitigation approaches. In this paper
-
Enhancing honeynet-based protection with network slicing for massive Pre-6G IoT Smart Cities deployments J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-18 Antonio Matencio Escolar, Qi Wang, Jose Maria Alcaraz Calero
Internet of Things (IoT) coupled with 5G and upcoming pre-6G networks will provide the scalability and performance required to deploy a wide range of new digital services in Smart Cities. This new digital services will undoubtedly contribute to an improvement in the quality of life of citizens. However, security is a major concern in IoT where low-powered constrained devices are a target for attackers
-
Formal dependability analysis of fault tolerant Virtual Machine allocation strategies in Cloud Radio Access Network J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-13 Sana Younes, Maroua Idi
Cloud Radio Access Network (C-RAN) has been proposed as a fifth generation (5G) cellular network that is designed to physically separate the Baseband Units (BBUs) from the Remote Radio Heads (RRHs). The BBUs are placed in the BBU pool/hotel, while the RRHs are located in the cells. This separation enables sharing baseband processing resources among RRHs by generating Virtual Machines (VMs) in the BBU
-
Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-06-01 Dalhatu Muhammed, Ehsan Ahvar, Shohreh Ahvar, Maria Trocan, Marie-José Montpetit, Reza Ehsani
The Artificial Intelligence of Things (AIoT), a combination of the Internet of Things (IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture (SA). AIoT has been adopted in many applications including agriculture, such as crop yield estimation, soil and water conservation, pest and disease detection and supply chain management. While there are plenty of studies
-
Green grant-free power allocation for ultra-dense Internet of Things: A mean-field perspective J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-31 Sami Nadif, Essaid Sabir, Halima Elbiaze, Abdelkrim Haqiq
Grant-free access, in which each Internet-of-Things (IoT) device delivers its packets through a randomly selected resource without spending time on handshaking procedures, is a promising solution for supporting the massive connectivity required for IoT systems. In this paper, we explore grant-free access with multi-packet reception capabilities, with an emphasis on ultra-low-end IoT applications with
-
A survey of data mining methodologies in the environment of IoT and its variants J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-31 Syeda Zeenat Marshoodulla, Goutam Saha
-
[formula omitted]: Low-latency and reliable event collection in network measurement J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-31 Hongyan Liu, Xi Sun, Xiang Chen, Qun Huang, Dong Zhang, Haifeng Zhou, Chunming Wu, Xuan Liu, Muhammad Khurram Khan
Modern network measurement employs several in the substrate network. These points perform measurement tasks to measure traffic and report real-time to in the control plane. These servers convert events to flow statistics and report them to network management applications, which require both (i.e., collecting events within a limited time deadline) and (i.e., bounding the probability of event loss).
-
Optimal deployment of private 5G multi-access edge computing systems at smart factories: Using hybrid crow search algorithm J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-30 Chun-Cheng Lin, Der-Jiunn Deng, Li-Tsung Hsieh, Pei-Tzu Pan
In smart factories, an increasing number of mobile intelligent devices are deployed to meet the growing demands for flexible manufacturing. These devices, equipped with various sensors, synchronize a substantial amount of data with cloud servers for real-time monitoring and control. Fifth generation mobile networks (5G) combined with multi-access edge computing (MEC) provide the capabilities for multiple
-
Enhanced detection of low-rate DDoS attack patterns using machine learning models J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-27 Razvan Bocu, Maksim Iavich
-
CRAMP: Clustering-based RANs association and MEC placement for delay-sensitive applications J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-09 Saumyaranjan Dash, Asif Uddin Khan, Binayak Kar, Santosh Kumar Swain, Primatar Kuswiradyo, Seifu Birhanu Tadele, Frezer Guteta Wakgra
With advancements in networking technology and ubiquitous computing, there has been a significant increase in the number of edge devices and delay-sensitive applications. To facilitate efficient processing, mobile edge computing (MEC) technology provides resources through MEC servers, which are deployed at the radio access networks (RANs) of 5G networks. However, these MEC servers possess a limited
-
Energy-efficient resource allocation for bidirectional wireless power and information transfer over interference channels J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-07 Kisong Lee, Hyun-Ho Choi
Energy efficiency is an important performance metric for the sustainable operation of energy-limited communication networks. This study investigates an energy-efficient resource allocation strategy to maximize the energy efficiency of wireless-powered bidirectional communication over interference channels. The receivers in the system harvest energy and decode information simultaneously using a time
-
Nefis: A network coding based flexible device-to-device video streaming scheme J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-05-03 Jun Yin, Jiaxin Wen, Ming Zhu, Yulong Li, Lei Wang
Wireless device-to-device (D2D) communication has empowered efficient and convenient video sharing among neighboring devices. However, the mobility and diversity of user devices, combined with dynamically shifting channel conditions, make these processes susceptible to environmental interference. In this paper, we introduce an adaptive network coding scheme tailored for D2D raw source video streaming
-
Resource allocation in Fog–Cloud Environments: State of the art J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-27 Mohammad Zolghadri, Parvaneh Asghari, Seyed Ebrahim Dashti, Alireza Hedayati
The rapid expansion of omnipresent phenomena, exemplified by the Internet of Things (IoT), necessitates significant consideration of data volume and processing requirements. Cloud servers serve as the ultimate destination for IoT data. However, the centralized nature of cloud-based architecture may lead to communication limitations and reduced response times. By placing servers close to the sources
-
A comprehensive survey of smart contract security: State of the art and research directions J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-26 Guangfu Wu, HaiPing Wang, Xin Lai, Mengmeng Wang, Daojing He, Sammy Chan
-
SafeCoder: A machine-learning-based encoding system to embed safety identification information into QR codes J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-25 Hao Su, Jianwei Niu, Xuefeng Liu, Mohammed Atiquzzaman
In social networks, the Internet of Things, mobile computing, electronic commerce, and other fields, Quick Response (QR) codes have been widely used as the interface between online and offline scenarios. In offline lives, users can readily scan QR codes with smartphones to access online networks or remote devices. However, standard QR codes appear as random black-and-white modules that make users difficult
-
Digital twin-driven secured edge-private cloud Industrial Internet of Things (IIoT) framework J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-24 Muna Al-Hawawreh, M. Shamim Hossain
-
Deep Neural Networks meet computation offloading in mobile edge networks: Applications, taxonomy, and open issues J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-24 Ehzaz Mustafa, Junaid Shuja, Faisal Rehman, Ahsan Riaz, Mohammed Maray, Muhammad Bilal, Muhammad Khurram Khan
Mobile Edge Computing (MEC) is a modern paradigm that involves moving computing and storage resources closer to the network edge, reducing latency, and enabling innovative, delay-sensitive applications. Within MEC, computation offloading refers to the process of transferring computationally intensive tasks or processes from mobile devices to edge servers, optimizing the performance of mobile applications
-
An efficient mechanism for function scheduling and placement in function as a service edge environment J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-22 Sahar Pilevar Moakhar, Saeid Abrishami
With the advancement of Internet of Things (IoT) applications and the substantial surge in associated traffic, coupled with the rise in demand for low-latency mobile applications, the utilization of remote cloud computing infrastructure has encountered notable challenges. As a solution, edge computing has emerged, decentralizing computational resources closer to data sources. This results in quicker
-
Edge caching and computing of video chunks in multi-tier wireless networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-22 Dongjae Kim, Dong-Wook Seo, Minseok Choi
This paper proposes a video caching and transcoding strategy for delay-constrained content delivery in multi-tier wireless networks. Particularly for multimedia services whose content can be encoded into multiple quality versions and consists of multiple chunks, we present an approach of caching chunks of an identical file separately in different network layers with different qualities. Given this
-
Exploring the integration of edge computing and blockchain IoT: Principles, architectures, security, and applications J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-22 Tri Nguyen, Huong Nguyen, Tuan Nguyen Gia
IoT systems are widely used in various applications, including healthcare, agriculture, manufacturing, and smart cities. However, these systems still have limitations, such as lack of security, high latency, energy inefficiency, the inefficiency of bandwidth utilization, and shortage of automaticity. The integration of edge computing and blockchain into IoT has been proposed to address these limitations
-
Flow optimization strategies in data center networks: A survey J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-21 Yong Liu, Tianyi Yu, Qian Meng, Quanze Liu
-
Efficient cloud data center: An adaptive framework for dynamic Virtual Machine Consolidation J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-20 Seyyed Meysam Rozehkhani, Farnaz Mahan, Witold Pedrycz
Cloud computing is a thriving and ever-expanding sector in the industry world. This growth has sparked increased interest from organizations seeking to harness its potential. However, the sheer volume of services and offerings in this field has resulted in a noticeable surge in related data. With the rapid evolution and growing demand, cloud computing resource management faces a fresh set of challenges
-
An ensemble maximal feature subset selection for smartphone based human activity recognition J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2024-04-15 S. Reshmi, E. Ramanujam
Smartphone-based Human Activity Recognition (HAR) uses spatiotemporal time series data collected from a smartphone’s in-built accelerometer, gyroscope, and magnetometer sensor. Real-time HAR datasets such as UCI-HAR and UCI-HAPT extract time and frequency domain statistical features for activity recognition from the collected time series signals. Various Machine Learning techniques have been proposed