Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

53 results for “Internet Traffic”
Set a search alert
Research ArticleOpen accessPhrase in the titleANALYSIS OF INTERNET TRAFFIC IN EDUCATIONAL NETWORK BASED ON USERS’ PREFERENCESMustafa M.H. Ibrahim, Mohd Hasbullah Omar, Adib M. Monzer Habbal, Khuzairi Mohd ZainiThe demand for Internet services and network resources in Educational networks are increasing rapidly. Specifically, the revolution of web 2.0 "also referred to as the Read-Write Web" has changed the way of information exchange and distribution. Although web 2.0 has gained attraction in all sectors of the education industry, but it results in high-traffic loads on networks which often leads … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 6,962 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Forager Bee's Intelligence Inspired Dynamic Queue Scheduling for the Internet TrafficY. Suresh, S. Arumugam, M. A. BhagyaveniProblem statement: In the present evolution of large scale internet communication, per flow control scheme faces scalability issue due to tremendous number of flows. The aggregation based approaches such as differentiated architecture relieve the storage of state of flows in core router. TCP is the dominating protocol that carries majority of the total internet traffic. Recent internet traffic measurement shows … …Journal of Computer Science, Vol. 8, Issue 5 · 22 Feb 2012 · 7,011 accessesView PDFCite
Review ArticleOpen accessIn the keywordsA Succinct Review on Identification of Network Anomalies and Protection in Cyber-Physical SystemsShalini Kumari, Chander Prabha, Prakash Srivastava et al.Advanced cyberattacks outperform traditional threat detection methods in the rapidly expanding cybersecurity field. Advanced Machine Learning (ML) algorithms can detect network traffic and system problems using AI-based Anomaly Detection (AD) for cybersecurity in real-time. Signature-based systems may overlook new and subtle threats. This paper examines Artificial Intelligence (AI) driven AD systems' design, methodology, and efficacy. The process includes data preprocessing … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,234 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intrusion Detection Framework for MEC-Enabled IoT NetworksRofaida Tawfik, Abdelfattah Hegazy, Hesham Dahshan, Ahmed Gaber AbuabdallahMobile Edge Computing (MEC) has emerged as a promising paradigm for supporting latency-sensitive Internet of Things (IoT) applications by bringing computational resources closer to data sources. However, the distributed nature of MEC environments increases exposure to network-based security threats, particularly network intrusions that can impact both system reliability and task offloading efficiency. This paper proposes a security-aware framework that integrates … …Journal of Computer Science, Vol. 22, Issue 4 · 1 Apr 2026 · 1,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Grey Wolf Optimizer and Deep Transfer Learning-Based Intrusion Detection System for IoTKapil Shrivastava, Manish Tiwari, Prasun ChakrabartiThe rapid proliferation of Internet of Things (IoT) devices has driven significant advancements in connectivity and automation, but it has also introduced substantial cybersecurity risks, including intrusions and cyberattacks. To address these challenges, this study proposes a hybrid intrusion detection framework that combines advanced optimization techniques with ensemble deep learning to enhance detection accuracy and computational efficiency. The proposed framework … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,506 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Optimized Multi-Layer Perceptron Framework for Detecting and Classifying IoT AttacksSanchit Vashisht, Shalli RaniThe Internet of Things (IoT) is revolutionizing industries by connecting billions of smart devices, enabling automation and information exchange. The expansion of IoT ecosystems has simultaneously increased the surface area for cyberattacks. These environments are particularly vulnerable to a wide range of threats, such as Distributed Denial-of-Service (DDoS), poisoning, brute-force SSH intrusions, and various network reconnaissance techniques. The dynamic nature … …Journal of Computer Science, Vol. 21, Issue 12 · 11 Feb 2026 · 1,333 accessesView PDFCite
Research ArticleOpen accessIn the abstractAlternative Monitoring Approach for IPTVAngel Ignatov, Hristo Toshkov Hristov, Jan Latal et al.IPTV emerged in the late 1990s as a solution for delivering Video on Demand (VoD) and live television over managed networks. Its widespread adoption accelerated after the expansion of broadband internet and the introduction of web technologies such as HTML5 and adaptive streaming protocols (MPEG-DASH and HLS), which enabled television content to be streamed directly through web browsers. Across Europe, … …Journal of Computer Science, Vol. 22, Issue 11 · 8 Oct 2026 · 430 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrioritized Experience Replay-Based Deep Deterministic Policy Gradient for Reliable Path Selection in SDN-IoT NetworksGaurav Kumar, G. S. Girisha, N. ShamanthRouting optimization is becoming prominent in Software-Defined Networks (SDN) due to the exponential growth of network traffic demands and the requirement for Quality of Service (QoS). However, reliable routing that satisfies the QoS requirements, such as end-to-end delay, packet loss, and bandwidth, remains a difficult task in SDN. To overcome this limitation, a Deep Reinforcement Learning (DRL)-based Prioritized Experience Replay-based … …Journal of Computer Science, Vol. 22, Issue 8 · 4 Aug 2026 · 1,001 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning-Based Traffic Prediction in 4G LTE Networks. Case Study of a Mobile Operator in CameroonEric Michel Deussom Djomadji, Valery Nkemeni et al.Mobile subscribers are increasingly demanding the availability of broadband services while the radio resources allowing them to be connected are limited. Understanding mobile Internet consumption trends and subscriber traffic demands is essential to enable the management of existing radio resources. However, it can be difficult to understand and describe the data usage patterns of mobile users because of the complexity … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 1 Mar 2025 · 8,728 accessesView PDFCite
Research ArticleOpen accessIn the abstractSecuring IoT Networks: Multi-Attack Detection of RPL Routing Threats Using Deep LearningAyoub Krari, Abdelmajid Hajami, Ayoub Toubi, Marouane Ait SaidThe growing frequency of cyber threats in Internet of Things (IoT) networks, including attacks on RPL routing, requires the creation of strong detection systems to safeguard network integrity and provide dependable communication. This study is driven by the pressing necessity to tackle the security weaknesses in IoT networks, where threats such as black holes, version number alteration, DIS flooding, and … …Journal of Computer Science, Vol. 21, Issue 4 · 6 Mar 2025 · 5,397 accessesView PDFCite