Research ArticleOpen accessIn the keywordsMulti-Satellite Custody of Moving Ground TargetsDavid SchusterMaintaining persistent custody of ground targets from Low Earth Orbit (LEO) is a key challenge in space-based surveillance and reconnaissance. Traditional rule-based tasking strategies struggle with scalability as the number of assets and targets grows. In this paper, we present a centralized Reinforcement Learning (RL) approach using Proximal Policy Optimization (PPO) to coordinate four LEO satellites tasked with tracking two … …Journal of Computer Science, Vol. 22, Issue 3 · 25 Mar 2026 · 1,575 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAdaptive Cybersecurity: Dynamically Retrainable Firewalls for Real-Time Network ProtectionSina AhmadiThe growing complexity of cyberattacks has necessitated the evolution of firewall technologies from static models to adaptive, machine learning-driven systems. This research introduces “Dynamically Retrainable Firewalls”, which respond to emerging threats in real-time. Unlike traditional firewalls that rely on static rules to inspect traffic, these advanced systems leverage machine learning algorithms to analyze network traffic patterns dynamically and identify threats. … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,558 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEnhancing Telecommunication Network Management with Autonomous Optimization Agents and Machine LearningDanny Adil Sibarani, Evaristus Didik MadyatmadjaThis study explores the integration of Machine Learning (ML) and Autonomous Optimization Agents (AOAs) in the management and optimization of Radio Access Networks (RAN). The research addresses the growing challenges posed by the need for skilled network experts capable of managing and analyzing large-scale network data, including Key Performance Indicators (KPIs) and thousands of network configuration parameters. To overcome these … …Journal of Computer Science, Vol. 21, Issue 2 · 4 Mar 2025 · 7,041 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHuman-Centric Design Integration in UAV Interfaces and Operational Procedures for Enhanced User ExperienceArun Chakravarthy R., Arun M., Sureshkumar C. et al.Unmanned Aerial Vehicles (UAVs) have become essential tools across numerous sectors, including agriculture, disaster response, search and rescue and logistics. While UAV capabilities have rapidly evolved due to technological advancements, the integration of human-centric design principles remains a key area for further improvement. This article provides an in-depth exploration of how user-focused design considerations can enhance UAV interfaces and operational … …Journal of Computer Science, Vol. 21, Issue 4 · 3 Mar 2025 · 5,237 accessesView PDFCite
Research ArticleOpen accessIn the keywordsRoute Optimization using Hybrid GRU Learning Model for SDN and Edge-Based VANET TopologySavitha Kumar, Chandrasekar ChinnasamyIntelligent Transportation System (ITS) offersoutstanding features, including security applications and emergency alerts.Unfortunately, ITS limits traffic control services, adaptability, andadjustability due to the traffic volume. Hence, expanding the standard VehicularAd hoc Networks (VANET) framework is a requirement. As a result, in the latestdays, the concept of Software-Defined Networking based Vehicular Ad hocNetworks (SDN-VANETs) has drawn considerable attention, creating VANETssmarter. The SDN-VANETs … …Journal of Computer Science, Vol. 18, Issue 8 · 26 Aug 2022 · 6,160 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTransfer Learning in Attack Avoidance GamesEdwin Torres, Fernando LozanoTransfer knowledge is a human characteristic that has been replicated in machine learning algorithms to improve learning performance measures. However, little success has been accomplished in reinforcement learning tasks when a function approximation is needed to estimate the value functions. In this study, we present a new strategy to facilitate knowledge transfer when an agent is learning to solve a … …Journal of Computer Science, Vol. 16, Issue 10 · 13 Nov 2020 · 6,577 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Q-Routing Protocol Using Self-Aware Approach for Mobile Ad hoc NetworksAmal Alharbi, Abdullah Al-Dhalaan, Miznah Al-RodhaanMobile Ad hoc Networks (MANET) are self-organized networks that are characterized by dynamic topologies in time and space. This creates an instable environment, where classical routing approaches cannot achieve high performance. Thus, adaptive routing is necessary to handle the challenges in MANETs. Furthermore, it is necessary for nodes to be self-aware i.e., able to discover neighbors, links and paths when … …American Journal of Applied Sciences, Vol. 12, Issue 12 · 7 Dec 2015 · 6,463 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHybrid Optimize Strategy based QoS Route Algorithm for Mobile Ad hoc NetworksFu Peng, Zhang DeyunIt is very difficult to find feasible QoS (Quality of service) routes in the mobile ad hoc networks (MANETs), because of the nature constrains of it, such as dynamic network topology, wireless communication link and limited process capability of nodes. In order to reduce average cost in flooding path discovery scheme of the traditional MANETs routing protocols and increase the … …Journal of Computer Science, Vol. 2, Issue 2 · 28 Feb 2006 · 6,546 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSeek of an Optimal Way by Q-LearningY. Dahmani, A. BenyettouIn this article, we presented the Q-Learning training method which is a derivative of the reinforcement learning called sometimes training by penalty-reward. We illustrate this by an application to the mobility of a mobile in an enclosure closed on the basis of a starting point towards an unspecified arrival point. The objective is to find an optimal way optimal without … …Journal of Computer Science, Vol. 1, Issue 1 · 31 Mar 2005 · 6,929 accessesView PDFCite
Research ArticleOpen accessIn the keywordsQ-Optimizer: An AI-Based Optimization Framework for Efficient SDN Routing and QoS EnhancementDeepthi Goteti, Vurrury Krishna ReddyWith their rigid layers, traditional networks do not meet evolving traffic demands. As a result, they tend to face congestion along with un-optimized routing. SDN controls traffic management by introducing a programmable control plane, enabling dynamic and intelligent network management. However, older routing techniques, such as Dijkstra's and Multipath, suffer from low adaptability, leading to a rise in latency and … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,227 accessesView PDFCite