شماره ركورد
15246
عنوان
بررسي تعادل بار تطبيقي در شبكههاي دريايي مبتني بر SDN: رويكردي آگاه از كيفيت سرويس (QoS) براي ارتباطات كشتي به ساحل
سال تحصيل
1403
استاد راهنما
دكتر مرتضى ملاجعفري
چکيده
The marine Internet of Things (MIoT), Maritime Autonomous Surface Ships (MASS), and the need for real time data interchange in operations are all driving a big digital transition in the marine industry. These new technologies put unprecedented demands on Maritime Communication Networks (MCNs), which must deliver dependable, high capacity, and low
latency connectivity across a wide range of situations, including SATCOM, coastal LTE/5G, and Wi Fi/WiMAX. Traditional static load balancing approaches, like round robin or weighted distribution, donʹt work well in these dynamic and unpredictable settings because they donʹt adjust to changing connection conditions and different Quality of Service (QoS) needs. This presentation talks about adaptable and intelligent load balancing solutions, with a focus on how Software Defined Networking (SDN) may help with centralized programmability and real time traffic management. We critically look at many methods, from fuzzy logic and latency aware optimization to advanced machine learning and reinforcement learning frameworks. The results show that adaptive systems are better at making the most of resources, making sure QoS, and enabling safety critical applications like remote piloting and autonomous vessel navigation. The seminar finally finds important research gaps, such as the lack of frameworks that are particular to maritime issues and the lack of empirical validation. It also suggests ways to improve next
generation maritime networks by creating strong, QoS aware adaptive load balancing solutions.
نام دانشجو
فيصل الحمراني
تاريخ ارائه
10/29/2025 12:00:00 AM
متن كامل
88002
پديد آورنده
فيصل الحمراني
تاريخ ورود اطلاعات
1404/08/08
عنوان به انگليسي
Review of Adaptive Load Balancing in SDN Based Maritime Networks: A QoS Aware Approach for Ship to Shore Communications
كليدواژه هاي لاتين
Maritime Communication Networks (MCNs), , Software Defined Networking (SDN), , Adaptive Load Balancing , Quality of Service (QoS), , Reinforcement Learning (RL)