Advanced Handover Management In Future Wireless Networks Using Prediction Of Qos

Advanced Handover Management in Future Wireless Networks Using Prediction of QoS

Traffic and QoS Management in Wireless Multimedia Networks

The current book provides a final report of activity performed by the COST 290 Action, ‘‘Traffic and QoS Management in Wireless Multimedia Networks,’’ which ran from March 10, 2004, until June 3, 2008. After an introduction to the COST framework and the Action’s survey time-frame and activities, the main part of the book addresses a number of technical issues, which are structured into several chapters. All those issues have been carefully investigated by the COST 290 community during the course of the project – the information presented in this book can be regarded as ultimate for each particular topic; every open research issue addressed in the book is described carefully, corresponding existing studies are analyzed and results achieved by the COST 290 community are presented and compared, and further research directions are defined and analyzed. Because the book covers a wide area of research addressing issues of modern wired and wireless networking at different layers, starting from the physical layer up to the application layer, it can be recommended to be used by researchers and students to obtain a comprehensive analysis on particular research topics including related areas, to obtain broad and ultimate referencing, and to be advised on current open issues. COST 290 is one of the Actions of the European COST Program. Founded in 1971, COST is an intergovernmental framework for European Cooperation in the field of Scientific and Technical Research, allowing the coordination of nationally funded research on a European level.

A RELIABLE HANDOFF MECHANISM FOR ENERGY EFFICIENT INTERNET-OF-THINGS WIRELESS SENSORS NETWORK

Enhancing Seamless Connectivity and Intelligent Resource Allocation for Next-Generation IoT Systems The explosive growth of smart applications and Internet of Things (IoT) devices demands a future-ready communication framework that delivers high bandwidth, ultra-low latency, seamless handovers, and optimized resource usage. This book presents a comprehensive solution to mobility management and network resource optimization through the integration of LTE sub-6 GHz and mmWave technologies—a crucial step in building reliable and high-performance heterogeneous wireless networks (HWNs). Addressing key challenges such as beam coverage issues, interference, and energy-efficient handovers, this research introduces: The Mobility Aware Handover Execution (MAHE) algorithm using the XGBoost machine learning model, achieving significant improvements in handover success rate, reduced signaling overhead, and better throughput. The Resource Optimized Network Selection (RONS) method, designed to minimize handover failures and enhance Quality of Experience (QoE) through intelligent, load-balanced resource allocation for users of varying priorities. Through detailed experiments and analysis, the book demonstrates how machine learning-based models can revolutionize connectivity in dynamic, real-time IoT environments—making it essential reading for researchers, engineers, and practitioners in the fields of wireless communications, network management, and smart IoT infrastructure. Key Topics Covered: LTE-mmWave handover optimization Machine learning-based prediction for handover success Energy-efficient mobility support for IoT Load balancing and QoS/QoE trade-offs in HWNs Interference-aware resource selection techniques