Results 81 to 90 of about 292,632 (247)
Real-life performance of protocol combinations for wireless sensor networks [PDF]
, 2010 Wireless sensor networks today are used for many and diverse applications like nature monitoring, or process and wireless building automation. However, due to the limited access to large testbeds and the lack of benchmarking standards, the real-life ...
De Poorter, Eli +4 more
core +2 more sources
Information Systems Journal, EarlyView.ABSTRACT The recent rise of Generative Artificial Intelligence (GenAI) is fundamentally changing the way businesses operate, with many now investing heavily in this technology. However, businesses are still exploring ways to extract value from GenAI and develop organisational capabilities.
Ashish Jagdish Sharma +4 more
wiley +1 more source
The effects of qos level degradation cost on provider selection and task allocation model in telecommunication networks [PDF]
, 2010 Firms acquire network capacity from multiple suppliers which offer different Quality of Service (QoS) levels. After acquisition, day-to-day operations such as video conferencing, voice over IP and data applications are allocated between these acquired ...
Kasap, Nihat +4 more
core +1 more source
Robust Linear Precoder Design for Multi-cell Downlink Transmission
, 2010 Coordinated information processing by the base stations of multi-cell wireless networks enhances the overall quality of communication in the network. Such coordinations for optimizing any desired network-wide quality of service (QoS) necessitate the base
Prasad, Narayan +2 more
core +1 more source
QoS-LI: QoS Loss Inference in Disadvantaged Networks [PDF]
21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007 Quality of Service (QoS) of disadvantaged networks is considered from a purely network standpoint in existing works. Adversarial intervention in such networks is not analyzed, nor is it possible to infer if a QoS loss is benign or otherwise. In this paper, we present a QoS loss inference module, where the end nodes can infer the nature of a QoS loss in
Vidyaraman Sankaranarayanan +2 more
openaire +1 more source
An Overview of Deep Learning Techniques for Big Data IoT Applications
International Journal of Communication Systems, Volume 39, Issue 4, 10 March 2026.Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur +2 more
wiley +1 more source
Communications, 2017 Broadband telecommunication networks are the future of communication and distribution of multimedia services. Thanks to the high transmission potential and capacity of optical fibres, the optical networks are predestined to be more widely used in ...
Jan Latal +4 more
doaj +1 more source
Tourism Resource Management and Optimization Based on Internet of Things Edge Computing
Engineering Reports, Volume 8, Issue 3, March 2026.Tourism is a major driver of economic growth, contributing to local economies while promoting cultural exchange and environmental awareness. Tourism resource management plays a crucial role in optimizing the efficiency and sustainability of tourism destinations.
Yuli Kan
wiley +1 more source
A Comprehensive Study of the Enhanced Distributed Control Access (EDCA) Function [PDF]
, 2006 This technical report presents a comprehensive study of the Enhanced Distributed Control Access (EDCA) function defined in IEEE 802.11e. All the three factors are considered.
Hou, Jennifer C., Hu, Chunyu
core
Satisfaction Equilibrium: A General Framework for QoS Provisioning in Self-Configuring Networks
, 2010 This paper is concerned with the concept of equilibrium and quality of service (QoS) provisioning in self-configuring wireless networks with non-cooperative radio devices (RD).
Debbah, Merouane +3 more
core +3 more sources