相关论文: A Study to Optimize Heterogeneous Resources for Op…
The IoT's explosive growth has led to a massive number of connected devices, which demand high-speed and pervasive connectivity, posing significant challenges for current-generation wireless communication infrastructures. Considering our…
As the number of Internet of Things (IoT) devices keeps increasing, data is required to be communicated and processed by these devices at unprecedented rates. Cooperation among wireless devices by exploiting Device-to-Device (D2D)…
Besides enabling an enhanced mobile broadband, next generation of mobile networks (5G) are envisioned for the support of massive connectivity of heterogeneous Internet of Things (IoT)s. These IoTs are envisioned for a large number of…
Fog computing significantly enhances the efficiency of IoT applications by providing computation, storage, and networking resources at the edge of the network. In this paper, we propose a federated fog computing framework designed to…
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems to robotics control and military surveillance. This is driven by…
The rapid deployment of Internet of Things (IoT) applications leads to massive data that need to be processed. These IoT applications have specific communication requirements on latency and bandwidth, and present new features on their…
The goal of this dissertation is to design efficient data aggregation frameworks for massive IoT networks in different scenarios to support the proper functioning of IoT analytics layer. This dissertation includes modern algorithmic…
The adoption of the Internet of Things (IoT) deployments has led to a sharp increase in network traffic as a vast number of IoT devices communicate with each other and IoT services through the IoT-edge-cloud continuum. This network traffic…
This paper investigates a three-layer IoT-fog-cloud computing system to determine the optimum workload and power allocation at each layer. The objective is to minimize maximum per-layer latency (including both data processing and…
The Internet of Things (IoT) refers to a pervasive presence of interconnected and uniquely identifiable physical devices. These devices' goal is to gather data and drive actions in order to improve productivity, and ultimately reduce or…
With the growing demand for latency-critical and computation-intensive Internet of Things (IoT) services, the IoT-oriented network architecture, mobile edge computing (MEC), has emerged as a promising technique to reinforce the computation…
Today's needs for monitoring and control of different devices in organizations require an Internet of Things (IoT) platform that can integrate heterogeneous elements provided by multiple vendors and using different protocols, data formats…
With the remarkable growth of the Internet and communication technologies over the past few decades, Internet of Things (IoTs) is enabling the ubiquitous connectivity of heterogeneous physical devices with software, sensors, and actuators.…
The emergence of new services and applications in emerging wireless networks (e.g., beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) in the Internet of Things (IoT). However, the proliferation of…
Large-scale Internet of Things (IoT) networks enable intelligent services such as smart cities and autonomous driving, but often face resource constraints. Collecting heterogeneous sensory data, especially in small-scale datasets, is…
Internet of Things (IoT) is an Internet-based environment of connected devices and applications. IoT creates an environment where physical devices and sensors are flawlessly combined into information nodes to deliver innovative and smart…
With the advent of the Internet-of-Things (IoT) era, the ever-increasing number of devices and emerging applications have triggered the need for ubiquitous connectivity and more efficient computing paradigms. These stringent demands have…
The significance of distributed learning and inference algorithms in Internet of Things (IoT) network is growing since they flexibly distribute computation load between IoT devices and the infrastructure, enhance data privacy, and minimize…
This research introduces a revolutionary paradigm for HetNet management, presenting an innovative algorithmic framework that transcends traditional notions of network capacity enhancement. Our exploration delves into the intricate interplay…
An increasing amount of data is being injected into the network from IoT (Internet of Things) applications. Many of these applications, developed to improve society's quality of life, are latency-critical and inject large amounts of data…