相关论文: Decentralized Edge-to-Cloud Load-balancing: Servic…

The heterogeneous and distributed nature of the Internet of Things (IoT) is driving the need for extremely fast and fine-grained service provisioning in 5/5+G architectures and beyond. To meet these needs, it is critical to enable efficient…

Emerging technologies that generate a huge amount of data such as the Internet of Things (IoT) services need latency aware computing platforms to support time-critical applications. Due to the on-demand services and scalability features of…

Fog computing emerged as a promising paradigm to address the challenges of processing and managing data generated by the Internet of Things (IoT). Load balancing (LB) plays a crucial role in Fog computing environments to optimize the…

The rapid proliferation of latency-sensitive and battery-constrained Internet-of-Things (IoT) applications has intensified the need for intelligent workload placement mechanisms across the Edge-Cloud computing continuum. In such…

For effective use of edge computing in an IoT application, we need to partition the application into tasks and map them into the cloud, fog (edge server), device levels such that the resources at the different levels are optimally used to…

Resource management is the principal factor to fully utilize the potential of Edge/Fog computing to execute real-time and critical IoT applications. Although some resource management frameworks exist, the majority are not designed based on…

Edge computing is a distributed computing paradigm that relies on computational resources of end devices in a network to bring benefits such as low bandwidth utilization, responsiveness, scalability and privacy preservation. Applications…

Novel Internet of Things (IoT) requirements derived from a broader interconnection of heterogeneous devices have pushed the horizons of Cloud computing and are giving rise to a wider decentralisation of applications and data centers. An…

Internet of Things (IoT) is a system of interrelated devices that can be used to allow large-scale collection and analysis of data. However, as it grew, IoT networks were not capable of managing the data from these services. As a result,…

Distributed fog and edge applications communicate over unreliable networks and are subject to high communication delays. This makes using existing distributed coordination technologies from cloud applications infeasible, as they are built…

Internet of Things and cloud computing are two technological paradigms that reached widespread adoption in recent years. These paradigms are complementary: IoT applications often rely on the computational resources of the cloud to process…

Fog computing is essentially the expansion of cloud computing towards the network edge, reducing user access time to computing resources and services. Various advantages attribute to fog computing, including reduced latency, and improved…

The number of Internet of Things (IoT) applications, especially latency-sensitive ones, have been significantly increased. So, Cloud computing, as one of the main enablers of the IoT that offers centralized services, cannot solely satisfy…

Mobile devices supporting the "Internet of Things" (IoT), often have limited capabilities in computation, battery energy, and storage space, especially to support resource-intensive applications involving virtual reality (VR), augmented…

This paper addresses the escalating challenges posed by the ever-increasing data volume, velocity, and the demand for low-latency applications, driven by the proliferation of smart devices and Internet of Things (IoT) applications. To…

Cloud computing has grown to become a popular distributed computing service offered by commercial providers. More recently, Edge and Fog computing resources have emerged on the wide-area network as part of Internet of Things (IoT)…

With the recent considerable developments in the Internet of Things (IoT), billions of resource-constrained devices are interconnected through the internet. Monitoring this huge number of IoT devices that are heterogeneous in terms of…

The exponential growth of Internet of Things (IoT) devices has intensified the demand for efficient and responsive services. To address this demand, fog and edge computing have emerged as distributed paradigms that bring computational…

To address the increased latency, network load and compromised privacy issues associated with the Cloud-centric IoT applications, fog computing has emerged. Fog computing utilizes the proximal computational and storage devices, for sensor…

With rapid technological advancements within the domain of Internet of Things (IoT), strong trends have emerged which indicate a rapid growth in the number of smart devices connected to IoT networks and this growth cannot be supported by…