Related papers: MOFCO: Mobility- and Migration-Aware Task Offloadi…
The increasing use of Internet of Things (IoT) devices generates a greater demand for data transfers and puts increased pressure on networks. Additionally, connectivity to cloud services can be costly and inefficient. Fog computing provides…
The limited capabilities of user equipment restrict the local implementation of computation-intensive applications. Edge computing, especially the edge intelligence system, enables local users to offload the computation tasks to the edge…
The emergence of the Fog computing paradigm that leverages in-network virtualized resources raises important challenges in terms of resource and IoT application management in a heterogeneous environment offering only limited computing…
Offloading computationally intensive tasks from mobile users (MUs) to a virtualized environment such as containers on a nearby edge server, can significantly reduce processing time and hence end-to-end (E2E) delay. However, when users are…
Fog computing has become an attractive research topic in recent years. As an extension of the cloud, fog computing provides computing resources for Internet of Things (IoT) applications through communicative fog nodes located at the network…
We develop a joint offloading and resource allocation framework for a multi-layer cooperative fog computing network, aiming to minimize the total energy consumption of multiple mobile devices subject to their service delay requirements. The…
This work evaluates three Fog Computing dataplacement algorithms via experiments carried out with theiFogSim simulator. The paper describes the three algorithms(Cloud-only, Mapping, Edge-ward) in the context of an Internetof Things…
Mobile edge computing (MEC) is a new paradigm that provides cloud computing services at the edge of networks. To achieve better performance with limited computing resources, peer offloading between cooperative edge servers (e.g. MEC-…
Fog computing is an emerging distributed computing model for the Internet of Things (IoT). It extends computing and caching functions to the edge of wireless networks. Uncrewed Aerial Vehicles (UAVs) provide adequate support for fog…
This letter investigates a cache-enabled multiuser mobile edge computing (MEC) system with dynamic task arrivals, taking into account the impact of proactive cache placement on the system's overall energy consumption. We consider that an…
Facing the trend of merging wireless communications and multi-access edge computing (MEC), this article studies computation offloading in the beyond fifth-generation networks. To address the technical challenges originating from the…
We propose a game theoretic framework for task allocation in mobile cloud computing that corresponds to offloading of compute tasks to a group of nearby mobile devices. Specifically, in our framework, a distributor node holds a…
In an edge-cloud system, mobile devices can offload their computation intensive tasks to an edge or cloud server to guarantee the quality of service or satisfy task deadline requirements. However, it is challenging to determine where tasks…
Advances in space exploration have led to an explosion of tasks. Conventionally, these tasks are offloaded to ground servers for enhanced computing capability, or to adjacent low-earth-orbit satellites for reduced transmission delay.…
This paper studies the problem of information freshness-aware task offloading in an air-ground integrated multi-access edge computing system, which is deployed by an infrastructure provider (InP). A third-party real-time application service…
This paper studies the potential performance improvement that can be achieved by enabling multi-operator wireless connectivity for cloud/fog computing-connected vehicular systems. Mobile network operator (MNO) selection and switching…
Mobile edge computing (MEC) is a promising paradigm to accommodate the increasingly prosperous delay-sensitive and computation-intensive applications in 5G systems. To achieve optimum computation performance in a dynamic MEC environment,…
As a key technology in the 5G era, Mobile Edge Computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the processing pressure on the core network. MEC can be regarded…
The rapid growth of time-sensitive applications and services has driven enhancements to computing infrastructures. The main challenge that needs addressing for these applications is the optimal placement of the end-users demands to reduce…
Migrating computational intensive tasks from mobile devices to more resourceful cloud servers is a promising technique to increase the computational capacity of mobile devices while saving their battery energy. In this paper, we consider a…