Related papers: Impact of User Privacy and Mobility on Edge Offloa…
Edge computing is the practice of placing computing resources at the edges of the Internet in close proximity to devices and information sources. This, much like a cache on a CPU, increases bandwidth and reduces latency for applications but…
The importance of human mobility analyses is growing in both research and practice, especially as applications for urban planning and mobility rely on them. Aggregate statistics and visualizations play an essential role as building blocks…
A method for optimizing encryption mechanism and resource allocation based on edge computing environment is proposed. A local differential privacy algorithm based on a histogram algorithm is used to protect user information during task…
Mobile edge computing facilitates users to offload computation tasks to edge servers for meeting their stringent delay requirements. Previous works mainly explore task offloading when system-side information is given (e.g., server…
With the pervasiveness of IoT devices, smart-phones and improvement of location-tracking technologies huge volume of heterogeneous geo-tagged (location specific) data is generated which facilitates several location-aware services. The…
We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices,…
In this article, we evaluate the first experience of computation offloading from drones to real fifth-generation (5G) operator systems, including commercial and private carrier-grade 5G networks. A follow-me drone service was implemented as…
Mobile devices have become an indispensable component of Internet of Things (IoT). However, these devices have resource constraints in processing capabilities, battery power, and storage space, thus hindering the execution of…
Users care greatly about preserving the privacy of their personal data gathered during their use of information systems. This extends to both the data they actively provide in exchange for services as well as the metadata passively…
We present procedures that exploit mobility prediction and prefetching to enhance offloading of traffic from mobile networks to WiFi hotspots, for both delay tolerant and delay sensitive traffic. We evaluate the procedures in terms of the…
Computation offloading is indispensable for mobile edge computing (MEC). It uses edge resources to enable intensive computations and save energy for resource-constrained devices. Existing works generally impose strong assumptions on radio…
The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and provide some services, such as personalized offers, through…
Sharing location traces with context-aware service providers has privacy implications. Location-privacy preserving mechanisms, such as obfuscation, anonymization and cryptographic primitives, have been shown to have impractical…
Multi-access edge computing (MEC) emerges as an essential part of the upcoming Fifth Generation (5G) and future beyond-5G mobile communication systems. It adds computational power towards the edge of cellular networks, much closer to…
Caching popular content at mobile devices, accompanied by device-to-device (D2D) communications, is one promising technology for effective mobile content delivery. User mobility is an important factor when investigating such networks, which…
The integration of Large Language Models (LLMs) in 6G vehicular networks promises unprecedented advancements in intelligent transportation systems. However, offloading LLM computations from vehicles to edge infrastructure poses significant…
The evolving landscape of edge computing envisions platforms operating as dynamic intermediaries between application providers and edge servers (ESs), where task offloading is coupled with payments for computational services. Ensuring…
While mobile edge computing (MEC) alleviates the computation and power limitations of mobile devices, additional latency is incurred when offloading tasks to remote MEC servers. In this work, the power-delay tradeoff in the context of task…
In this paper, we consider user location privacy in mobile edge clouds (MECs). MECs are small clouds deployed at the network edge to offer cloud services close to mobile users, and many solutions have been proposed to maximize service…
Multi-access edge computing (MEC) is a promising solution for providing the computational resources and low latency required by vehicular services such as autonomous driving. It enables cars to offload computationally intensive tasks to…