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OL-EUA: Online User Allocation for NOMA-Based Mobile Edge Computing
IEEE Transactions on Mobile Computing, 2023Mobile edge computing (MEC) raises a variety of new challenges for app vendors, including the Edge User Allocation (EUA) problem. EUA aims to allocate as many app users as possible in an MEC system to minimum edge servers in the system. In non-orthogonal
Guangming Cui +6 more
semanticscholar +1 more source
Reinforcement Learning Based Energy-Efficient Collaborative Inference for Mobile Edge Computing
IEEE Transactions on Communications, 2023Collaborative inference in mobile edge computing (MEC) enables mobile devices to offload the computation tasks for the computation-intensive perception services, and the inference policy determines the inference latency and energy consumption.
Yilin Xiao +6 more
semanticscholar +1 more source
A Middleware for Mobile Edge Computing
IEEE Cloud Computing, 2017Telecom operators have recently started to deploy massive computing and storage resources at the very edge of their access networks, hence evolving their infrastructures into large, distributed, and capillary computing environments, capable of placing applications very close to users and terminals and well-suited to effectively fulfill the challenging ...
Carrega A. +3 more
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Dynamic Task Scheduling in Cloud-Assisted Mobile Edge Computing
IEEE Transactions on Mobile Computing, 2023The cloud-assisted mobile edge computing system is a critical architecture to process computation-intensive and delay-sensitive mobile applications in close proximity to mobile users with high resource efficiency. Due to the heterogenous dynamics of task
Xiao Ma +5 more
semanticscholar +1 more source
2017
Paradigms of ubiquitous IoT coupled with strong context-aware data access controls are a must for the success of Health 4.0. These together with the inherent requirement of adhering to strict QoS guarantees in the health domain create a technologically challenging environment which can be effectively addressed through novel platforms.
Karthikeyan Ganesan, Swaroop Nunna
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Paradigms of ubiquitous IoT coupled with strong context-aware data access controls are a must for the success of Health 4.0. These together with the inherent requirement of adhering to strict QoS guarantees in the health domain create a technologically challenging environment which can be effectively addressed through novel platforms.
Karthikeyan Ganesan, Swaroop Nunna
openaire +4 more sources
Location Privacy Protection via Delocalization in 5G Mobile Edge Computing Environment
IEEE Transactions on Services Computing, 2023In the past several years, we have witnessed a variety of mechanisms for protecting mobile users’ location privacy, e.g., k-anonymity, cloaking, encryption, etc. Unfortunately, existing techniques suffer from a common limitation - mobile users’ locations
Guangming Cui +5 more
semanticscholar +1 more source
Game Theoretical Task Offloading for Profit Maximization in Mobile Edge Computing
IEEE Transactions on Mobile Computing, 2023In this paper, a novel task offloading architecture called Flex-MEC is proposed, which achieves efficient task allocation and scheduling (TAS) between MEC servers.
Haojun Teng +5 more
semanticscholar +1 more source
A survey on mobile edge computing
2016 10th International Conference on Intelligent Systems and Control (ISCO), 2016Mobile Edge Computing is an emerging technology that provides cloud and IT services within the close proximity of mobile subscribers. Traditional telecom network operators perform traffic control flow (forwarding and filtering of packets), but in Mobile Edge Computing, cloud servers are also deployed in each base station.
Ejaz Ahmed, Arif Ahmed
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IEEE Transactions on Industrial Informatics, 2022
The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).
Ryan Wen Liu +6 more
semanticscholar +1 more source
The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).
Ryan Wen Liu +6 more
semanticscholar +1 more source
Multi-Agent Deep Reinforcement Learning for Task Offloading in UAV-Assisted Mobile Edge Computing
IEEE Transactions on Wireless Communications, 2022Mobile edge computing can effectively reduce service latency and improve service quality by offloading computation-intensive tasks to the edges of wireless networks.
Nan Zhao +4 more
semanticscholar +1 more source