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Mobile computing at the edge (keynote)

Proceedings of the 1st International Conference on Mobile Software Engineering and Systems, 2014
As sales of mobile devices grow and smartphones and tablets become for many the preferred way of interacting with the Internet, social media and the enterprise, organizations are striving to push content and functionality out to mobile users. However, mobile devices still do not have the computing power and battery life that will allow them to perform ...
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Learning for Computation Offloading in Mobile Edge Computing

IEEE Transactions on Communications, 2018
Mobile edge computing (MEC) is expected to provide cloud-like capacities for mobile users (MUs) at the edge of wireless networks. However, deploying MEC systems faces many challenges, one of which is to achieve an efficient distributed offloading mechanism for multiple users in time-varying wireless environments.
Thinh Quang Dinh   +3 more
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Cognitive Service in Mobile Edge Computing

2020 IEEE International Conference on Web Services (ICWS), 2020
Cognitive services have revolutionized the way we live, work and interact with the world. In recent years, deep neural networks have become the mainstream approach in cognitive service, and mobile edge computing facilitates a variety of cognitive services for users by offloading computation tasks from resource-limited mobile devices to relatively ...
Chuntao Ding   +3 more
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Towards Flying Mobile Edge Computing

2020 International Conference on Information Networking (ICOIN), 2020
With the development of mobile edge computing (MEC), many approaches are proposed to improve the computation performances, such as network congestion, transmission latency, and quality of Internet of Things (IoTs) services. Although ground MEC system architectures are developed, there are still unsolved problems, such as depending on the ground ...
Ngo Thien Thu   +5 more
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Energy-Efficient Mobile Edge Hosts for Mobile Edge Computing System

2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), 2018
Mobile edge computing is emerging as the new solution for next generation mobile applications, which require very low latency and high computing resources. By offloading the computation intensive tasks to mobile edge (ME) hosts located in the radio access network, users could gain energy saving benefits at the user equipment.
Shanmuganathan Thananjeyan   +3 more
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Mobile computing at the edge

Proceedings of the 2013 ACM workshop on Mobile development lifecycle, 2013
Edge environments, such as those in which first responders and military personnel operate in, are characterized by dynamic context, limited computing resources, intermittent network connectivity, and high levels of stress. First responders and soldiers can use handheld devices in these environments to help with tasks such as speech and image ...
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Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing

2017 Global Internet of Things Summit (GIoTS), 2017
When it comes to storage and computation of large scales of data, Cloud Computing has acted as the de-facto solution over the past decade. However, with the massive growth in intelligent and mobile devices coupled with technologies like Internet of Things (IoT), V2X Communications, Augmented Reality (AR), the focus has shifted towards gaining real-time
Soumya Kanti Datta, Koustabh Dolui
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Adaptive Replication for Mobile Edge Computing

IEEE Journal on Selected Areas in Communications, 2018
Mobile edge computing (MEC) has been proposed to complement the limitations of cloud computing. Allocating replicas in MEC servers can shorten transmission latency and improve the quality of service (QoS). However, cloud-based replication schemes may not be suitable for MEC servers due to their limited resources and the varied traffic in RANs.
Wan-Chi Chang, Pi-Chung Wang
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Molecular imaging in oncology: Current impact and future directions

Ca-A Cancer Journal for Clinicians, 2022
Martin G Pomper, Steven P Rowe
exaly  

Emerging 2D Memory Devices for In‐Memory Computing

Advanced Materials, 2021
Jun He, Ruiqing Cheng, Qisheng Wang
exaly  

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