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- surveyApril 2024
Epidemic Model-based Network Influential Node Ranking Methods: A Ranking Rationality Perspective
ACM Computing Surveys (CSUR), Volume 56, Issue 8Article No.: 203, Pages 1–39https://doi.org/10.1145/3653296Existing surveys and reviews on Influential Node Ranking Methods (INRMs) have primarily focused on technical details, neglecting thorough research on verifying the actual influence of these nodes in a network. This oversight may result in erroneous ...
- research-articleAugust 2023
Cross task neural architecture search for EEG signal recognition
AbstractElectroencephalograms (EEGs) are brain dynamics measured outside of the brain, which have been widely utilized in non-invasive brain-computer interface applications. Recently, various neural network approaches have been proposed to improve the ...
- research-articleJuly 2023
Multi-UAV-Assisted Federated Learning for Energy-Aware Distributed Edge Training
IEEE Transactions on Network and Service Management (ITNSM), Volume 21, Issue 1Feb. 2024, Pages 280–294https://doi.org/10.1109/TNSM.2023.3298220Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) has largely extended the border and capacity of artificial intelligence of things (AIoT) by providing a key element for enabling flexible distributed data inputs, computing capacity, and ...
- research-articleMarch 2023
Air-Ground Collaborative Edge Intelligence for Future Generation Networks
IEEE Network: The Magazine of Global Internetworking (IEEENETW), Volume 37, Issue 2March/April 2023, Pages 118–125https://doi.org/10.1109/MNET.008.2200287The air-ground integrated mobile edge computing (MEC) is expected to fulfill the ever-growing resource demands of artificial intelligence (AI)-enabled applications in sixth-generation (6G) wireless networks, ranging from computer vision to natural ...
- research-articleNovember 2020
Service cost-based resource optimization and load balancing for edge and cloud environment
Knowledge and Information Systems (KAIS), Volume 62, Issue 11Nov 2020, Pages 4255–4275https://doi.org/10.1007/s10115-020-01489-6AbstractThe application of edge clouds is becoming more and more widespread. The resource optimization is one of the important research contents of edge cloud. Generally, the edge cloud has limited computing resources and energy. Resource optimization can ...
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- research-articleOctober 2020
Elastic edge cloud resource management based on horizontal and vertical scaling
The Journal of Supercomputing (JSCO), Volume 76, Issue 10Oct 2020, Pages 7707–7732https://doi.org/10.1007/s11227-020-03192-3AbstractThe resources in the edge cloud are numerous and complex, and elastic scaling services can make efficient use of these resources. However, the elastic scaling services need to suspend the user’s application tasks forcibly when carrying out ...
- research-articleFebruary 2020
Load balance based workflow job scheduling algorithm in distributed cloud
Journal of Network and Computer Applications (JNCA), Volume 152, Issue CFeb 2020https://doi.org/10.1016/j.jnca.2019.102518AbstractAs the scale of the geo-distributed cloud increases and the workflow applications become more complex, the system operation is more likely to cause the waste of resources and excessive energy consumption. In this paper, a workflow job ...
- research-articleDecember 2019
Energy efficient computation offloading for nonorthogonal multiple access assisted mobile edge computing with energy harvesting devices
Computer Networks: The International Journal of Computer and Telecommunications Networking (CNTW), Volume 164, Issue CDec 2019https://doi.org/10.1016/j.comnet.2019.106890AbstractThe mobile edge computing (MEC) is combined with wireless energy transfer (WET) to enhance the performance of wireless devices in Internet of Things (IoT) systems, which is called wireless powered mobile edge computing (WP-MEC). The ...
- research-articleSeptember 2019
Radio and computing resource allocation with energy harvesting devices in mobile edge computing environment
Computer Communications (COMS), Volume 145, Issue CSep 2019, Pages 193–202https://doi.org/10.1016/j.comcom.2019.06.001AbstractMobile edge computing (MEC) has been recognized as a promising technique for the Internet of Things (IoT) era which allow the booming mobile devices offload their highly demanding tasks to the MEC server thus release these resource-...
- research-articleJuly 2019
Load Balance Based Job Scheduling in Geo-Distributed Clouds
Wireless Personal Communications: An International Journal (WPCO), Volume 107, Issue 1Jul 2019, Pages 169–192https://doi.org/10.1007/s11277-019-06247-8AbstractIn the wake of rapid development of Internet, more and more people could access it from any places in the world, which leads to the characteristic of geographical distribution of the data. Only one single cloud cannot deal with such data ...
- research-articleJune 2019
Collaborative cache allocation and task scheduling for data-intensive applications in edge computing environment
Future Generation Computer Systems (FGCS), Volume 95, Issue CJun 2019, Pages 249–264https://doi.org/10.1016/j.future.2019.01.007AbstractIn the wake of the development of mobile devices, how to provide low-latency mobile services with the limited battery power is attracting more and more attention. A novel paradigm, edge computing, can make services closer to users, ...
Highlights- Collaborative cache allocation and task scheduling in edge computing is proposed.
- research-articleApril 2019
Dynamic multi-user computation offloading for wireless powered mobile edge computing
Journal of Network and Computer Applications (JNCA), Volume 131, Issue CApr 2019, Pages 1–15https://doi.org/10.1016/j.jnca.2019.01.020AbstractThe combination of mobile edge computing (MEC) and wireless energy transfer (WET) has been recognized as a prominent solution to liberate massive wireless devices from limited battery capacities and compute-intensive workloads in the ...
- articleMarch 2019
Cost-aware scheduling for ensuring software performance and reliability under heterogeneous workloads of hybrid cloud
Automated Software Engineering (KLU-AUSE), Volume 26, Issue 1March 2019, Pages 125–159https://doi.org/10.1007/s10515-019-00252-8Cloud computing is a rapidly growing paradigm in software engineering that offers different services. The hybrid cloud is the best choice for the enterprise to benefit by taking resources on lease from the public cloud only if private cloud resources ...