Search Results - "Leung, Kin K"

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  1. 1

    Online Placement of Multi-Component Applications in Edge Computing Environments by Shiqiang Wang, Zafer, Murtaza, Leung, Kin K.

    Published in IEEE access (2017)
    “…Mobile edge computing is a new cloud computing paradigm, which makes use of small-sized edge clouds to provide real-time services to users. These mobile…”
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    Journal Article
  2. 2

    Context-Awareness for Mobile Sensing: A Survey and Future Directions by Yurur, Ozgur, Liu, Chi Harold, Zhengguo Sheng, Leung, Victor C. M., Moreno, Wilfrido, Leung, Kin K.

    “…The evolution of smartphones together with increasing computational power has empowered developers to create innovative context-aware applications for…”
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    Journal Article
  3. 3

    Network Capability in Localizing Node Failures via End-to-End Path Measurements by Liang Ma, Ting He, Swami, Ananthram, Towsley, Don, Leung, Kin K.

    Published in IEEE/ACM transactions on networking (01-02-2017)
    “…We investigate the capability of localizing node failures in communication networks from binary states (normal/failed) of end-to-end paths. Given a set of…”
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    Journal Article
  4. 4

    A Survey of Indoor Localization Systems and Technologies by Zafari, Faheem, Gkelias, Athanasios, Leung, Kin K.

    Published in IEEE Communications surveys and tutorials (01-01-2019)
    “…Indoor localization has recently witnessed an increase in interest, due to the potential wide range of services it can provide by leveraging Internet of Things…”
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    Journal Article
  5. 5

    Opportunistic Relaying for Secrecy Communications: Cooperative Jamming vs. Relay Chatting by Zhiguo Ding, Leung, K. K., Goeckel, D. L., Towsley, D.

    “…In this letter, we study the opportunistic use of relays for secret communications, and propose two transmission schemes that do not require the knowledge of…”
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    Journal Article
  6. 6

    Energy-Efficient Relay Selection for Cooperative Relaying in Wireless Multimedia Networks by Zhengguo Sheng, Jun Fan, Liu, Chi Harold, Leung, Victor C. M., Xue Liu, Leung, Kin K.

    Published in IEEE transactions on vehicular technology (01-03-2015)
    “…In existing wireless networks, supporting multimedia services are becoming more popular and important. In general, wireless multimedia networks should require…”
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    Journal Article
  7. 7

    Adaptive Federated Learning in Resource Constrained Edge Computing Systems by Wang, Shiqiang, Tuor, Tiffany, Salonidis, Theodoros, Leung, Kin K., Makaya, Christian, He, Ting, Chan, Kevin

    “…Emerging technologies and applications including Internet of Things, social networking, and crowd-sourcing generate large amounts of data at the network edge…”
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    Journal Article
  8. 8

    Energy-Efficient Resource Management for Federated Edge Learning With CPU-GPU Heterogeneous Computing by Zeng, Qunsong, Du, Yuqing, Huang, Kaibin, Leung, Kin K.

    “…Edge machine learning involves the deployment of learning algorithms at the network edge to leverage massive distributed data and computation resources to…”
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    Journal Article
  9. 9

    Comprehensive binary interaction mapping of SH2 domains via fluorescence polarization reveals novel functional diversification of ErbB receptors by Hause, Jr, Ronald J, Leung, Kin K, Barkinge, John L, Ciaccio, Mark F, Chuu, Chih-Pin, Jones, Richard B

    Published in PloS one (04-09-2012)
    “…First-generation interaction maps of Src homology 2 (SH2) domains with receptor tyrosine kinase (RTK) phosphosites have previously been generated using protein…”
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    Journal Article
  10. 10

    On the Design of Network Coding for Multiple Two-Way Relaying Channels by Zhiguo Ding, Wang, T., Peng, M., Wang, W., Leung, K. K.

    “…In this paper, we study the design of network coding for the multiple two-way relaying channels where multiple pairs of sources wish to exchange information…”
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    Journal Article
  11. 11

    Model Pruning Enables Efficient Federated Learning on Edge Devices by Jiang, Yuang, Wang, Shiqiang, Valls, Victor, Ko, Bong Jun, Lee, Wei-Han, Leung, Kin K., Tassiulas, Leandros

    “…Federated learning (FL) allows model training from local data collected by edge/mobile devices while preserving data privacy, which has wide applicability to…”
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    Journal Article
  12. 12

    Dynamic Service Migration in Mobile Edge Computing Based on Markov Decision Process by Wang, Shiqiang, Urgaonkar, Rahul, Zafer, Murtaza, He, Ting, Chan, Kevin, Leung, Kin K.

    Published in IEEE/ACM transactions on networking (01-06-2019)
    “…In mobile edge computing, local edge servers can host cloud-based services, which reduces network overhead and latency but requires service migrations as users…”
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    Journal Article
  13. 13

    Joint Beamforming and Power Management for Nonregenerative MIMO Two-Way Relaying Channels by Chee Yen Leow, Zhiguo Ding, Leung, K. K.

    Published in IEEE transactions on vehicular technology (01-11-2011)
    “…We consider multiple-input-multiple-output (MIMO) two-way relaying channels where a pair of multiantenna users wishes to exchange information with the help of…”
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    Journal Article
  14. 14

    A Trustworthiness-based QoS routing protocol for wireless ad hoc networks by Ming Yu, Leung, K.K.

    “…Due to the fact that the wireless links in an ad hoc network are susceptible to attacks and the nodal mobility renders the network to have a highly dynamic…”
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    Journal Article
  15. 15

    Dynamic Service Placement for Mobile Micro-Clouds with Predicted Future Costs by Wang, Shiqiang, Urgaonkar, Rahul, He, Ting, Chan, Kevin, Zafer, Murtaza, Leung, Kin K.

    “…Mobile micro-clouds are promising for enabling performance-critical cloud applications. However, one challenge therein is the dynamics at the network edge. In…”
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    Journal Article
  16. 16

    Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach by Han, Pengchao, Wang, Shiqiang, Leung, Kin K.

    “…Federated learning (FL) is an emerging technique for training machine learning models using geographically dispersed data collected by local entities. It…”
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    Conference Proceeding
  17. 17

    Live Service Migration in Mobile Edge Clouds by Machen, Andrew, Shiqiang Wang, Leung, Kin K., Bong Jun Ko, Salonidis, Theodoros

    Published in IEEE wireless communications (01-02-2018)
    “…Mobile edge clouds (MECs) bring the benefits of the cloud closer to the user, by installing small cloud infrastructures at the network edge. This enables a new…”
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    Journal Article
  18. 18

    MAC Essentials for Wireless Sensor Networks by Bachir, Abdelmalik, Dohler, Mischa, Watteyne, Thomas, Leung, Kin K

    Published in IEEE Communications surveys and tutorials (01-01-2010)
    “…The wireless medium being inherently broadcast in nature and hence prone to interferences requires highly optimized medium access control (MAC) protocols. This…”
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    Journal Article
  19. 19

    Ensuring Threshold AoI for UAV-Assisted Mobile Crowdsensing by Multi-Agent Deep Reinforcement Learning With Transformer by Wang, Hao, Liu, Chi Harold, Yang, Haoming, Wang, Guoren, Leung, Kin K.

    Published in IEEE/ACM transactions on networking (01-02-2024)
    “…Unmanned aerial vehicle (UAV) crowdsensing (UCS) is an emerging data collection paradigm to provide reliable and high quality urban sensing services, with…”
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    Journal Article
  20. 20

    Reconfigurable Intelligent Surface for Low-Latency Edge Computing in 6G by Dai, Yueyue, Guan, Yong Liang, Leung, Kin K., Zhang, Yan

    Published in IEEE wireless communications (01-12-2021)
    “…Edge computing, as one of the key technologies in 6G networks, establishes a distributed computing environment by deploying computation and storage resources…”
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    Journal Article