• English
    • العربية
  • العربية
  • Login
  • QU
  • QU Library
  •  Home
  • Communities & Collections
  • Help
    • Item Submission
    • Publisher policies
    • User guides
    • FAQs
  • About QSpace
    • Vision & Mission
View Item 
  •   Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  • Qatar University Digital Hub
  • Qatar University Institutional Repository
  • Academic
  • Faculty Contributions
  • College of Engineering
  • Computer Science & Engineering
  • View Item
  •      
  •  
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Distributed cross-layer optimization for healthcare monitoring applications

    Thumbnail
    Date
    2014
    Author
    Awad A.
    Mohamed A.
    Metadata
    Show full item record
    Abstract
    Mobile Health (mHealth) systems leverage wireless and mobile communication technologies to provide healthcare stakeholders with innovative tools and solutions that can revolutionize healthcare provisioning. Body Area Sensor Networks (BASNs) is part of the mHealth system that focuses on the acquisition by a group of biomedical sensors of vital signals. However, the design and operation of BASNs are challenging, because of the limited power and small form factor of biomedical sensors. The source encoding and data transmission are the two dominant power-consuming operations in wireless monitoring system. Therefore, in this paper, a cross-layer framework that aims at minimizing the total energy consumption subject to delay and distortion constraints is proposed. The optimal encoding and transmission energy are computed to minimize the energy consumption in a delay constrained wireless BASN. This cross-layer framework is proposed, across Application-MAC-Physical layers. At large scale networks and due to heterogeneity of wireless BASNs, centralized cross-layer optimization becomes less efficient and more complex. Therefore, a distributed cross-layer optimization has been considered in this paper. The proposed solution has close-to-optimal performance with lower complexity. Simulation results show that the distributed scheme achieves the compromise between complexity and efficiency in energy consumption compared to centralized scheme. 2014 IFIP.
    DOI/handle
    http://dx.doi.org/10.1109/WIOPT.2014.6850279
    http://hdl.handle.net/10576/30157
    Collections
    • Computer Science & Engineering [‎2428‎ items ]

    entitlement

    Related items

    Showing items related by title, author, creator and subject.

    • Thumbnail

      Self-organized Operational Neural Networks with Generative Neurons 

      Kiranyaz, Mustafa Serkan; Malik J.; Abdallah H.B.; Ince T.; Iosifidis A.; Gabbouj M.... more authors ... less authors ( Elsevier Ltd , 2021 , Article)
      Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron ...
    • Thumbnail

      Wireless Network Slice Assignment with Incremental Random Vector Functional Link Network 

      He, Yu Lin; Ye, Xuan; Cui, Laizhong; Fournier-Viger, Philippe; Luo, Chengwen; Huang, Joshua Zhexue; Suganthan, Ponnuthurai N.... more authors ... less authors ( IEEE Computer Society , 2022 , Article)
      This paper presents an artificial intelligence-assisted network slice prediction method, which utilizes a novel incremental random vector functional link (IRVFL) network to deal with the wireless network slice assignment ...
    • Thumbnail

      A novel multi-hop body-To-body routing protocol for disaster and emergency networks 

      Ben Arbia, Dhafer; Alam, Muhammad Mahtab; Attia, Rabah; Ben Hamida, Elye ( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference)
      In this paper, a new multi-hop routing protocol (called ORACE-Net) for disaster and emergency networks is proposed. The proposed hierarchical protocol creates an ad-hoc network through body-To-body (B2B) communication ...

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Home

    Submit your QU affiliated work

    Browse

    All of Digital Hub
      Communities & Collections Publication Date Author Title Subject Type Language Publisher
    This Collection
      Publication Date Author Title Subject Type Language Publisher

    My Account

    Login

    Statistics

    View Usage Statistics

    About QSpace

    Vision & Mission

    Help

    Item Submission Publisher policiesUser guides FAQs

    Qatar University Digital Hub is a digital collection operated and maintained by the Qatar University Library and supported by the ITS department

    Contact Us | Send Feedback
    Contact Us | Send Feedback | QU

     

     

    Video