MCS '13 call for papers

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MCS 2013  

The Fourth International Workshop on Mobile Cloud Computing & Services


Co-located with ACM MobiSys 2013, Taipei, Taiwan

June 25th, 2013


Sponsored by ACM SIGMOBILE



DESCRIPTION

Mobile phone applications demand greater resources and improved interactivity for better user experience. Resources in cloud computing platforms such as Amazon EC2, Microsoft Azure, and Google AppEngine are a natural fit to remedy the lack of local resources in mobile devices.  Mobile cloud computing refers to an infrastructure where data storage and data processing happen outside of the mobile device to enable a new class of applications previously not possible.  Mobile cloud computing is poised to become a disruptive force in the mobile world.


While prior work on thin client related research is relevant, the availability of cloud computing resources on a pay-as-you-go basis, the advances in virtualization, the emergence of LTE and WiMAX, IEEE 802.11n and 60 GHz, and mobile application programming platforms create a new set of rich problems that require re-thinking old issues with a new lens.


The scope of the MCS workshop will encompass system and networking topics such as device virtualization, notification services, location services, and scalable mobile cloud computing platforms. Suggested topics for paper submissions include but are not limited to:

    1. Mobile cloud computing programming models

    2. Scalable mobile cloud computing platforms

    3. Mobile social networks

    4. Data services and architectures

    5. Cloud-assisted energy management of mobile devices

    6. Mobile device virtualization

    7. Notification services

    8. Location based services

    9. Mobile cloud resource management

    10. Mobile cloud middleware

    11. Mobile cloud architecture

    12. Mobile cloud applications

    13. Data privacy and security

    14. High availability and reliability

    15. Economic considerations in offering mobile cloud computing services

    16. Data mining and machine learning in mobile cloud computing

    17. Context-aware services and computing