This is an example of a HTML caption with a link.


13th International Conference on Mobile Data Management. July 23-26, 2012, Bengaluru, India.

Advanced Seminars

  • strict warning: Non-static method view::load() should not be called statically in /customers/e/0/6/ on line 906.
  • strict warning: Declaration of views_handler_filter::options_validate() should be compatible with views_handler::options_validate($form, &$form_state) in /customers/e/0/6/ on line 607.
  • strict warning: Declaration of views_handler_filter::options_submit() should be compatible with views_handler::options_submit($form, &$form_state) in /customers/e/0/6/ on line 607.
  • strict warning: Declaration of views_handler_filter_boolean_operator::value_validate() should be compatible with views_handler_filter::value_validate($form, &$form_state) in /customers/e/0/6/ on line 159.
  • strict warning: Declaration of views_plugin_row::options_validate() should be compatible with views_plugin::options_validate(&$form, &$form_state) in /customers/e/0/6/ on line 134.
  • strict warning: Declaration of views_plugin_row::options_submit() should be compatible with views_plugin::options_submit(&$form, &$form_state) in /customers/e/0/6/ on line 134.
Printer-friendly versionPDF version

Mobile Data Stream Mining: From Algorithms to Applications

Teaser: Mobile data stream mining is a key technology for real-time analysis of data streams generated on-board the phone itself for the data generated by sensors on the phone and/or in close proximity to the phone. The significant advantages that mobile data stream mining provides over traditional strategies for leveraging the phone as a “transmission device” for sensor data, are as follows: reduce the amount of data transmitted from the phone to servers/the cloud, as well as reduce the energy/battery usage on the phone due to transmission of sensor data. Mobile data stream mining is particularly significant for applications that need real-time analysis of continuous data streams such as such as mobile crowd sensing, mobile activity recognition, intelligent transportation systems, mobile healthcare, and so on.

For detailed abstract. Click here.


  • Dr. Shonali Krishnaswamy (Institute for Infocomm Research, Singapore and Monash University, Austalia)
  • Prof. Joao Gama (University of Porto, Portugal)
  • Dr Mohamed Medhat Gaber (University of Portsmouth, United Kingdom)


Crowdsourcing: Dynamic Data Management in Mobile P2P Networks


Teaser: Dynamic Data management has become a necessity in emerging networks (e.g., mobile ad hoc networks and mobile P2P networks) to address fragile wireless connections and devices with very limited capacity. Moreover, traditional methods of data management in mobile environments generally consider only single-hop client-server communication. On the other hand, in mobile P2P networks, the network communication is multi-hop and mobile devices can collect real time data. Due to the dynamic nature of moving hosts, network topology changes very often, thus data availability can be low. Consequently, traditional data management schemes are not adequate for the purpose of maintaining availability.

For detailed abstract. Click here.


  • Prof. Sanjay Kumar Madria (Department of Computer Science at the Missouri University)
  • Prof. Anirban Mondal (Indraprastha Institute of Information Technology (IIIT))


Important Dates (more...)
  • Abstract Submission: December 12, 2011, 23:59 PT
  • Paper Submission: December 12, 2011, 23:59 PT
  • Acceptance Noification: February 20, 2012
  • Camera-ready due: April 27, 2012
  • Conference: July 23 to July 26, 2012
Latest Tweets (more...)