DocumentCode :
3761745
Title :
Learning mechanism for RT task scheduling
Author :
A. Prasantha Rao;Swathi Agarwal;K. Srinivas;B. Kavitha Rani
Author_Institution :
Department of Information Technology, Anurag Group of Intuitions, Hyderabad, Telangana, India
fYear :
2015
Firstpage :
1
Lastpage :
4
Abstract :
The fascinations of Internet of Things (IoT) necessitate a large number of devices are to be integrated with the existing IoT. These devices are very difficult to manage in a large distributed environment without a careful management design. These location based devices generate data at fixed intervals of time and need configure these devices to software platform to analyze data and understand environment in better way. So, learning capability should incorporate within the system as the environment of system changes dynamically. As the Internet of Things continues to develop, further potential is estimated by a combination with related technology approaches and concepts such as Cloud Computing, Future Internet, Big Data, Robotics and Semantic Technologies. The idea is becomes now evident as those related concepts have started to reveal synergies by combining them.
Keywords :
"Clustering algorithms","Scheduling algorithms","Classification algorithms","Mobile handsets","Computational modeling","Indexes"
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4799-7848-9
Type :
conf
DOI :
10.1109/ICCIC.2015.7435795
Filename :
7435795
Link To Document :
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