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 Call for Papers




 Special Issue on "Machine and Robotic Networking"




 IEEE Network Magazine

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The advances in communication networking technologies have been very successful 
in academia, industry and consumer markets. “Being connected” becomes an 
essential part of our daily life. Recently, we have been also observing that 
the communication distance between transmitters and receivers shrinks in many 
commercial applications. This includes sensor/RFID networks, WiFi and near 
field communication (NFC) devices. Such shortened distance is mostly caused by 
the high volume of data demand of users. One other reason is that the modern 
communications is not any more for human-to-human (H2H) information exchange 
only but also for machine-to-machine (M2M) or machine-to-human (M2H). The 
inter-machine distance will be gradually decreasing in many upcoming 
applications. This trend adds complexity to the communication protocols with 
very high node density and unpredictable interference in particular in wireless 
networks. 



The machine in M2M or M2H refers to various devices from remote metering 
modules to vehicles or small networked robots with communication functions 
embedded. M2M applications and use cases currently under consideration by ETSI, 
3GPP, 3GPP2 and IEEE are mainly focused on stationary nodes (machines) or at 
least control of node mobility is out of scope of M2M applications. However, 
the controllable node mobility willconstitute a core part of M2M 
communications. Robotic networks will belong to this class of M2M, where the 
position of nodes can be changed to meet the needs of M2M applications.

 

Independently, in the automatic control and robotics community, there has been 
special interest in connecting multiple robots for effectively achieving the 
common mission of a group of autonomous robots. This area is known as networked 
robotics. The main background of this approach is that connecting robots with 
less intelligence would be more beneficial than a single isolated robot with 
full intelligence. In particular, there have been a group of researchers 
focusing on the behaviours of small animals to mimic their grouping patterns 
such as group navigation and communications. 



This special issue is dedicated to fundamentals and applications in the machine 
and robotic networks. The main emphasis is to introduce and to open new 
research horizon to the networking researchers. Those who are currently 
investigating protocols for inter-machine data exchange or designing a group of 
networked machines (including robots) are potential authors for this special 
issue. The comprehensive survey and forecasting of this inter-disciplinary area 
with deep insight on research challenges and business opportunities are also 
seriously considered.

 

The special issue encourages authors to submit their papers on the specific 
areas, which are not strictly limited to the followings, though:

 

·Networking protocol design for machine and robotic networks

·Distributed algorithm design for machine and robotic networks

·Resource management for machine and robotic networks

·Networked robots with special emphasis on networking and distributed computing

·Capacity issues in machine and robotic networks

·Mobility issues in machine and robotic networks

·Cognitive machine and robotic networks

·Bio-inspired networking in robotics

·Design and application issues in M2M and networked robots

·Business models and use cases for M2M and networked robots

 

The interested authors are expected to submit their papers confirming to the 
guidelines of IEEE Network Magazine, 
http://dl.comsoc.org/livepubs/ni/info/authors.html according to the following 
schedule:




 

Paper submission will be handled electronically through EDAS 
(http://edas.info/newPaper.php?c=10905). 




·Paper submissions: October 15, 2011 

·Notifications to authors: January 15, 2012

·Final manuscripts: March 1, 2012

·Publication of special issue: May 2012

 

Guest Editors

 

Seong-Lyun Kim

Yonsei University, Korea

[email protected]

 

Dapeng Oliver Wu

University of Florida, USA

[email protected]

 

Klaus Schilling

Julius-Maximilians-University Würzburg, Germany 

[email protected]
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