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ACM ToIT: Intelligent Internet 2014 : ACM ToIT Special Issue on the Intelligent Internet of Things

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Link: http://toit.acm.org/CfP/ACM-ToIT-CfP-IIoT.pdf
 
When N/A
Where N/A
Submission Deadline Oct 15, 2014
Notification Due Nov 28, 2014
Final Version Due Apr 10, 2015
Categories    internet of things   special issue
 

Call For Papers


ACM Transactions on Internet Technology (TOIT)

Special Issue on The Intelligent Internet of Things
(deadline is extended to 15th October 2014)

Description

The vision of the Internet of Things (IoT) is a dynamic global network based on standards and interoperable communication protocols where physical and virtual things have attributes, identities, and capabilities and are seamlessly integrated into the existing Internet infrastructure. The range of devices deployed as part of the IoT range from passive radio tags to embedded computer systems. Deploying such devices to obtain real-time information for decision making has become common practise in many different domains, such as smart homes, e-health, automotive, transport and logistics, and environmental monitoring. However, due to the varying nature of devices, organisations, and social structures involved in the IoT, intelligent and automated approaches are needed to support decision makers so that sense could be derived from vast amount of information available through IoT networks.

In order to enable automatic inference of appropriate information for decision problems, one has to address many issues found in IoT networks such as: (1) inability to discover appropriate devices and data/information (2) inability to effectively and efficiently aggregate and cross-reference information from IoT networks (2) trustworthiness of information associated with IoT networks; (2) obfuscated information found in IoT to safeguard the privacy and security of individuals leading to possible incorrect inferences; and (4) modelling provenance of information and the transparency of the processes used to asses the importance and impact of the information. Such issues require new ways of thinking about approaches and design paradigms for IoT-based networks so that one can reduce risks associated with decision problems and make the decision making transparent.

Motivated by the above issues, the aim of this section is to bring together leading research on knowledge representation, fuzzy reasoning, trust modelling, and provenance modelling so that important properties of IoT networks could be better captured to support decision making. Topics of interest for the section include, but are not limited to:

- Knowledge-based approaches to evaluate the trustworthiness of devices and services in the IoT
- Knowledge-based policy management and reasoning for the IoT
- Ontologies describing IoT devices and their use
- Provenance and usage in the IoT
- Modelling and evaluating quality in IoT
- Modeling and communicating transparency in IoT
- Situational awareness through context modeling in IoT
- Intelligent decision making using knowledge-based reasoning
- Knowledge-based discovery of devices, data and services in the IoT
- Reasoning with incomplete or uncertain information in the context of the IoT
- Adaptive architectures and application scenarios for IoT

Guest Editors
- Ananthram Swami - US Army Research Laboratory, USA
Ananthram Swami is a Senior Research Scientist at US Army Research Laboratory (ARL) where he is the CAM for ARL's Cyber Security Collaborative Research Alliance and a government lead in ARL's Network Science Collaborative Technology Alliance. He serves on the founding steering board of IEEE TNSE, and is a co-recipient of the best paper award at IEEE TrustCom 2009 and IEEE ICDCS 2013. Prior to this, he received a PhD in Electrical Engineering from the University of Southern California (USC) in Electrical Engineering and has held positions with Unocal Corporation, USC, CS-3, Malgudi Systems, California Lottery, and a visiting faculty positions at INP, Toulouse.

- Edoardo Pignotti - dot.rural Digital Economy Hub, University of Aberdeen, UK
Edoardo Pignotti is a Research Fellow working on trust and provenance issues in Linked Data at the dot.rural Digital Economy Hub. He has ten years experience in Semantic Web technologies, provenance and policy based reasoning gained during his involvement with a number of UK eScience projects. Pignotti is currently the principal investigator of a UK EPSRC funded pilot project investigating technologies to support trust and transparency of devices in the IoT.

- Geeth de Mel - IBM T J Watson Research Centre, USA
Geeth de Mel is Research Staff Member at IBM TJ Watson Research. His interests are in artificial intelligence – especially Semantic Web technologies – and decision support systems in the presence of (or lack of) dynamicity, trust, and provenance. He currently conducts research on next generation sensor networks for coalition military operations; through these collaborations he has co-organised and co-chaired many workshops and conferences.

- Murat Sensoy - Özyeğin University, Turkey
Dr. Murat ≈ûensoy received a Ph.D. degree in 2008 in Computer Engineering from Bogazici University. Shortly after completing his Ph.D, he joined the University of Aberdeen as a Research Fellow where he worked in network and information sciences projects funded by the US Department of Defense (DoD) and the UK Ministry of Defence (MoD). His research interests include Web Intelligence, Semantic Web, Trust/Reputation, and Multiagent Systems.



Submission Instructions
For detailed information on manuscript preparation, please consult http://toit.acm.org/submission.html

Timeline
- Submissions: 15th October 2014
- First decisions: 28th December 2014
- Revisions: 16th February 2015
- Final decisions: 13th March 2015
- Final: 10th April 2015
- Publication date: 11thst September 2015

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