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December 2014

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[P2P] CFP: IEEE TETC SI on "Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds"
by DEEPAK PUTHAL 17 Dec '14

17 Dec '14

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Transactions on Emerging Topics in Computing Special Issue on "Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds" http://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tetcsi_mtpsb… IMPORTANT DATES ***************************** Submission Deadline: June 1 2015 Reviews Completed: September 1 2015 Major Revisions Due (if Needed): October 1 2015 Reviews of Revisions Completed (if Needed): November 1 2015 Minor Revisions Due (if Needed): December 1 2015 Notification of Final Acceptance: February 1 2016 Publication Materials for Final Manuscripts Due: March 1 2016 Publication date: Second Issue 2016 (June Issue) DETAILS ABOUT THE ISSUE ***************************** Internet of Things (IoT) is an emerging paradigm that has gained a significant interest from both academia and industry. IoT is a part of Future Internet and comprises many billions of Internet connected Objects (ICOs) or 'things' where things can sense, communicate, compute and potentially actuate as well as have intelligence, multi-modal interfaces, physical/ virtual identities and attributes. ICOs can include sensors, RFIDs, social media, actuators (such as machines/equipments fitted with sensors and deployed for mining, oil exploration, and manufacturing operations) as well as lab instruments (e.g., high energy physics synchrotron), and smart consumer appliances (smart TV, smart phone, etc.). This IoT vision has recently given rise to the notion of IoT big data applications that are capable of producing billions of data stream and tens of years of historical data to provide the knowledge required to support timely decision making. Some of the emerging IoT big data applications, e.g. smart energy grids, syndromic bio-surveillance, environmental monitoring, emergency situation awareness, digital agriculture, and smart manufacturing, need to process and manage massive, streaming, and multi-dimensional (from multiple sources) data from geographically distributed data sources. Despite recent technological advances of the data-intensive computing paradigms (e.g. the MapReduce paradigm, workflow technologies, stream processing engines, distributed machine learning frameworks) and datacentre clouds, large-scale reliable system-level software for IoT big data applications are yet to become commonplace. As new diverse IoT applications begin to emerge, there is a need for optimized techniques to distribute processing of the streaming data produced by such applications across multiple datacentres that combine multiple, independent, and geographically distributed software and hardware resources. However, the capability of existing data-intensive computing paradigms is limited in many important aspects such as: (i) they can only process data on compute and storage resources within a centralised local area network, e.g., a single cluster within a datacentre. This leads to unsatisfied Quality of Service (QoS) in terms of timeliness of decision making, resource availability, data availability, etc. as application demands increase; (ii) they do not provide mechanisms to seamlessly integrate data spread across multiple distributed heterogeneous data sources (ICOs); (iii) lack support for rapid formulation of intuitive queries over streaming data based on general purpose concepts, vocabularies and data discovery; and (iv) they do not provide any decision making support for selecting optimal data mining and machine algorithms, data application programming frameworks, and NoSQL database systems based on nature of the big data (volume, variety, and velocity). Furthermore, adoption of existing datacentre cloud platform for hosting IoT applications is yet to be realised due to lack of techniques and software frameworks that can guarantee QoS under uncertain big data application behaviours (data arrival rate, number of data sources, decision making urgency, etc.), unpredictable datacentre resource conditions (failures, availability, malfunction, etc.) and capacity demands (bandwidth, memory, storage, and CPU cycles). It is clear that existing data intensive computing paradigms and related datacentre cloud resource provisioning techniques fall short of the IoT big data challenge or do not exist. Topics of interest include, but are not limited to: - Programming abstractions for extedmding existing data intensive computing paradigms to multiple datacentres - Technical foundations for selection of data mining and machine learning algorithms Streaming data query and indexing systems based on semantic web concepts - IoT big data application specific ontology models for capturing heterogeneous data from multiple sources - Decentralised data flow optimisation and management techniques across multiple datacentres - Techniques for petabyte efficient no-SQL query-based IoT big data processing - QoS optimized parallel data analytic techniques beyond traditional relational database systems - Knowledge driven, predictive datacentre resource allocation and provisioning for streaming data - Innovative IoT big data application use cases - Techniques for providing a secure end-to-end connection between users and data sources SUBMISSION GUIDELINES ***************************** Submitted articles must not have been previously published or currently submitted for journal publication elsewhere. As an author, you are responsible for understanding and adhering to our submission guidelines. You can access them at the IEEE Computer Society web site, www.computer.org. TETC is the newest Transactions of the IEEE Computer Society with Open Access only. Please submit your paper to Manuscript Central at https://mc.manuscriptcentral.com/tetc-cs. Please address all other correspondence regarding this special Section to Lead Guest Editor *Dr. Rajiv Ranjan* GUEST EDITORS ***************************** *Dr. Rajiv Ranjan - Corresponding Guest Editor * Senior Research Scientist & Julius Fellow, CSIRO Computational Informatics, Australia Email: raj.ranjan(a)csiro.au *Prof. Lizhe Wang * Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Email:Lizhe.wang@gmail.com *Dr. Jie Tao * Steinbuch Centre for Computing (SCC) Karlsruhe Institute of Technology Email: jie.tao(a)kit.edu *Prof. Albert Zomaya * Australian Research Council Professorial Fellow The University of Sydney, NSW 2006, Australia Email: albert.zomaya(a)sydney.edu.au *Dr. Prem Prakash Jayaraman * Postdoctoral Research Scientist CSIRO Computational Informatics, Australia Email: prem.jararaman(a)csiro.au *Prof. Dimitrios Georgakopoulos * Professor, Computer Science & Info Tech RMIT University, Australia Email: dimitrios.georgakopoulos(a)rmit.edu.au

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[P2P] CFP: IEEE TC SI on "Selected Topics in Smart City Computing"
by DEEPAK PUTHAL 09 Dec '14

09 Dec '14

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Transactions on Computers Special Issue on "Selected Topics in Smart City Computing" http://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tcsi_stscc.p… IMPORTANT DATES ***************************** Open for submissions in ScholarOne Manuscripts: Nov. 1, 2014 Closed for submissions: February 1, 2015 Results of first round of reviews: May 1, 2015 Submission of revised manuscripts: June 1, 2015 Results of second round of reviews: Aug. 1, 2015 Publication materials due: Sep. 1, 2015 DETAILS ABOUT THE ISSUE ***************************** Developing smart city is the key to the next generation urbanization process for improving the efficiency, reliability, and security of a traditional city. The concept of smart city includes various aspects such as environmental sustainability, social sustainability, regional competitiveness, natural resources management, cybersecurity, and quality of life improvement. With the massive deployment of networked smart devices/sensors, unprecedentedly large amount of sensory data can be collected and processed by advanced computing paradigms which are the enabling techniques for smart city. For example, given historical environmental, population and economic information, salient modeling and analytics are needed to simulate the impact of potential city planning strategies, which will be critical for intelligent decision making. Analytics are also indispensable for discovering the underlying structure from retrieved data in order to design the optimal policies for real time automatic control in the cyberphysical smart city system. Furthermore, uncertainties and security concerns in the data collected from heterogeneous resources aggravate the problem, which makes smart city planning, operation, monitoring and control highly challenging. The topics of interest for this special issue include, but are not limited to: * Advanced big data modeling and analytics for smart city planning, monitoring and control * Social media, crowdsourcing and collaborative behavior management * Outdoor/indoor geolocation and cartography continuity * Design and implementation of embedded system for smart city applications * Advanced control techniques in the smart city as a cyberphysical system * Technologies in electrical vehicle, smart building and smart home * Cybersecurity and privacy issues related to smart city * Heterogeneous sensor network and cooperative sensing for smart city * Renewable energy and smart energy management for smart city * Design and synthesis of computing schemes and architectures for smart city * Development of fault detection and diagnosis techniques for smart city * Modeling and computing techniques for environmental and social issues in smart city * Sustainable technologies for smart city SUBMISSION GUIDELINES ***************************** Prospective authors are invited to submit their manuscripts electronically after the "open for submissions" date, adhering to the IEEE Transactions on Computers guidelines (http://www.computer.org/portal/web/tc/author) Please submit your papers through the online system ( https://mc.manuscriptcentral.com/tc-cs) and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by e-mail to the Guest Editors directly. GUEST EDITORS ***************************** *Lizhe Wang, * Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, P.R. China Lizhe.Wang(a)gmail.com *Shiyan Hu, * Michigan Technological University, USA shiyan(a)mtu.edu *Gilles BETIS, * Current EIT ICT Labs, France gilles.betis(a)eitictlabs.eu *Rajiv Ranjan, * CSIRO, Australia rranjans(a)gmail.com

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