April 2015 - p2p@lists.ogf.org

[P2P] CFP: IEEE TCSS SI on "Cyber-Physical-Social Systems"
by DEEPAK PUTHAL 27 Apr '15

27 Apr '15

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Transactions on Computational Social Systems Special Issue on "Cyber-Physical-Social Systems" DETAILS ABOUT THE ISSUE ***************************** Cyber-physical-social systems (CPSS) integrates the computational physical elements (seamless integration of computational algorithms and physical components) capable of interacting with, reflecting and influencing each other as well as the complicated system and information exhibited by human's social behaviour. Rapid advances in mobile cloud computing, man-machine, machine-machine communications, smart phone networks will cause a new paradigm shift in CPSS design, applications, and operations by bringing improvements not only to the quality of service (QoS) but also to quality of experiment (QoE) and quality of protection (QoP) in terms of the cost efficiency, reliability, security, and energy efficiency from the human perspective of view. The integration of cyber-physical systems and social networks also provides a novel platform to addresses challenges in cyber-physical-social interactions and human-centric technologies development by using powerful tools such as social computing, social cooperation, and social sensing, etc. Application examples of employing mobile computing in CPSS include traffic accidents detection in smart transportation, energy management in smart grid, health monitoring and evaluation. The introduction of social elements into CPS poses new system design challenges and open research issues. Therefore, safety and reliability requirements of physical components are qualitatively different from general-purpose distributed computing infrastructures and lack of consistent and unified system modelling and design principles. Resources in data centers and cloud infrastructures have to be efficiently managed and scheduled to optimize reliability and scalability of CPSS under various constraints of QoE and QoP. Besides, CPSS are expected to deal with data directly coming from trans-domain applications, which could be in various forms such as GPS coordinates, flood level, temperature, rainfall rate, vehicle speed, electricity consumption, etc. How to coordinate various applications of heterogeneous systems and facilitate a deeper integration, interaction and personalization of the physical, cyber, and social domains is another important challenge. This "Cyber-Physical-Social Systems" special issue aims to cover the most recent research and development on the enabling technologies for CPSS, and to stimulate more discussions in this field. Original and unpublished high-quality research results are solicited to explore various challenging topics which include, but are not limited to: l New architecture, protocols, and services for CPSS l Green and energy efficiency design principles and technologies for CPSS l Information fusion and data mining for CPSS l Fault tolerance and reliability for CPSS l High performance computing and many-task computing for CPSS l Security, privacy and trust for CPSS l Resource and service management, scheduling, and migration for CPSS l Applications, simulations, and field test for CPSS l Enabling information, communication and control technologies for CPSS l Exploring social cloud networks and social cloud computing for CPSS l CPSS for novel applications such as smart city, smart grid, smart transportation, etc. l Content and service distribution for CPSS l M2M and D2D communication technologies for CPSS l Big data analytics for CPSS l Quality of experience and quality of protection issues for CPSS l Mobile cloud sensing for CPSS *Schedule* Paper submission due: June 15th, 2015 First round decisions: August 1st, 2015 Submission of revised manuscripts: September1st, 2015 Final decisions: October 1st, 2015 Publication date: Oct/Nov 2015 Issue. *Submission & Major Guidelines* This special issue invites original research papers that make significant contributions to the state-of-the-art in "Cyber-Physical-Social Systems". Submitted articles must not have been previously published or submitted for journal or conference publications. However, the papers that have been previously published with reputed conferences could be considered for publication in the special issue if they contain significant number of "new and original" ideas/contributions along with more than 49% brand "new" material. Every submitted paper will receive at least three reviews. The editorial review committee will include well known experts in the area. Submissions must be directly submitted via the IEEE TCSS submission web site at https://mc.manuscriptcentral.com/tcss, and must follow instructions for formatting and length listed there. *Selection and Evaluation Criteria* - Significance to the readership of the journal - Relevance to the special issue - Originality of idea, technical contribution, and significance of the presented results - Quality, clarity, and readability of the written text - Quality of references and related work - Quality of research hypothesis, assertions, and conclusion *Co-Editor-in-Chief * George Cybenko, Dartmouth College, USA Eunice E. Santos, Illinois Institute of Technology, USA *Guest Editors* Mianxiong Dong, mx.dong(a)csse.muroran-it.ac.jp, Muroran Institute of Technology, Japan Rajiv Ranjan, rajiv.ranjan(a)csiro.au, CSIRO, Australia Albert Y. Zomaya, albert.zomaya(a)sydney.edu.au, The University of Sydney, Australia Man Lin, mlin(a)stfx.ca, St. Francis Xavier University, Canada

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[P2P] CFP: IEEE TETC SI on "Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds"
by DEEPAK PUTHAL 13 Apr '15

13 Apr '15

[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 TCSS SI on "Cyber-Physical-Social Systems"
by DEEPAK PUTHAL 01 Apr '15

01 Apr '15

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Transactions on Computational Social Systems Special Issue on "Cyber-Physical-Social Systems" DETAILS ABOUT THE ISSUE ***************************** Cyber-physical-social systems (CPSS) integrates the computational physical elements (seamless integration of computational algorithms and physical components) capable of interacting with, reflecting and influencing each other as well as the complicated system and information exhibited by human's social behaviour. Rapid advances in mobile cloud computing, man-machine, machine-machine communications, smart phone networks will cause a new paradigm shift in CPSS design, applications, and operations by bringing improvements not only to the quality of service (QoS) but also to quality of experiment (QoE) and quality of protection (QoP) in terms of the cost efficiency, reliability, security, and energy efficiency from the human perspective of view. The integration of cyber-physical systems and social networks also provides a novel platform to addresses challenges in cyber-physical-social interactions and human-centric technologies development by using powerful tools such as social computing, social cooperation, and social sensing, etc. Application examples of employing mobile computing in CPSS include traffic accidents detection in smart transportation, energy management in smart grid, health monitoring and evaluation. The introduction of social elements into CPS poses new system design challenges and open research issues. Therefore, safety and reliability requirements of physical components are qualitatively different from general-purpose distributed computing infrastructures and lack of consistent and unified system modelling and design principles. Resources in data centers and cloud infrastructures have to be efficiently managed and scheduled to optimize reliability and scalability of CPSS under various constraints of QoE and QoP. Besides, CPSS are expected to deal with data directly coming from trans-domain applications, which could be in various forms such as GPS coordinates, flood level, temperature, rainfall rate, vehicle speed, electricity consumption, etc. How to coordinate various applications of heterogeneous systems and facilitate a deeper integration, interaction and personalization of the physical, cyber, and social domains is another important challenge. This "Cyber-Physical-Social Systems" special issue aims to cover the most recent research and development on the enabling technologies for CPSS, and to stimulate more discussions in this field. Original and unpublished high-quality research results are solicited to explore various challenging topics which include, but are not limited to: l New architecture, protocols, and services for CPSS l Green and energy efficiency design principles and technologies for CPSS l Information fusion and data mining for CPSS l Fault tolerance and reliability for CPSS l High performance computing and many-task computing for CPSS l Security, privacy and trust for CPSS l Resource and service management, scheduling, and migration for CPSS l Applications, simulations, and field test for CPSS l Enabling information, communication and control technologies for CPSS l Exploring social cloud networks and social cloud computing for CPSS l CPSS for novel applications such as smart city, smart grid, smart transportation, etc. l Content and service distribution for CPSS l M2M and D2D communication technologies for CPSS l Big data analytics for CPSS l Quality of experience and quality of protection issues for CPSS l Mobile cloud sensing for CPSS *Schedule* Paper submission due: June 15th, 2015 First round decisions: August 1st, 2015 Submission of revised manuscripts: September1st, 2015 Final decisions: October 1st, 2015 Publication date: Oct/Nov 2015 Issue. *Submission & Major Guidelines* This special issue invites original research papers that make significant contributions to the state-of-the-art in "Cyber-Physical-Social Systems". Submitted articles must not have been previously published or submitted for journal or conference publications. However, the papers that have been previously published with reputed conferences could be considered for publication in the special issue if they contain significant number of "new and original" ideas/contributions along with more than 49% brand "new" material. Every submitted paper will receive at least three reviews. The editorial review committee will include well known experts in the area. Submissions must be directly submitted via the IEEE TCSS submission web site at https://mc.manuscriptcentral.com/tcss, and must follow instructions for formatting and length listed there. *Selection and Evaluation Criteria* - Significance to the readership of the journal - Relevance to the special issue - Originality of idea, technical contribution, and significance of the presented results - Quality, clarity, and readability of the written text - Quality of references and related work - Quality of research hypothesis, assertions, and conclusion *Co-Editor-in-Chief * George Cybenko, Dartmouth College, USA Eunice E. Santos, Illinois Institute of Technology, USA *Guest Editors* Mianxiong Dong, mx.dong(a)csse.muroran-it.ac.jp, Muroran Institute of Technology, Japan Rajiv Ranjan, rajiv.ranjan(a)csiro.au, CSIRO, Australia Albert Y. Zomaya, albert.zomaya(a)sydney.edu.au, The University of Sydney, Australia Man Lin, mlin(a)stfx.ca, St. Francis Xavier University, Canada

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