- p2p@lists.ogf.org - lists.ogf.org

[P2P] SCPE - Special Issue on Modeling and Simulation Applications of Software Agents
by Katarzyna Wasielewska 09 Nov '14

09 Nov '14

SCALABLE COMPUTING: PRACTICE AND EXPERIENCE - Volume 15, Issue 3 (2014) Scientific International Journal for Parallel and Distributed Computing ISSN 1895-1767 www.scpe.org SCPE is an electronic journal. It provides immediate open access to its content following the principle that making research freely available to the public supports a greater global exchange of knowledge. Special Issue on Modeling and Simulation Applications of Software Agents Full texts available at http://www.scpe.org/index.php/scpe/issue/view/122 TABLE OF CONTENTS * Introduction to the Special Issue on Modeling and Simulation Applications of Software Agents - Costin Badica, Mirjana Ivanovic * A system supporting the evaluation of the operational effectiveness of naval tasks based on agent simulation - Davide Anghinolfi, Alberto Capogrosso, Massimo Paolucci, Perra Francesco * Formal modelling and simulation of a multi-agent nano-robotic drug delivery system - Marina Ntika, Petros Kefalas, Ioanna Stamatopoulou * ABVE-construct: an agent-based virtual entreprise model for civil engineering - Mihaela Oprea * Portability in clouds: approaches and research opportunities - Dana Petcu, Athanasios V. Vasilakos * Fariness of task scheduling in high performance computing environments - Art Sedighi, Yuefan Deng, Peng Zhang

1 0

[P2P] CFP: IEEE Cloud Computing Magazine SI on "Cloud-based Smart Evacuation Systems for Emergency Management"
by DEEPAK PUTHAL 24 Oct '14

24 Oct '14

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Cloud Computing Magazine Special Issue on "Cloud-based Smart Evacuation Systems for Emergency Management" IMPORTANT DATES ***************************** Submissions Due: October 30, 2014 (Extended) DETAILS ABOUT THE ISSUE ***************************** Natural and man-made emergencies, such as tsunamis, earthquakes, floods, and epidemics pose a significant threat to human societies. The lessons learned from the growing number of recent emergencies, such as Japan's earthquake (2011), Katrina hurricane (2005), Colorado flood (2013), Queensland flooding in Australia (2010), Haiti earthquake (2010), has put impetus on the development of emergency evacuation planning systems. Well-coordinated emergency management activities that involves guiding of citizens out of danger areas, placement of medical team to the most appropriate locations, and real-time planning of evacuation routes before and after a disaster play a significant role in saving lives, protecting critical infrastructures, and minimizing causalities. For example, due to lack of proper evacuation planning system, 25 people lost their lives in the first 30 minutes while attempting to flee their Oakland Hills neighborhood in California during a wildfire in 1991. The management of evacuation activities such as guiding people out of dangerous areas and coordinating rescue teams is dependent on the availability of historical data as well as on the effective real-time integration and utilisation of data streaming from multiple sources including on-site sensors, social media feeds and messaging on mobile devices (i.e. text messaging, location, etc.). However, there is a pitfall; the growing ubiquity of on-site sensors, social media and mobile devices means there are more sources of outbound traffic, which ultimately results in the creation of a tsunami of data, beginning shortly after the onset of emergency events. This data tsunami phenomenon is being described as a new grand challenge in computing: The 'Big Data' problem. Over 20 million tweets posted during Hurricane Sandy (2012) lead to an instance of the Big Data problem. During the 2010 Haiti earthquake, text messaging via mobile phones and Twitter made headlines as being crucial for disaster response, but only some 100,000 messages were actually processed by government agencies due to lack of automated and scalable data processing infrastructure. Design and development of evacuation systems for emergency management requires a complete ICT (Information and Communication Technology) paradigm shift in a way that systems do not get overwhelmed by incoming data volume, data rate, data sources, and data types. New cloud-based techniques are needed that can extract meaningful information from large-scaled data in real-time, while avoiding unnecessary data transmission or storage. Future initiative should focus on developing cloud-based techniques to improve the performance of multiple data stream processing system while balancing computational complexity and Quality of Service (e.g., decision making delay, alert generation delay, etc.). *We solicit papers and columns from both industrial and academic research communities.* SUBMISSION GUIDELINES ***************************** Submissions will be subject to the IEEE Cloud Computing Magazines' peer-review process. Articles should be at most 6,000 words, with a maximum of 15 references, and should be understandable to a broad audience of people interested in cloud computing, big data and related application areas. ¬ The writing style should be down to earth, practical, and original. Authors should not assume that the audience will have specialized experience in a particular sub field. All accepted articles will be edited according to the IEEE Computer Society style guide. Submit your papers to Manuscript Central at https://mc.manuscriptcentral.com/ccm-cs. If any questions please contact the guest editors. GUEST EDITORS ***************************** Dr. Rajiv Ranjan, CSIRO, Australia raj.ranjan(a)csiro.au Dr. Samee Khan, NDSU, USA samee.khan(a)ndsu.edu Prof. Joanna Kolodziej, CUT, Poland joanna.kolodziej68(a)gmail.com Prof. Albert Zomaya, Sydney University, Australia zomaya(a)it.usyd.edu.au

1 0

[P2P] CFP - Special Issue on Collective Adaptive Systems
by Katarzyna Wasielewska 21 Oct '14

21 Oct '14

CALL FOR PAPERS Scalable Computing: Practice and Experience (www.scpe.org) Special Issue on Collective Adaptive Systems Collective Adaptive Systems (CAS) is a broad term that describes large scale systems that comprise of many units/nodes, each of which may have their own individual properties, objectives and actions. Decision-making in such a system is distributed and possibly highly dispersed, and interaction between the units may lead to the emergence of unexpected phenomena. CASs are open, in that nodes may enter or leave the collective at any time, and boundaries between CASs are fluid. The units can be highly heterogeneous (computers, robots, agents, devices, biological entities, etc.), each operating at different temporal and spatial scales, and having different (potentially conflicting) objectives and goals, even if often the system has a global goal that is pursued by means of collective actions. Our society increasingly depends on such systems, in which collections of heterogeneous ‘technological’ nodes are tightly entangled with human and social structures to form ‘artificial societies’. Yet, to properly exploit them, we need to develop a deeper scientific understanding of the principles by which they operate, in order to better design them. The special issue will feature articles that concern different and interdisciplinary aspects of collective adaptive systems, as specified in the following list of topics. TOPICS Areas of interest for this special issue include, but are not limited to: - Novel theories relating to operating principles of CAS - Novel design principles for building CAS systems - Insights into the short and long term adaptation of CAS systems - Insights into Emergent Properties of CAS - Insights into general properties of large scale, distributed CAS - Methodologies for studying, analysing and building CAS - Frameworks for analysing or developing CAS - Case-studies/Scenarios that can be used to investigate CAS properties IMPORTANT DATES - Submission: December 15th, 2014 - Author notification: January 31st 2015 - Revised papers (for major revisions): February 28th 2015 - Author notification (for major revisions): April 15th, 2015 - Camera Ready papers due: May 31th, 2015 - Expected publication: September, 2015 SUBMISSION DETAILS The special issue seeks original, unpublished work on technologies enabling collaboration. The authors of the best papers form FoCAS@SASO2014 will be invited to submit an extended version to this special issue. The SCPE journal has a rigorous peer-review process and papers will be sent to at least two independent referees. Papers that do not merit publication (for any reason) can be rejected by the Special Issue Editors without further review. Submitted papers must be formatted according to the journal's instructions, which can be found at: http://www.scpe.org/index.php/scpe/about/submissions#authorGuidelines SPECIAL ISSUE EDITORS - Prof. Giacomo Cabri. Università di Modena e Reggio Emilia, Italy - Prof. Emma Hart. Edinburgh Napier University, UK SCALABLE COMPUTING PRACTICE AND EXPERIENCE The journal focus on algorithm development, implementation and execution on parallel and distributed architectures, as well on application of parallel and distributed computing to the solution of real-life problems. SCPE provides immediate open access to its content. The journal is submitted for indexation in Scopus SciVerse, The Collection of Computer Science Bibliographies, Directory of Open Access Journals (DOAJ), EBSCO, dblp - Computer Science Bibliography, CiteFactor, Index Copernicus, Open Access Library, J-Gate, ZDB, AcademicKeys, BibNet Project at University of Utah, ZENODO, Journal Click. In 2013, the SCPE's SNIP (Scopus Source Normalized Impact per Paper) was 0.619 and SCPE's SJR (Scimago Journal Ranking) was 0.151 (previous year values where: SNIP 0.376 and SJR 0.105). SCPE's SJIF factor was 2.785 in 2012.

1 0

[P2P] CFP: IEEE TETC SI on "Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds"
by DEEPAK PUTHAL 19 Oct '14

19 Oct '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 * CSIRO Computational Informatics Email: dimitrios.georgakopoulos(a)csiro.au

1 0

[P2P] Final Call for Demo and Poster - SustainCom2014 (Sustainable Computing and Communication), Dec. 2014, Sydney, Australia
by Jesson Butt 03 Oct '14

03 Oct '14

Final Call for Poster and Demo: The 4th IEEE International Conference on Sustainable Computing and Communication (SustainCom2014), 3-5 December 2014, Sydney, Australia. Website: http://www.swinflow.org/confs/susc2014/demo.htm Important Dates: Deadline for proceedings published posters/demos with display at conference: 5 October 2014 Notification of Acceptance: 7 October 2014 Final versions of proceeding published posters/demos: 15 October 2014 Deadline for web published posters/demos with display at conference: 30 October 2014 Submissions: Please email your posters/demos to confs.aus(a)gmail.com with the email subject as "SustainCom 2014 demo poster submission". Two types of posters and demos are welcome. Both of them will be displayed during the conference. 1. Proceedings published posters and demos: Submission is a 2-page short paper describing the post/demo content, research, relevance and importance to Sustainable Computing and Communication community. If accepted, the 2-page short paper will be published in the main conference proceedings. 2. Web published posters and demos: Submission is a 1-page extended abstract. Such posters/demos will not be included in the conference proceedings, but will be published on the conference website. --------------- Participants are invited to submit posters and research demos to SustainCom2014. SustainCom2014 (Sustainable Computing and Communication) is created to provide a prime international forum for both researchers, industry practitioners and environment experts to exchange the latest fundamental advances in the state of the art and practice of Sustainable Computing and Communication as well as joint-venture and synergic research and development across various related areas. Topics of interest for posters and demos include, but not limited to: *Track 1: Sustainable Computing and Communications* · Theoretical Aspect of Energy, Power, and Temperature · Algorithms for Reduced Power, Energy and Heat · Power-aware Design of Software, Middleware and Systems · Power-aware Networking · Real-time systems · Power-efficient Computing Architectures · Efficient Circuit Design for Energy Harvesting · Power Management in Memory, Disk, Storage and other peripheral Devices · Configurable and Renewable Energy · Low Power Electronics · Energy Efficient Network Hardware · Energy-Efficient Communication Protocols · Low power Communication Technologies · Embedded Systems, ASICs and FPGSs · Power Leakage and Dissipation · Code Profiling and Transformation for Power Management · Power-aware Scheduling and Resource Allocation · Energy-efficient Wireless/Mobile/Sensor Systems and Networks · Security and Privacy · Wearable Computing · Ecological Monitoring, Analytics and Visualization · Green Communications Architectures and Frameworks · Green Data Centres and Enterprise Computing · QoS and Green Computing · Integration of Smart Appliances · Green Software Engineering Methodologies and Tools · Virtualization Impact for Green Computing · Case Studies on Green Computing and Communications · Green Computing Models, Methodologies and Paradigms *Track 2: Sustainable Systems and Technologies* · Sustainable Architectures for Smart Grids · Smart Grid Security, Reliability and Load Balancing · Energy Management Systems (EMS) · Economic Models of Energy Efficiency · Energy Monitoring, Profiling and Measurement · Renewable Energy Systems and Harvesting Energy (e.g. Solar, Wind) · Greener Systems Planning and Design · Virtualization for Reducing Power Consumption · Evolutionary Algorithms in Energy Applications · Scheduling and Switching Power Supplies · Optimization Techniques for Efficient Energy Consumption · Reliability of Power-aware Computers · Runtime Systems that Assist in Power Saving · Models for Collective Optimization of Power and Performance · Monitoring Tools for Power and Performance of Parallel and Distributed Systems · Use of Sensors for Environmental Monitoring · Smart Control for Eco-friendly Buildings *Track 3: Sustainable Methodologies and Applications* · Smart City (Sustainable Design, Models, Frameworks, Policies and Strategies) · Smart City (Sustainable Integration and Optimization of Comprehensive Resources and Information Flows - energy, emissions, people, goods and services) · Sustainable Energy Generation, Transmission, Distribution and Delivery · Smart Buildings and Urban Infrastructures · Smart Grid for Energy Generation, Transmission, Monitoring and Management · Open Government, Open Data Policies, Urban-Scale Data Sharing, Information Security and Privacy · Smart Logistics and Sustainable Supply Chain Management · Smart People, Smart Living and Smart Citizen Engagement · Intelligent Transport Systems and Traffic Management · Smart Energy-efficient Sensor Networks and Internet of Things · Smart Home, Smart Healthcare and Ageing Population support · e-Mobility, e-Work and e-Business Applications · Sustainable Urban Mobility and Smart Vehicle Management · Smart Resource Support and Demand Management and Optimization · User-Centred Services and Systems · Open Big City Data, Cloud Computing, Internet-Enabled Infrastructures and Services for Sustainability · Innovation Labs, Experimental Test-Beds and Simulation Environments · Mechanisms for Motivating Behavior Change · Advanced Data Analytics for Smart Cities · IS Architecture Design and Platform for Sustainability · Case Studies and Innovative Applications for Sustainability Chairs: Chang Liu, University of Technology Sydney, Australia Jesson Butt, University of Technology Sydney, Australia

1 0

[P2P] CFP - Special Issue on Scalable and Distributed Applications
by Katarzyna Wasielewska 01 Oct '14

01 Oct '14

CALL FOR PAPERS Scalable Computing: Practice and Experience (www.scpe.org) Special Issue on Scalable and Distributed Applications The increased demand for data-intensive computations enforced to utilize homogeneous and heterogeneous multi-processors and multi-computers distributed across Internet. These computations are represented as applications, which are deployed in GPUs, Grids, Clusters, Supercomputers, Cloud-based or other virtualized resources. Speeding up the computations and increasing the bandwidth require many techniques like algorithm optimizations, load balancing, parallelization, resource brokering, reducing communication, etc. The special issue will feature articles that concern large scale computations and scalable computing in distributed systems, considering a wide range of aspects, as specified in the following list of topics. TOPICS Areas of interest for this special issue include, but are not limited to: - Large-scale algorithms and applications - High performance computations for large scale simulations - Large-scale distributed computations - Agent-based computing - Performance analysis, evaluation and prediction - Programming models - Peer-to-peer models and services for scalable Grids - Data-intensive applications - Operations on large-scale distributed databases - Computation as a service - Federation of compute capacity - Virtualization supporting computations - Self-adaptive computational / storage systems - Volunteer computing - Large scale computation with GPU - Horizontal and Vertical scaling - Load Balancing in large-scale distributed systems - Intelligent resource allocation - High Performance Cloud Computing - Cloud Interoperability and Portability - Cloud Application Scalability and Availability - Big Data Cloud Service IMPORTANT DATES - Submission: December 1st, 2014 - Author notification: January 15th 2015 - Revised papers: February 15th 2015 - Author notification: March 1st, 2015 - Camera Ready papers due: March 15th, 2015 - Publication: March 30th, 2015 SUBMISSION DETAILS The special issue seeks original, unpublished work on Scalable and Distributed Application. The SCPE journal has a rigorous peer-review process and papers will be sent to at least two independent referees. Papers that do not merit publication (for any reason) can be rejected by the Special Issue Editors without further review. Submitted papers must be formatted according to the journal's instructions, which can be found at:http://www.scpe.org/index.php/scpe/about/submissions#authorGuidelines SPECIAL ISSUE EDITORS - David Anderson, University of California, Berkeley, USA - Alexey Lastovetsky, University College Dublin, Ireland SCALABLE COMPUTING PRACTICE AND EXPERIENCE The journal focus on algorithm development, implementation and execution on parallel and distributed architectures, as well on application of parallel and distributed computing to the solution of real-life problems. SCPE provides immediate open access to its content. The journal is submitted for indexation in Scopus SciVerse, The Collection of Computer Science Bibliographies, Directory of Open Access Journals (DOAJ), EBSCO, dblp - Computer Science Bibliography, CiteFactor, Index Copernicus, Open Access Library, J-Gate, ZDB, AcademicKeys, BibNet Project at University of Utah, ZENODO, Journal Click. In 2013, the SCPE's SNIP (Scopus Source Normalized Impact per Paper) was 0.619 and SCPE's SJR (Scimago Journal Ranking) was 0.151 (previous year values where: SNIP 0.376 and SJR 0.105). SCPE's SJIF factor was 2.785 in 2012.

1 0

[P2P] CFP: IEEE Cloud Computing Magazine SI on "Cloud-based Smart Evacuation Systems for Emergency Management"
by DEEPAK PUTHAL 01 Oct '14

01 Oct '14

[Apologies if you receive multiple copies of this message] *Call for papers:* IEEE Cloud Computing Magazine Special Issue on "Cloud-based Smart Evacuation Systems for Emergency Management" IMPORTANT DATES ***************************** Submissions Due: October 30, 2014 (Extended) DETAILS ABOUT THE ISSUE ***************************** Natural and man-made emergencies, such as tsunamis, earthquakes, floods, and epidemics pose a significant threat to human societies. The lessons learned from the growing number of recent emergencies, such as Japan's earthquake (2011), Katrina hurricane (2005), Colorado flood (2013), Queensland flooding in Australia (2010), Haiti earthquake (2010), has put impetus on the development of emergency evacuation planning systems. Well-coordinated emergency management activities that involves guiding of citizens out of danger areas, placement of medical team to the most appropriate locations, and real-time planning of evacuation routes before and after a disaster play a significant role in saving lives, protecting critical infrastructures, and minimizing causalities. For example, due to lack of proper evacuation planning system, 25 people lost their lives in the first 30 minutes while attempting to flee their Oakland Hills neighborhood in California during a wildfire in 1991. The management of evacuation activities such as guiding people out of dangerous areas and coordinating rescue teams is dependent on the availability of historical data as well as on the effective real-time integration and utilisation of data streaming from multiple sources including on-site sensors, social media feeds and messaging on mobile devices (i.e. text messaging, location, etc.). However, there is a pitfall; the growing ubiquity of on-site sensors, social media and mobile devices means there are more sources of outbound traffic, which ultimately results in the creation of a tsunami of data, beginning shortly after the onset of emergency events. This data tsunami phenomenon is being described as a new grand challenge in computing: The 'Big Data' problem. Over 20 million tweets posted during Hurricane Sandy (2012) lead to an instance of the Big Data problem. During the 2010 Haiti earthquake, text messaging via mobile phones and Twitter made headlines as being crucial for disaster response, but only some 100,000 messages were actually processed by government agencies due to lack of automated and scalable data processing infrastructure. Design and development of evacuation systems for emergency management requires a complete ICT (Information and Communication Technology) paradigm shift in a way that systems do not get overwhelmed by incoming data volume, data rate, data sources, and data types. New cloud-based techniques are needed that can extract meaningful information from large-scaled data in real-time, while avoiding unnecessary data transmission or storage. Future initiative should focus on developing cloud-based techniques to improve the performance of multiple data stream processing system while balancing computational complexity and Quality of Service (e.g., decision making delay, alert generation delay, etc.). *We solicit papers and columns from both industrial and academic research communities.* SUBMISSION GUIDELINES ***************************** Submissions will be subject to the IEEE Cloud Computing Magazines' peer-review process. Articles should be at most 6,000 words, with a maximum of 15 references, and should be understandable to a broad audience of people interested in cloud computing, big data and related application areas. ¬ The writing style should be down to earth, practical, and original. Authors should not assume that the audience will have specialized experience in a particular sub field. All accepted articles will be edited according to the IEEE Computer Society style guide. Submit your papers to Manuscript Central at https://mc.manuscriptcentral.com/ccm-cs. If any questions please contact the guest editors. GUEST EDITORS ***************************** Dr. Rajiv Ranjan, CSIRO, Australia raj.ranjan(a)csiro.au Dr. Samee Khan, NDSU, USA samee.khan(a)ndsu.edu Prof. Joanna Kolodziej, CUT, Poland joanna.kolodziej68(a)gmail.com Prof. Albert Zomaya, Sydney University, Australia zomaya(a)it.usyd.edu.au

1 0

[P2P] FedCSIS 2015 - Call for Events
by Federated Conference on Computer Science and Information Technologies 21 Sep '14

21 Sep '14

CALL FOR EVENTS Federated Conference on Computer Science and Information Systems Lodz, Poland, 13-16 September, 2015 www.fedcsis.org The 2015 Federated Conference on Computer Science and Information Systems cordially invites you to consider contributing an Event (conference, symposium, workshop, consortium meeting, research dissemination meeting, special session). The FedCSIS multi-conference consists of a significant number of recurring Events and it welcomes proposals for new Events until October 31, 2014. The Events can run over any span of time within the conference dates; from half-day to three days. Lodz, the third-largest Polish city, located in the central Poland south-west of Warsaw. The former textile industry empire, today is an academic city, desirable location for creative industries, home of modern arts and grand events. The FedCSIS Events provide a platform for bringing together researchers, practitioners, and academia to present and discuss ideas, challenges, and potential solutions on established or emerging topics related to research and practice in computer science and information systems. The Events will be selected based on the scientific/technical interest and/or their relevance to practitioners in their topics, the clarity of the proposal in addressing the requested information, the innovativeness of the Event topics, and the fit with the FedCSIS multi-conference program. The FedCSIS 2014 - held in Warsaw, Poland - attracted 430 papers, of which 150 were accepted as full papers (acceptance rate of approximately 35%). Some events accepted additionally short and position papers. FedCSIS 2014 full and short papers will be published in the IEEE Xplore Digital Library, while position papers in a separate volume of the Annals of Computer Science and Information systems series (publication process will be completed by October 31, 2014). PUBLICATIONS As in previous years, FedCSIS preprints will be published on a USB memory stick given to FedCSIS participants. Only papers presented during the conference will be published in the IEEE Xplore Digital Library proceedings (or as position papers, published in a separate volume), and posted at the conference WWW site. The IEEE DL proceedings will be published with an ISBN and ISSN numbers (and, an IEEE Catalog number), under a nonexclusive copyright. Such copyright implies that Events' organizers can and, indeed, are strongly encouraged to invite extended and revised papers for post-conference publications in high-quality journals, edited volumes, etc. EVENT PROPOSALS Event proposals should include the following information (2 pages maximum): 1. The nature of the Event. 2. The title of the Event, and a clear description of the topic, including a brief justification. 3. The complete contact information of the Event organizers, including a link to their personal websites, and an overview of previous experiences with organization of scientific events. 4. Preliminary list of PC members who have agreed to join. 5. Indication of the expected number of papers/attendees to attend the Event. 6. Information of expected post-Event publications, of extended and revised papers, in high-quality journals, edited volumes, etc. Event organizers should email their proposals (in a single pdf file) by October 31, 2014, to the FedCSIS Secretariat at: secretariat(a)fedcsis.org More information concerning Event organization can be found at: http://www.fedcsis.org/2015/cfe

1 0

[P2P] Call for Demo and Poster - BDCloud2014 (Big Data and Cloud Computing), 3-5 Dec. 2014, Sydney, Australia
by Chang Liu 20 Sep '14

20 Sep '14

Call for Poster and Demo: The 4th IEEE International Conference on Big Data and Cloud Computing (BDCloud 2014), 3-5 December 2014, Sydney, Australia. Website: http://www.swinflow.org/confs/bdcloud2014/demo.htm <http://www.swinflow.org/confs/bdds2013/demo.htm> Important Dates: Deadline for proceedings published posters/demos with display at conference: 5 October 2014 Notification of Acceptance: 7 October 2014 Final versions of proceeding published posters/demos: 15 October 2014 Deadline for web published posters/demos with display at conference: 30 October 2014 Submissions: Please email your posters/demos to confs.aus(a)gmail.com with the email subject as "BDCloud 2014 demo poster submission". Two types of posters and demos are welcome. Both of them will be displayed during the conference. 1. Proceedings published posters and demos: Submission is a 2-page short paper describing the post/demo content, research, relevance and importance to Big Data and Cloud Computing community. If accepted, the 2-page short paper will be published in the main conference proceedings. 2. Web published posters and demos: Submission is a 1-page extended abstract. Such posters/demos will not be included in the conference proceedings, but will be published on the conference website. --------------- Participants are invited to submit posters and research demos to BDCloud2014. BDCloud2014 (Big Data and Cloud Computing) is created to provide a prime international forum for both researchers, industry practitioners and environment experts to exchange the latest fundamental advances in the state of the art and practice of Big Data and Cloud Computing as well as joint-venture and synergic research and development across various related areas. Topics of interest for posters and demos include, but not limited to: · Fundamentals of cloud computing · Architectural cloud models · Programming cloud models · Provisioning/pricing cloud models · Data storage and computation in cloud computing · Resource and large-scale job scheduling in cloud computing · Security, privacy, trust, risk in cloud and big data · Fault tolerance and reliability in cloud computing · Access control to cloud computing · Resource virtualisation · Monitoring and auditing in cloud · Scalable and elastic cloud services · Social computing and impacts on the cloud · Innovative HCI and touch-screen models and technologies to cloud · Mobile commerce, handheld commerce and e-markets on cloud · Intelligent/agent-based cloud computing · Migration of business applications to cloud · Energy efficient cloud architecture · Energy aware data storage and computation in cloud computing · Energy aware scheduling, monitoring, auditing in cloud · Green Cloud · Cloud use case studies · Big Data theory, applications and challenges · Big Data mining and analytics on Cloud · Big Data Infrastructure, MapReduce and Cloud Computing · Big Data visualization · Large data stream, incremental datasets on cloud · Distributed and federated datasets · NoSQL data stores and DB scalability · Big Data sharing, security, privacy and trust · Big Data placement, scheduling, and optimization · Distributed file systems for Big Data · Big Data processing, resource scheduling and SLA on Cloud · Performance characterization, evaluation and optimization · Simulation and debugging of Big Data systems · Volume, Velocity, Variety, Value and Veracity of Big Data · Storage and computation management of Big Data · Large-scale workflow management in Big Data · Data management and distributed data systems · Big data applications Chairs: Nazanin Borhan, University of Technology Sydney, Australia Rajiv Ranjan, CSIRO, Australia

1 0

[P2P] CFP: IEEE TETC SI on "Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds"
by DEEPAK PUTHAL 11 Sep '14

11 Sep '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 * CSIRO Computational Informatics Email: dimitrios.georgakopoulos(a)csiro.au

1 0