INVITATION:
=================
Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to:
– ICAS 2021, The Seventeenth International Conference on Autonomic and Autonomous Systems
ICAS 2021 is scheduled to be May 30 – June 03, 2021 in Valencia, Spain under the InfoSys 2021 umbrella.
The submission deadline is March 2, 2021.
Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: https://www.iariajournals.org
All events will be held in a hybrid mode: on site, online, prerecorded videos, voiced presentation slides, pdf slides.
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============== ICAS 2021 | Call for Papers ===============
CALL FOR PAPERS, TUTORIALS, PANELS
ICAS 2021, The Seventeenth International Conference on Autonomic and Autonomous Systems
General page: https://www.iaria.org/conferences2021/ICAS21.html
Submission page: https://www.iaria.org/conferences2021/SubmitICAS21.html
Event schedule: May 30 – June 03, 2021
Contributions:
– regular papers [in the proceedings, digital library]
– short papers (work in progress) [in the proceedings, digital library]
– ideas: two pages [in the proceedings, digital library]
– extended abstracts: two pages [in the proceedings, digital library]
– posters: two pages [in the proceedings, digital library]
– posters: slide only [slide-deck posted at www.iaria.org]
– presentations: slide only [slide-deck posted at www.iaria.org]
– demos: two pages [posted at www.iaria.org]
Submission deadline: March 2, 2021
Extended versions of selected papers will be published in IARIA Journals: https://www.iariajournals.org
Print proceedings will be available via Curran Associates, Inc.: https://www.proceedings.com/9769.html
Articles will be archived in the free access ThinkMind Digital Library: https://www.thinkmind.org
The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.
All tracks are open to both research and industry contributions.
Before submission, please check and comply with the editorial rules: https://www.iaria.org/editorialrules.html
ICAS 2021 Topics (for topics and submission details: see CfP on the site)
Call for Papers: https://www.iaria.org/conferences2021/CfPICAS21.html
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ICAS 2021 Tracks (topics and submission details: see CfP on the site)
SELFTRENDS: Toward brain-like autonomic and autonomous systems
Adaptive robust resource allocation; Optimal self-organized collective actions; Collective adaptation; Active learning; Opportunistic collaborative interactive learning; Adaption fairness; Social and biometric data-aware adaptation; Brain connectivity models; Using unbalanced Datasets; Quantum-inspired optimization; Automated (industrial) assembly environments; Deep neural networks; Multimodal knowledge of the brain; Self-organization in M2M infrastructures; Self-organizing socio-technical systems; Context-aware data self-adaptation; Multi-level loop encapsulation in smart systems; Uncertainty in self-adaptive systems; Adaptive Software defined systems (SDS) scalability; Adaptability in multi-tenant Clouds; Self-aware model-driven systems; Proactive self-adaptation; Self-adaptive urban traffic; Adaptive power profiling; Run-time for self-adaptive systems; Distributed adaptive systems; Self-improving system integration; Self-improving activity recognition systems; Feedback computing; Optimal feedback control; Dynamic adaptive applications; Self-managing Clouds; Decentralized autonomic behavior; Market-adaptive trust; Semantics of self-behavior; Self-organizing patterns; Stability propagation in self-organizing systems; Inconsistency in self-deciding systems; Reasoning problems tractability; Decidability in self-organizing systems
ROBOTRENDS: Robot-related trends
Autonomous aquatic agents; Aerial autonomous robots; Drones control and management; Knowledge-based robot motions; Autonomous mobile robot interaction; Humanoid robots; Intelligent robots; Self-reconfigurable mobile robots; Humanoid imitative learning; Robots in unknown environments; Human centric robots; Adjustable robust optimizations; Moral autonomous agents and human evolution; Cognitive robotics; Robot partnership; Affective communication robots; Human-centric robotics; Visually-impaired and robots; Evolutionary swarm robotics; Robots and human advices; Universal robot hands
SOCIAL ROBOTS: Social robots and cognition
Human-robot interaction; Robot-robot interaction; Perception of a humanoid robots; Humanoid robots mediating social Interaction; Socially assistive robots; Conversational robots; Verbal Interaction; Human-robot touch interaction; Expressive interactions; Social emotions; Arts by humanoid robots; Collaborative social robots; Game approaches; Human-robot interactive games; Robots co-worker partners; Healthcare companion robots; Socially assistive robots; Robot-assisted rehabilitation therapy; Child-robot interaction; Mobile assistive robots; Robots in public spaces; Shopping mall robots; Home utility robots; Robot-assisted cognitive training; Robot-based multimodal emotion recognition; Advertizign robots; Telepresence robots; Robot teleoperation; Robots' social credibility
MACHINE LEARNING: Advanced topics in Deep/Machine learning
Distributed and parallel learning algorithms; Image and video coding; Deep learning and Internet of Things; Deep learning and Big data; Data preparation, feature selection, and feature extraction; Error resilient transmission of multimedia data; 3D video coding and analysis; Depth map applications; Machine learning programming models and abstractions; Programming languages for machine learning; Visualization of data, models, and predictions; Hardware-efficient machine learning methods; Model training, inference, and serving; Trust and security for machine learning applications; Testing, debugging, and monitoring of machine learning applications; Autonomous and robotics systems; Machine learning for systems.
SYSAT: Advances in system automation
Methods, techniques ant tools for automation features; Methodologies for automating of design systems; Industrial automation for production chains; Nonlinear optimization and automation control; Nonlinearities and system stabilization; Automation in safety systems; Structured uncertainty; Open and closed automation loops; Test systems automation; Theory on systems robustness; Fault-tolerant systems
UNMANNED: Driver-less cars and unmanned vehicles
Self-driving cars; Drones; Terrestrial unmanned vehicles; Unmanned aerial vehicles; Underwater unmanned vehicles; Unmanned sea surface vehicles; Collision control; Traffic surveillance challenges; Path planning and estimation; Communication between unmanned vehicles; Integration of unmanned aerial vehicles in civil airspace; Unmanned vehicular clusters; Designing unmanned vehicular-based systems; Safety of unmanned vehicles; Commercial and surveillance applications; Emergency applications; Legal aspects of unmanned vehicular systems; Testbeds and pilot experiments
AUTSY: Theory and Practice of Autonomous Systems
Design, implementation and deployment of autonomous systems; Frameworks and architectures for component and system autonomy; Design methodologies for autonomous systems; Composing autonomous systems; Formalisms and languages for autonomous systems; Logics and paradigms for autonomous systems; Ambient and real-time paradigms for autonomous systems; Delegation and trust in autonomous systems; Centralized and distributed autonomous systems; Collocation and interaction between autonomous and non-autonomous systems; Dependability in autonomous systems; Survivability and recovery in autonomous systems; Monitoring and control in autonomous systems; Performance and security in autonomous systems; Management of autonomous systems; Testing autonomous systems; Maintainability of autonomous systems
AWARE: Design and Deployment of Context-awareness Networks, Services and Applications
Context-aware fundamental concepts, mechanisms, and applications; Modeling context-aware systems; Specification and implementation of awareness behavioral contexts; Development and deployment of large-scale context-aware systems and subsystems; User awareness requirements and design techniques for interfaces and systems; Methodologies, metrics, tools, and experiments for specifying context-aware systems; Tools evaluations, Experiment evaluations
AUTONOMIC: Autonomic Computing: Design and Management of Self-behavioral Networks and Services
Theory, architectures, frameworks and practice of self-adaptive management mechanisms; Modeling and techniques for specifying self-ilities; Self-stabilization and dynamic stability criteria and mechanisms; Tools, languages and platforms for designing self-driven systems; Autonomic computing and GRID networking; Autonomic computing and proactive computing for autonomous systems; Practices, criteria and methods to implement, test, and evaluate industrial autonomic systems; Experiences with autonomic computing systems
CLOUD: Cloud computing and Virtualization
Hardware-as-a-service; Software-as-a-service [SaaS applicaitions]; Platform-as-service; On-demand computing models; Cloud Computing programming and application development; Scalability, discovery of services and data in Cloud computing infrastructures; Privacy, security, ownership and reliability issues; Performance and QoS; Dynamic resource provisioning; Power-efficiency and Cloud computing; Load balancing; Application streaming; Cloud SLAs, business models and pricing policies; Custom platforms; Large-scale compute infrastructures; Managing applications in the clouds; Data centers; Process in the clouds; Content and service distribution in Cloud computing infrastructures; Multiple applications can run on one computer (virtualization a la VMWare); Grid computing (multiple computers can be used to run one application); Virtualization platforms; Open virtualization format; Cloud-computing vendor governance and regulatory compliance
MCMAC: Monitoring, Control, and Management of Autonomous Self-aware and Context-aware Systems
Agent-based autonomous systems; Policy-driven self-awareness mechanisms and their applicability in autonomic systems; Autonomy in GRID networking and utility computing; Studies on autonomous industrial applications, services, and their developing environment; Prototypes, experimental systems, tools for autonomous systems, GRID middleware
CASES: Automation in specialized mobile environments
Theory, frameworks, mechanisms and case studies for satellite systems; Spatial/temporal constraints in satellites systems; Trajectory corrections, speed, and path accuracy in satellite systems; Mechanisms and case studies for nomadic code systems; Platforms for mobile agents and active mobile code; Performance in nomadic code systems; Case studies systems for mobile robot systems; Guidance in an a priori unknown environment; Coaching/learning techniques; Pose maintenance, and mapping; Sensing for autonomous vehicles; Planning for autonomous vehicles; Mobile networks, Ad hoc networks and self-reconfigurable networks
ALCOC: Algorithms and theory for control and computation
Control theory and specific characteristics; Types of computation theories; Tools for computation and control; Algorithms and data structures; Special algorithmic techniques; Algorithmic applications; Domain case studies; Technologies case studies for computation and control; Application-aware networking
MODEL: Modeling, virtualization, any-on-demand, MDA, SOA
Modeling techniques, tools, methodologies, languages; Model-driven architectures (MDA); Service-oriented architectures (SOA); Utility computing frameworks and fundamentals; Enabled applications through virtualization; Small-scale virtualization methodologies and techniques; Resource containers, physical resource multiplexing, and segmentation; Large-scale virtualization methodologies and techniques; Management of virtualized systems; Platforms, tools, environments, and case studies; Making virtualization real; On-demand utilities; Adaptive enterprise; Managing utility-based systems; Development environments, tools, prototypes
SELF: Self-adaptability and self-management of context-aware systems
Novel approaches to modeling and representing context adaptability, self-adaptability, and self-manageability; Models of computation for self-management context-aware systems; Use of MDA/MDD (Model Driven Architecture / Model Driven Development) for context-aware systems; Design methods for self-adaptable context-aware systems; Applications of advanced modeling languages to context self-adaptability; Methods for managing adding context to existing systems and context-conflict free systems; Architectures and middleware models for self-adaptable context-aware systems; Models of different adaptation and self-adaptation mechanisms (component-based adaptation approach, aspect oriented approach, etc.); System stability in the presence of context inconsistency; Learning and self-adaptability of context-aware systems; Business considerations and organizational modeling of self-adaptable context-aware systems; Performance evaluation of self-adaptable context-aware systems; Scalability of self-adaptable context-aware systems
KUI: Knowledge-based user interface
Evolving intelligent user interface for WWW; User interface design in autonomic systems; Adaptive interfaces in a knowledge-based design; Knowledge-based support for the user interface design process; Built-in knowledge in adaptive user interfaces; Requirements for interface knowledge representation; Levels for knowledge-based user interface; User interface knowledge on the dynamic behavior; Support techniques for knowledge-based user interfaces; Intelligent user interface for real-time systems; Planning-based control of interface animation; Model-based user interface design; Knowledge-based user interface migration; Automated user interface requirements discovery for scientific computing; Knowledge-based user interface management systems; 3D User interface design; Task-oriented knowledge user interfaces; User-interfaces in a domestic environment; Centralised control in the home; User-interfaces for the elderly or disabled; User-interfaces for the visually, aurally, or mobility impaired; Interfacing with ambient intelligence systems; Assisted living interfaces; Interfaces for security/alarm systems
AMMO: Adaptive management and mobility
QoE and adaptation in mobile environments; Content marking and management (i.e. MPEG21); Adaptive coding (H.265, FEC schemes, etc.. ); Admission control resource allocation algorithms; Monitoring and feedback systems; Link adaptation mechanisms; Cross layer approaches; Adaptation protocols (with IMS and NGNs scenarios); QoE vs NQoS mapping systems; Congestion control mechanisms; Fairness issues (fair sharing, bandwidth allocation…); Optimization/management mechanisms (MOO, fuzzy logic, machine learning, etc.)
CfP for EUSIPCO 2021 Special Session “Image and video analysis for autonomous drones” (Deadline February 12, 2021)
February 5th, 2021 
Daniela Lopez de Luise you are invited to submit an original, unpublished technical paper to the Special Session “Image and video analysis for autonomous drones”
of EUSIPCO 2021: https://eusipco2021.org/. Conference submission deadline is February 12, 2021.
Autonomous Unmanned Aerial Vehicles (UAVs, or drones) are becoming more and more important to many industries, promising simplified logistics, cost reductions, increased safety for humans, quicker response times and more accurate results, when compared to traditional procedures. Drones are highly useful thanks to their easy deployment, their aerial point-of-view and their ability to access difficult-to-reach spaces. Recent advances in aerial robotics and AI have already pushed drone automation to an unprecedented degree in various application domains, such as infrastructure inspection and maintenance, aerial cinematography, search and rescue operations, etc.
Manipulation, processing, analysis and learning of visual signals lie at the forefront of this revolution. This special session will consider current research in this interdisciplinary subject, aiming to bring together researchers working on image/video analysis and experts in aerial robotics. Topics of interest may include, among others:
– Embedded computer vision
– Deep learning for image/video analysis
– Multimodal perception
– Sensor and data fusion
– Fault and anomaly detection in drone footage
– Subcentimeter-accuracy inspection
– Autonomous drone cinematography
– Vision-based localization and mapping
– Vision-based drone navigation/control
– Vision-based human-drone interaction
This Special Session concerns a very timely topic with high industrial potential, given that fully/semi- automated drones are slowly emerging as a viable alternative to manually teleoperated ones, thanks to recent advances in robotics and AI. A lot of underlying cognitive functionalities that enable such autonomy, particularly the ones facilitating drone perception, rely on advanced image/video analysis methods for achieving their goals, making this a highly interdisciplinary topic of exceptional interest both to imaging scientists and aerial robotics researchers.
The Special Session is organized by Prof. I. Pitas and Dr. I.
Mademlis, from the Artificial Intelligence and Information Analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece (AUTH), under the auspices of the EU-funded Horizon 2020 programme AERIAL-CORE (https://aerial-core.eu/).
Relevant links:
1) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/
2) AIIA Lab: https://aiia.csd.auth.gr/
Sincerely yours,
Prof. I. Pitas, Dr. Ioannis Mademlis,
Artificial Intelligence and Information Analysis (AIIA) Lab,
Aristotle University of Thessaloniki, Greece
IEEE Conference on Systems, Man, and Cybernetics SMC’2021, 2022, 2023, 2024: mark your calendars
February 5th, 2021 Daniela Lopez de Luise
The 2021 International IEEE Conference on Systems, Man, and
Cybernetics IEEE SMC'2021, Melbourne, Australia, October 17-20, 2021
Deadline for special session proposals February 15, 2021;
deadline for submissions and for tutorial and workshop proposals
April 5, 2021.
The conference will be online.
The 2022 International IEEE Conference on Systems, Man, and
Cybernetics IEEE SMC'2022, Prague, Czech Republic, October 9-12, 2022.
The 2023 International IEEE Conference on Systems, Man, and
Cybernetics IEEE SMC'2023, Maui, Hawaii, October 1-4, 2023.
The 2024 International IEEE Conference on Systems, Man, and
Cybernetics IEEE SMC'2024, Kuching City, Sarawark, Malaysia,
October 7-10, 2024.
IEEE TLT Special Issue on Workplace Learning Technologies
February 5th, 2021 Daniela Lopez de Luise Call for Papers for a Special Issue of the
IEEE Transactions on Learning Technologies
on
“DESIGNING TECHNOLOGIES TO SUPPORT PROFESSIONAL
AND WORKPLACE LEARNING FOR SITUATED PRACTICE”
Guest Editors:
Viktoria Pammer-Schindler, Graz University of Technology, Austria
Allison Littlejohn, University College London, U.K.
Tobias Ley, Tallinn University, Estonia
Joachim Kimmerle, IWM-KMRC Tuebingen, Germany
Mark J. W. Lee, Charles Sturt University, Australia
Email: tlt-workplacelearning@ieee.org
+++++++++++++++++++++++++++++++++++++++++++++++++++++
( PDF version of this CFP available at https://bit.ly/3iS8I1h )
In an era of global, organizational, and technological change, all of which are transforming the world of work, professional and workplace learning are critical for both employability and organizational competitiveness. Such learning is therefore needed on a greater scale than ever before, and the only way to provide that scale is through the integration of technology and learning. At the same time, if it is to serve the goal of boosting productivity, professional and workplace learning needs to be based around and integrated with work. Yet most advances in learning technologies have been made within K-12 and higher education settings, and in the area of formal learning environments in general. Technologies developed within formal education settings are nevertheless also increasingly being appropriated for use with/by professional learners in contexts other than those for which they were originally designed.
This special issue on “Designing technologies to support professional and workplace learning for situated practice” aims to showcase the latest developments and innovations in, and advance the scientific discourse on issues specific to, designing technologies that support learning for work. In setting out to achieve this aim, we place focus on learning that is intended to improve work practice, and that is situated within work activities and contexts.
By situating learning within work, a close relationship is evoked between the workplace environment and professional learning-for example, there are strong connections between working and learning; individual learning and organizational learning; and between learning and knowledge creation. This brings with it challenges, such as those stemming from the fact that learning is focused on solving concrete problems, that finding time and a space for learning can be difficult, and that overall the ability to transfer learning across different work contexts is challenging albeit crucial to professional learning. Technologies that have been developed and/or appropriated for situated workplace learning include mobile and ubiquitous technologies, social and collaborative work tools, intelligent and adaptive tutoring and mentoring/coaching systems, augmented and mixed reality applications for on-the-job learner guidance, professional learning analytics, and many others. However, these!
technologies only address some of the challenges of situated workplace learning. The sociotechnical systems of technology-enhanced professional learning, in which professional learners live, work, and learn, function differently to those of formal education, so technologies developed for K-12 and higher education are often not easily applied to work-integrated learning.
To address this crucial gap, we aim to trigger discussion around the state of the art and future imaginaries, in terms of novel technologies that support professional learning and how these can be designed, implemented, and used in order to open up opportunities for professionals (e.g., accelerating learning by enabling learning just in time and collaboratively in new ways) while mitigating risks that have been the focus of debate in the media as well as the academic literature (e.g., datafication, data ownership, algorithms with built-in biases, assumptions behind the design of these algorithms).
This is a call for papers that contribute to research and research-informed practice in technology-enhanced, professional learning by:
a) identifying characteristics of professional learning that are due to the social context in which professional learning is embedded and that are relevant for technology design;
b) interrogating technology practices specific to these characteristics of professional learning, and using the results to inform design-examples are issues of setting aside time and space for learning, privacy issues or issues related to existing power hierarchies, and the potential non-sharedness of learning as a goal of organizational relevance, to name a few;
c) evidencing the ways in which emerging, novel technologies might improve professional learning in a variety of work contexts. Such papers could both be based on experimental studies on emerging, novel technologies that consider salient aspects of professional learning in the experiment design as well as based on field studies investigating the design, development, and application of the technologies in professional learning settings. Special emphasis could be placed on reducing risks introduced by modern technologies, such as increased surveillance in the workplace.
More background on the rationale and motivations for this special issue, along with key references, can be found on the resource page for the special issue at https://ieee-edusociety.org/publications/tlt-workplace-learning-special-issue .
SUGGESTED TOPICS
Topics of interest for the special issue thus include, but are not limited to, the design and development of technological solutions and applications aimed at:
– remote or distributed work-based learning;
– workplace and professional learning that help ensure resilience to continuity crises (e.g., pandemics, natural disasters);
– supporting and assessing transfer of learning to, and between, on-the-job situations;
– learning-as-knowledge-creation in workplace and professional settings;
– learning in complex professional domains and/or in domains with low uptake of learning technologies;
– coaching and mentoring in the workplace (both human and intelligent agent-based);
– the development of “soft” skills in the workplace and professions;
– supporting the links between individual learning, organizational learning, and capability building;
– learning through reflection on workplace and professional practice, including collaborative or shared reflection;
– assessment and credentialing of workplace and professional learning;
– the modeling, development, and management of workplace and professional competencies (i.e., competency-based learning and assessment);
– computer-supported collaborative workplace and professional learning.
Also of interest are investigations of specific technologies as applied to workplace and professional learning, such as:
– adaptive and personalized learning systems, including learner models for enabling them;
– authoring and instructional design tools/platforms;
– games and gamification;
– modeling, simulation, and digital twin technologies and applications;
– reusable learning objects and learning designs;
– semantic Web services, applications, and ontologies;
– social networking and knowledge-sharing infrastructures;
– virtual reality (VR), augmented reality (AR), mixed reality (MR), and other extended reality (XR) technologies;
– wearable devices and interfaces;
– learning analytics and data mining technologies/applications.
Note: TLT is somewhat unique among educational technology journals in that it is both a computer science journal and an education journal. In order to be considered for publication in TLT, papers must make substantive technical and/or design-knowledge contributions to the development of learning technologies as well as show how the technologies can be used to support learning. Papers that are concerned primarily with evaluation of existing learning technologies and their applications are suitable for TLT only if the technologies themselves are novel, or if significant technical and/or design insights are offered.
KEY DATES
– Abstract submission (optional): April 15, 2021
– Feedback from guest editors to authors on abstract: April 22, 2021
– Full manuscripts due: June 15, 2021
– Completion of first review round: End of September 2021
– Revised manuscripts due: End of November 2021
– Final decision notification: End of January 2022
– Publication materials due: End of March 2022
– Publication of special issue: Summer 2022
SUBMISSION AND REVIEW PROCESS
Abstracts may be submitted to the guest editors via email at mailto:tlt-workplacelearning@ieee.org ; this is not mandatory, but will enable the editors to offer early feedback on the paper's suitability with respect to the aims and scope of the special issue.
Full manuscripts should be prepared in accordance with the IEEE Transactions on Learning Technologies guidelines ( https://ieee-edusociety.org/publications/tlt-author-resources ) and submitted via the journal's ScholarOne Manuscripts portal ( https://mc.manuscriptcentral.com/tlt-cs ), being sure to select the relevant special issue name during the submission process. Manuscripts must not have been published or currently be under consideration for publication elsewhere. Only full manuscripts intended for review, not abstracts, should be submitted via the ScholarOne portal, and conversely, full manuscripts cannot be accepted via email.
Each full manuscript that passes an initial prescreening will be subjected to rigorous peer review in accordance with TLT's editorial policies and procedures. It is anticipated that 7 or 8 articles (plus a guest editorial) will ultimately be published in the special issue.
CFP: (Extended Deadline) IEEE ICC Workshop Data Driven Intelligence for Networks and Systems (DDINS) June 2021 Montreal Canada
February 5th, 2021 Daniela Lopez de Luise Call for Papers
The 3-rd IEEE International Workshop on Data Driven Intelligence for Networks and Systems (DDINS)
Organized in conjunction with
IEEE International Conference on Communications (ICC 2021)
14-18 June 2021 // Montreal, Canada
Web link: https://icc2021.ieee-icc.org/
The first DDINS: https://icc2019.ieee-icc.org/workshop/w15-first-international-workshop-data-driven-intelligence-networks-and-systems-ddins
The second DDINS: https://infocom2020.ieee-infocom.org/workshop-data-driven-intelligence-networks-and-systems
Paper submission deadline: February 19, 2021 (FIRM)
Notification of acceptance: March 22, 2021
Camera-ready papers: March 31, 2021
EDAS submission link: https://www.edas.info/newPaper.php?c=27867
The extended selected accepted papers in this workshop will be recommended for publications in Series on Data Driven Intelligence, Sustainability, and Systems, Intelligent and Converged Networks （journal jointly published by International Telecommunication Union (ITU) and Tsinghua University Press (TUP)）http://icn.tsinghuajournals.com/EN/column/item1649.shtml
Network traffic is expected to grow exponentially in the next decade thanks to the advances in smart devices, Internet of Things (IoT) and cloud computing. Not only the volume of the traffic is increasing, the characteristics of the traffic are also becoming more diverse. To properly manage traffic diversity, different but coherent strategies are needed at different protocol layers, and this often results in complex designs in the network which are difficult to deploy and manage. The recent advancement in artificial intelligence (AI) technology has provided a promising approach to deal with complex problems faced in the network and/or systems design and operation. The trend towards highly integrated networks with diverse underlying access technologies to support simultaneously multiple vertical industries has demanded complex operation in the network and/or systems. This represents a great challenge in network and/or systems design.
This Workshop focuses on applying AI technologies to deal with the networks and/or systems, particularly the machine learning techniques that are based on empirical or simulated data. Topics that may apply data driven intelligence to manage the complexity of a smart networks and/or systems include, but not limited to:
* Data driven intelligence supported approaches and technologies
* Data driven intelligence supported applications and systems
* Quality of Service (QoS) and Quality of Experience (QoE) support
* Resource allocation and transmission scheduling
* Medium access control design
* Data centers and cloud systems
* Radio access technology selection
* Spectrum sharing in intra- and inter-tier HetNets
* Traffic load estimation and resource reservation
* User mobility prediction and handover support
* Network fault detection and self-healing
* Network self-configuration and self-organization
* Intrusion detection and self-protection
* Machine learning relevant topics
* Relevant Analysis and modelling
Submission Procedure
Submitted papers must represent original material which is not currently under review in any other conference or journal and has not been previously published. Paper length should not exceed six-page standard IEEE conference two-column format (including all text, figures, and references). Full details of submission procedures and requirements for authors of accepted papers are available at https://icc2021.ieee-icc.org/. All submitted papers will go through a peer review process. All accepted and presented papers will be included in the IEEE ICC 2021 proceedings and submitted to IEEE Xplore. IEEE reserves the right to exclude an accepted and registered but not presented paper from the IEEE digital library.
General Chairs:
– Jinsong Wu, Universidad de Chile, Chile (wujs AT ieee.org))
– Celimuge Wu, University of Electro-Communications, Japan (celimuge AT uec.ac.jp)
– Periklis Chatzimisios, International Hellenic University, Greece (pchatzimisios AT ihu.gr)
Technical Program Chairs:
– Chuan Heng Foh, University of Surrey, UK (c.foh AT surrey.ac.uk)
– Xianfu Chen, VTT Technical Research Centre of Finland, Finland (xianfu.chen AT vtt.fi)
– Muhammad Imran, University of Glasgow, UK (Muhammad.Imran AT glasgow.ac.uk)
Publicity Chairs:
– William Liu, Auckland University of Technology, New Zealand (william.liu AT aut.ac.nz)
– Chunguo Li, Southeast University, China (chunguoli AT seu.edu.cn)
Steering Committee:
– Chuan Heng Foh, University of Surrey, UK
– Jinsong Wu, Universidad de Chile, Chile
– Periklis Chatzimisios, International Hellenic University, Greece
Best Wishes,