Calls for Papers for Journals
The IEEE Computer Society Transactions publish archive-quality research papers on a variety of topics related to computer science and technology. If you are interested in publishing with us, please view our list of on-going calls for papers to determine which journal best suits your area of expertise.
- IEEE Computer Architecture Letters
- IEEE Transactions on Affective Computing
- IEEE Transactions on Big Data
- IEEE Transactions on Computers
- IEEE Transactions on Cloud Computing
- IEEE Transactions on Dependable and Secure Computing
- IEEE Transactions on Emerging Topics in Computing
- IEEE Transactions on Haptics
- IEEE Transactions on Knowledge & Data Engineering
- IEEE Transactions on Learning Technologies
- IEEE Transactions on Mobile Computing
- IEEE Transactions on Multi-Scale Computing Systems
- IEEE Transactions on Network Science and Engineering
- IEEE Transactions on Parallel & Distributed Systems
- IEEE Transactions on Pattern Analysis & Machine Intelligence
- IEEE Transactions on Services Computing
- IEEE Transactions on Software Engineering
- IEEE Transactions on Sustainable Computing
- IEEE Transactions on Visualization & Computer Graphics
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
IEEE Computer Architecture Letters (CAL), a bi-annual forum for fast publication of new, high-quality ideas in the form of short, critically refereed, technical papers, is seeking submissions on any topic in computer architecture.
Special Issue on Apparent Personality Analysis
Automatic analysis of videos and any other kind of input data to characterize human behavior has become an area of active research with applications in affective computing, human-machine interfaces, gaming, security, marketing, health, and other domains. Research advances in multimedia information processing, computer vision and pattern recognition have lead to established methodologies that are able to successfully recognize consciously executed actions, or intended movements (e.g., gestures, actions, interactions with objects and other people). However, recently there has been much progress in terms of computational approaches to characterize sub-conscious behaviors, which may be revealing aptitudes or competence, hidden intentions, and personality traits.
Special Issue on Affective Reasoning for Big Social Data Analysis
As theWeb rapidly evolves,Web users are evolving with it. In an era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through social networks, online communities, blogs, Wikis, and other online collaborative media. In recent years, this collective intelligence has spread to many different areas, with particular focus on fields related to everyday life such as commerce, tourism, education, and health, causing the size of the Web to expand exponentially.
The distillation of knowledge from such a big amount of unstructured information, however, is an extremely difficult task, as the contents of today’s Web are perfectly suitable for human consumption, but remain hardly accessible to machines. The opportunity to capture the opinions of the general public about social events, political movements, company strategies, marketing campaigns, and product preferences has raised growing interest both within the scientific community, leading to many exciting open challenges, as well as in the business world, due to the remarkable benefits to be had from marketing and financial market prediction.
Existing approaches to big social data analysis mainly rely on parts of text in which sentiment is explicitly expressed, e.g., through polarity terms or affect words (and their co-occurrence frequencies). However, opinions and sentiments are often conveyed implicitly through latent semantics, which make purely syntactical approaches ineffective. In this light, this Special Issue focuses on the introduction, presentation, and discussion of novel techniques that further develop and apply affective reasoning tools and techniques for big social data analysis. A key motivation for this Special Issue, in particular, is to explore the adoption of novel affective reasoning frameworks and cognitive learning systems to go beyond a mere word-level analysis of natural language text and provide novel concept-level tools and techniques that allow a more efficient passage from (unstructured) natural language to (structured) machineprocessable affective data, in potentially any domain.
Special Issue on Human Behavior Analysis "in-the-wild"
Coming generations of robots and intelligent virtual agents will interact with people in increasingly naturalistic ways. They will automatically perceive and process social signals on a rapid time base with the goal of understand people’s emotions, appraisals, and intentions. Because people operate in a diversity of contexts, human behavior analysis will need to be robust to the diversity of contexts in which people live and to the timing of their displays. The latter is important because the meaning of an expression can depend on its dynamics. Until recently, human behavior analysis was limited to posed behavior in highly controlled contexts and with little attention to precise detection of onsets, offsets, and the temporal, multimodal, and interpersonal envelope of displays. Recent work has turned attention to un-posed, unscripted behavior but contexts have remained relatively constrained and there has been relatively little attention to multimodal communication and the dynamics of displays. As an example, automatic spotting of subtle and fleeting expressions (i.e., micro-expressions) that may powerfully communicate emotion has only recently attracted attention. To meet the need for advanced human behavior understanding that is robust to context and accurately represents the flow and meaning of communicative displays, advances in databases and algorithms are critical.
This special issue addresses the need to bring together leading efforts in human behavior analysis in the wild. We seek advances in databases and algorithms for human behavior understanding in diverse contexts beyond the laboratory. We seek the full range of modalities, social signals, and levels of analysis. We are especially interested in efforts that consider the "packaging" of multimodal signals and interpersonal accommodation or coordination. Modalities include facial expression, body movement and gesture from video; acoustics and prosody from audio; wearable sensors; and infrared imaging. This special issue will present advances in databases, algorithms, benchmarks, and findings in support of the next generation of affective computing.
The IEEE Transactions on Affective Computing (TAC), a new bi-annual online-only publication, is seeking submissions of original research on the principles and theories explaining why and how affective factors condition interaction between humans and technology, on how affective sensing and simulation techniques can inform our understanding of human affective processes, and on the design, implementation, and evaluation of systems that carefully consider affect among the factors that influence their usability. Surveys of existing work will be considered for publication when they propose a new viewpoint on the history and the perspective on this domain.
Special Issue on Big Data Applications in Cyber Security and Threat Intelligence
This last decade has witnessed a tremendous rapid increase in volume, veracity, velocity and variety of data generated by different cyber security solutions and as part of cyber investigation cases. When a significant amount of data is collected from or generated by different devices and sources, intelligent big-data analytical techniques are necessary to mine, interpret and visualise such data. To mitigate existing cyber security threats, it is important for big-data analytical techniques to keep pace.
This special issue will focus on cutting-edge from both academia and industry, with a particular emphasis on novel techniques to mine, interpret and visualise big-data from a wide range of sources and can be applied in cyber security, cyber forensics and threat intelligence context. Only technical papers describing previously unpublished, original, state-of-the-art research, and not currently under review by a conference or a journal will be considered. Extended work must have a significant number of "new and original" ideas/contributions along with more than 30% brand "new" material.
Special Issue on Big Data Systems on Emerging Architectures
The continued evolution of computing hardware and infrastructure imposes new challenges and bottlenecks to big data management. Over the last few years there has been a renewed interest in the area of (big) data systems on emerging hardware. The opportunities and challenges from emerging computing systems have been raised different scales, from a single machine to thousands of machines. The need for effectively utilizing computing resources creates new technologies and research directions: from conventional ones (e.g., cluster computing, in-memory computing), to more recent ones (e.g., GPGPU, many-core processors, and NVRAM). In addition to performance, many other system features are important for big data applications, like energy consumption and total ownership costs. For a specific application domain such as graph processing and deep learning, the design and development of novel systems on emerging hardware will create the insight into new solution approaches of the application domain and even further. Thus, there is a need to fundamentally address all the above-mentioned issues in big data systems. IEEE Transaction on Big Data (TBD) seeks original manuscripts for a Special Issue on the theme - Big Data Systems on Emerging Architectures scheduled to appear in an issue of 2017.
Special Issue on Theoretical Foundations for Big Data Security and Privacy
Big data is one of the hottest research topics in science and technology communities, and it possesses a great application potential in every sector of human society. However, security and privacy, especially theoretical foundations of them, are critical barriers for extensive applications of big data. We have seen the vulnerability of the available privacy preserving data publishing methods against the dramatic development of mining techniques. We also meet the challenges to apply strict privacy protection frameworks (e.g., differential privacy) in practice. In terms of cryptography, we are experiencing the extraordinary efficiency problem given the volume and scale of big data. Moreover, we have to handle the existing and emerging attack methods in the big data environment. In summary, it is time for us to face the challenges. We have to improve or adjust the existing security and privacy techniques, even invent new tools and techniques, to accommodate the new problems and challenges in the age of big data.
Special Issue on Trustworthiness in Big Data and Cloud Computing Systems
The rapid advancement of digital sensors, computers, networks, and smart devices with their extensive use is leading to the integration of a significant amount of diversified data that results in emerging research on Big Data. Cloud computing means storing, computing, and accessing data and programs over the Internet. The growth of cloud computing and cloud data stores have been a precursor and facilitator to the emergence of Big Data. Thus, Big Data and Cloud systems are considered complimentary to each other.
Since Big Data are often in unstructured or semi-structured forms that are being generated from various sources, trustworthiness in data collection, integration, computing, decision-making, and data management becomes a great concern. For example, can we trust current Big Data storage and protection systems or can the use of Big Data analytic enhance security and privacy of the whole system? On the other hand, trustworthiness is also one of the most concerning issues in Cloud Computing environments in terms of fault tolerance, data loss recovery, data privacy/security/safety, and data protection, due to its open environment with very limited end user-side controls. Currently, many new applications are being developed explicitly for cloud system deployment, while many traditional applications will eventually evolve to cloud. The end user-side wants these cloud-based services to be at least as trustworthy and available as traditional offerings. To meet these expectations, cloud service providers and cloud consumers need to gain a solid understanding of the unique challenges of cloud computing and learn how to mitigate risks.
While information society, commercial and scientific companies, and industries share the need for massive throughput, trustworthiness of services will become a big concern. However, trustworthiness in both Big Data and Cloud Computing systems has received less attention from researchers and practitioners. The aim of this special issue is to solicit both original research that discusses the trustworthiness issues, trustworthy platforms, trustworthy frameworks, and design methodologies for Big Data and Cloud Computing systems.
Special Issue on Biomedical Big Data: Understanding, Learning and Applications
Biomedical imaging is an essential component in various fields of biomedical research and clinical practice. Biologists quantitatively study cell behavior and generate high-throughput microscopy data sets. Neuroscientists detect regional metabolic brain activity from positron emission tomography (PET), functional magnetic resonance imaging (MRI), and magnetic resonance spectrum imaging (MRSI) scans. Virologists generate 3D reconstructions of viruses from micrographs, and radiologists identify and quantify tumors from MRI and computed tomography (CT) scans. Advanced imaging equipment and diverse applications have driven the generation of biomedical big data. The main challenge and bottleneck for the related research is the conversion of “biomedical big data” into interpretable information and hence discoveries. Computer vision theory has a huge potential in many aspects for automated understanding of biomedical data and has been used successfully to speed up and improve applications such as large-scale cell image analysis (image preconditioning, cell segmentation and detection, cell tracking, and cell behavior identification), image reconstruction and registration, organ segmentation and disease classification. Moreover, when it comes to the new era of machine learning, deep learning has revolutionized multiple fields of computer vision, significantly pushing the state of arts of computer vision systems in a broad array of high-level tasks.
This special issue serves as a forum to bring together active researchers all over the world to share their recent advances in this exciting area. We solicit original contributions in three-fold: (1) present state-of-the-art theories and novel application scenarios related to biomedical big data analytics; (2) survey the recent progress in this area; and (3) build benchmark datasets.
The IEEE Transactions on Big Data (TBD) publishes peer reviewed articles with big data as the main focus. The articles will provide cross disciplinary innovative research ideas and applications results for big data including novel theory, algorithms and applications. Research areas for big data include, but are not restricted to, big data analytics, big data visualization, big data curation and management, big data semantics, big data infrastructure, big data standards, big data performance analyses, intelligence from big data, scientific discovery from big data security, privacy, and legal issues specific to big data. Applications of big data in the fields of endeavor where massive data is generated are of particular interest.
Special Section on Computer Arithmetic
Submitted papers must include a new significant contribution to Computer Arithmetic (simple application of classical computer arithmetic methods to other domains will not be considered). The submitted papers must include clear evaluation of the proposed solutions (based on models and/or implementations results) and comparisons to state-of-the-art solutions.
IEEE Transactions on Computers (TC), a monthly archival publication, is seeking submissions of papers, brief contributions, and comments on research in areas that include, but are not limited to, computer organizations and architectures; operating systems, software systems, and communication protocols; real-time systems and embedded systems; digital devices, computer components, and interconnection networks; and new and important applications and trends.
IEEE Transactions on Cloud Computing (TCC), will publish peer-reviewed articles that provide innovative research ideas and applications results in all areas relating to cloud computing. Topics relating to novel theory, algorithms, performance analyses and applications of techniques relating to all areas of cloud computing will be considered for the transactions. The transactions will consider submissions specifically in the areas of cloud security, tradeoffs between privacy and utility of cloud, cloud standards, the architecture of cloud computing, cloud development tools, cloud software, cloud backup and recovery, cloud interoperability, cloud applications management, cloud data analytics, cloud communications protocols, mobile cloud, liability issues for data loss on clouds, data integration on clouds, big data on clouds, cloud education, cloud skill sets, cloud energy consumption, cloud applications in commerce, education and industry. This title will also consider submissions on Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS).
Special Issue on Data-Driven Dependability and Security
Assessing dependability and security properties of computer systems is today an important concern for engineers and practitioners. The analysis of textual/numeric data and log files produced under real workload conditions by applications, systems, and networks, intrusion detection systems, monitors and issue-trackers plays a key role for dependability and security evaluation. Data analysis is crucial in a variety of tasks, such as measuring availability and reliability of a system, characterizing failures, gaining insights into the progression of security attacks, designing mitigation means and countermeasures.
Academia and industry widely recognize the inherent potential of dependability and security data analysis for assessing dependability of computer systems and operational networks, and improving the engineering process. Nevertheless, in spite of decades of research and methodological advances, data analysis in this specific area keeps posing challenging research questions due to the heterogeneity, volume and velocity of the collected data, the lack of systematic, end-to-end analysis procedures, the increasing diversity of analysis objectives and emerging application domains in critical areas.
The Special Issue aims to concentrate contributions from academic and industrial organizations addressing dependability and security of computer systems and networks through data analysis, and to publish consolidated research results focusing on data-driven methodologies, measurements from production systems, analysis of large datasets.
Special Issue on Paradigm Shifts in Cryptographic Engineering
Research on cryptologic approaches to solving real-world security problems has been conducted in the public domain for decades, and well established paradigms and techniques now exist that can solve numerous security problems in our lives. Since then, substantial breakthroughs have been made in cryptographic engineering especially in the recent years. To be more precise, by cryptographic engineering, we mean the security techniques researched with cryptographic rigour aimed at solving real-life problems in our current world; these involve systems, components, practical methods and algorithms, implementations as well as human elements.
Indeed, our society is constantly influenced by different lifestyle shifts driven by diverse technological advances: to name a few recent technological revolutions beyond the more established trends of cloud computing and big data; notably internet of things (IoT), cyber-physical systems (CPS), cyber-physical social lifestyles augmented by social media, smart clothing, and more recently nanosensors and flexible electronics.
Meanwhile, the security research community has now matured to a level where cryptographic engineering techniques with additional features beyond the basic security requirements are increasingly being proposed, due largely to real-world constraints, changing needs or socio-technological revolutions. Recent ones include fully homomorphic cryptography, functional cryptography and *-preserving cryptography, where we use * as a wildcard to denote different features that can be preserved, e.g. format, order, structure, privacy, property. In response to recent news of security systems being subverted, attention has also been devoted to the notions of malicious security and adversarial security, i.e. where security is no longer just against bad guys but where good guys who are conventionally viewed as mostly defensive can equally be adversarial. Meanwhile, the way that humans interact with each other has drastically changed since the days when cryptographic engineering research first commenced that modelled the security problems essentially as multi-party communications. From conventional terminal-based communications, our world now is one where people interact on the go, with others virtually in social media, aided by a myriad of personal networked gadgets and smart things.
IEEE Transactions on Dependable and Secure Computing (TDSC), a bimonthly archival publication, is seeking submissions of papers that focus on research into foundations, methodologies, and mechanisms that support the achievement—through design, modeling, and evaluation—of systems and networks that are dependable and secure to the desired degree without compromising performance. The focus also includes measurement, modeling, and simulation techniques, and foundations for jointly evaluating, verifying, and designing for performance, security, and dependability constraints.
IEEE Transactions on Emerging Topics in Computing (TETC) seeks original manuscripts for submission under Technical Tracks. In a track the technical contents of a submitted manuscript must be of an emerging nature and fall within the scope and competencies of the Computer Society. Manuscripts not abiding by these specifications will be administratively rejected. The topics of interest for the Technical Tracks are as follows:
- Enterprise Computing Systems
- Computational Networks
- Hardware and Embedded System Security
- Educational Computing
- High Performance Computing
- Next Generation Wireless Computing Systems
- Computer System Security
- Emerging Hardware for Computing
Submitted articles must describe original research which is not published or currently under review by other journals or conferences. Extended conference papers should be identified in the submission process and have considerable novel technical content; all submitted manuscripts will be screened using a similarity checker tool. 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. Please thoroughly read these before submitting your manuscript.
Please submit your paper to Manuscript Central at https://mc.manuscriptcentral.com/tetc-cs and select the "Technical Track" option in the drop-down menu for "Manuscript Type".
Please address all other correspondence regarding this Call For Papers to Fabrizio Lombardi, EIC of IEEE TETC, email@example.com
Special Issue on Big Data Computing for the Smart Grid
With the increasing deployment of new monitoring devices and advanced measurement infrastructures, such as phasor measurement units and smart meters, smart grid is collecting large amounts of energy-related data at an unprecedented granularity, speed, and complexity. Smart grid has become data-driven, which calls for intelligent big data computing methods and solutions (such as predictive data mining, robust data analytics, artificial intelligence, distributed and high performance computing, efficient data management, database and data warehousing, and cloud computing techniques). With the growing volume, speed and types of big data from the energy industry, data-intensive computing is imperative to guarantee critical functionalities in smart grid, such as real-time wide-area situational awareness, dynamic energy management, demand response, vehicle-to-grid technology, load prediction, and renewable production forecasting. The focus of this special issue is on the improvement of smart grid operations and applications with emphasis on big data computing. We solicit and publish original research papers on the technologies, algorithms, and methodologies that highlight emerging computation technologies for smart grid big data.
Special Issue on Cyber-Physical Social Systems: Integrating Human into Computing
IEEE Transaction on Emerging Topics in Computing (TETC) seeks original manuscripts for a Special Issue on Cyber-Physical-Social Systems: Integrating Human into Computing. The last decade has seen human factors becoming increasingly important in computing systems. Therefore, by integrating human factors as part of a system, a cyber-physical social system (CPSS) encompasses not only cyberspace and physical world, but also human knowledge, mental capacity, and sociocultural elements. Just as the Internet has transformed the way that people interact with information, CPSS will transform the way people interact with every computing systems and create new revolutionary science, technical capabilities for better quality of life. To actualize this vision, CPSS no doubt requires further innovations in creating new device, service and computing architecture. This special issue will comprise state-of-the-art research in enabling cyber-physical social systems with emphasis on computing, including a broad range of enabling technologies in developing and optimizing the architecture, design, and operation of CPSS.
Special Issue on High Dependability Systems
IEEE Transaction on Emerging Topics in Computing (TETC) seeks original manuscripts for a Special Issue/Section on High Dependability Systems scheduled to appear in the third issue of 2017. The continuous scaling of microelectronic technology enables to increase system complexity and performance. This comes together with new dependability (i.e., reliability, availability, safety and security) challenges, as possible in general purpose electronics as well for applications demanding high dependability, such as automotive, space, transportation, etc. All aspects of fault modelling, reliability, availability, safety and security are of interest for this Special Issue/Section. Original manuscripts covering the entire spectrum of relevant research activities are sought.
Joint Special Section on VLSI and Nanotechnology Design Trends for Computing Innovations
IEEE Transactions on Nanotechnology and IEEE Transactions on Emerging Topics in Computing seek original manuscripts for a Special Section tentatively scheduled to appear in the September 2017 issues.
Special Issue on eDemocracy and eGovernment (SIEDEG)
Representatives of the governments, international organizations and universities are called to develop a vision for eDemocracy, and eGovernment. The SIEDEG is a peer-review special issue to be published at IEEE Transactions on Emerging Topics in Computing. It covers technical and non-technical aspects of eSociety, eGovernance, eParticipation, eDemocracy, eGovernment and eHealth. The main objective is to discuss the regions’ transition to an information and knowledge society that will accelerate and enhance regional economic, social, cultural and technological development and exchange. SIEDEG addresses the main issues of public administration and electronic democracy with an academic and practical perspective.
Special Issue on Cyber Social Computing and Cyber-Enabled Applications
In the past several years, we have seen dramatic advancement in many application domains enabled by the use of emerging computing technologies and novice computational paradigms, as well as intelligent processing algorithms and methodologies. These emerging technologies are transforming our society, and have enormous economic impact from various aspects beyond people’s expectation. Thus, this special issue on Cyber Social Computing and Cyber-Enabled Applications aims to bring together researchers and engineers from all related areas in computer science and intelligent information processing to disseminate their findings on the computational theories, models, and technological solutions in terms of cyber-enabled applications with the cyber social computing paradigm. Therefore, this special issue will have a great significance and profound impact on the following computing-related topics: 1) Presenting emerging research and developments in the cyber social computing field. 2) Addressing the basic computational models and intelligent processing methodologies related to cyber social computing and cyber-enabled applications. 3) Enabling and facilitating practical computing and intelligence technologies to realize foundational frameworks, new functions, and adaptive services for cyber-enabled applications. 4) Exploring interests to seek potential collaborations, and push forward the development of cyber social computing.
Special Issue on Emerging Technologies for Disaster Management
We live in a world in which natural and man-made disasters (such as earthquakes, hurricanes, terrorist attacks, and industrial accidents) often occur. These disasters are so sudden in nature, so causing loss of human lives and interruption of essential public services (such as health care, electricity, water, transportation and communication). Disaster management aims to reduce or avoid potential losses from hazards, ensure prompt and appropriate assistance to victims and achieve a rapid and effective recovery. In recent years, new computing/communication technologies have emerged to improve the efficiency of disaster management; for example, crowdsourcing has been applied in the Nepal earthquake to collect the latest information from earthquake-affected areas and create a dynamic map that shows the locations in which aid and relief are needed. Although some preliminary attempts have been made to apply emerging technologies for disaster management, there are many open challenges that need to be addressed to fully exploit the potentials of these promising technologies.
Various technologies must be considered in the entire disaster management process and its many phases, including prevention, preparedness, relief and recovery. Although disasters cannot often be prevented, new technologies must be explored to predict and prepare through robust and resilient infrastructures. After a disaster occurs, advanced technologies are needed to assist in searching and rescuing victims. Since power and communication are usually interrupted, it is important to quickly recover communication using energy-efficient technologies, so that processing of information can take place; furthermore, good planning and scheduling can also help to quickly recover from a disaster.
Special Issue on Innovation in Technologies for Educational Computing
IEEE Transactions on Emerging Topics in Computing and IEEE Transactions on Learning Technologies seek original manuscripts for a Special Issue/Section on Innovation in Technologies for Educational Computing tentatively scheduled to appear in the December 2017 issues. The goal of this joint special issue is to provide an overview of most recent emerging and "fringe" learning technologies.
Special Issue on Reliability-aware Design and Analysis Methods for Digital Systems: from Gate to System Level
The continuous scaling of CMOS devices as well as the increased interest in the use of emerging technologies make more and more important the topics related to defect and fault tolerance in digital systems. To address the increasing complexity of digital systems and their challenging reliability requirements, it is imperative to employ design and analysis methods to different levels of the abstraction, starting from the system level down to the gate level. The IEEE Transaction on Emerging Topics in Computing (TETC) seeks original manuscripts for a Special Section on Reliability-aware Design and Analysis Methods for Digital Systems: from Gate to System Level scheduled to appear in the March issue of 2018. All aspects of design, manufacturing, test and analysis of systems affected by defects during manufacturing and by faults during system operation are of interest.
Special Issue on Cyber Security Threats and Defense Advances
With the rapid advancements in information and communications technology (ICT) and ‘expansion’ of cyber space, cyber security is of crucial importance to the stability of our Internet-connected society. For example, how do we ensure secure communications between servers, network nodes, terminals and user applications across public and private networks? Defending our cyber space is both a research challenge and an operational challenge. Designing effective security solutions is complicated by the need to carefully balance between security and usability, as well as the amount of efforts and resources required. For example, how do we achieve better security without compromising on communication speed?
This special issue aims to solicit state-of-the-art research advances in cyber-security threat mitigation and defense solutions, including the underlying cryptographic techniques. The issue welcomes both theoretical research, and applied research (e.g. implementations and applications).
IEEE Transactions on Emerging Topics in Computing is an open access journal that publishes papers on emerging aspects of computer science, computing technology, and computing applications not currently covered by other IEEE Computer Society Transactions. Some examples of emerging topics in computing include: IT for Green, Synthetic and organic computing structures and systems, Advanced analytics, Social/occupational computing, Location-based/client computer systems, Morphic computer design, Electronic game systems, & Health-care IT. TETC aggressively seeks proposals for Special Sections and Issues focusing on emerging topics. Prospective Guest Editors should contact the TETC EIC Fabrizio Lombardi at firstname.lastname@example.org for further details.
The IEEE Transactions on Haptics (ToH), a quarterly archival publication, is seeking submissions that address the science, technology, and applications associated with information acquisition and object manipulation through touch.
IEEE Transactions on Knowledge and Data Engineering (TKDE), a monthly archival publication, is seeking submissions that present well-defined theoretical results and empirical studies that have a potential impact on the acquisition, management, storage, and graceful degeneration of knowledge and data, as well as in provision of knowledge and data services. We welcome treatments of the role of knowledge and data in the development and use of information systems and in the simplification of software and hardware development and maintenance.
IEEE Transactions on Learning Technologies (TLT), a quarterly archival online-only publication using a delayed open access publication model, is seeking submissions about all advances in learning technologies, such as innovative online learning systems, personalized and adaptive learning systems, and learning with mobile devices
IEEE Transactions on Mobile Computing (TMC), a monthly archival publication, is seeking submissions of mature works of research, typically those that have appeared in part in conferences, and that focus on the key technical issues related to, but not limited to, architectures, support services, algorithm/protocol design and analysis, mobile environments, mobile communication systems, and emerging technologies.
Special Issue on System Support for Intermittent Computing
Low-power computing devices that harvest radio waves, vibration, light, etc. are key enablers of emerging applications, including infrastructure sensing, medical implants, IoT. A key challenge for energy-harvesting systems is that they operate only intermittently as energy is available. Systems may power off hundreds of times per second and when power fails, software, peripherals, and memory are disrupted. The intermittent execution model presents system designers with fundamentally new system design challenges that we must solve to make energy-harvesting computers viable. Today’s circuits, architectures, software & compilers, programming languages, and even programmers all assume that energy is continuously available. Intermittence invalidates this assumption demanding that we rethink s all layers of the system stack. This issue invites submissions solving problems faced by intermittent systems, with an emphasis on cross-cutting work with contributions in multiple areas.
Special Issue on Cognitive Computing with Emerging Technology
Over the last several decades, Dennard scaling and Moore's law have dramatically improved the capabilities of Von Neumann-style computing systems – where "memory" delivers instructions and data to a dedicated "processing unit". However, as scaling limitations of 2-D ICs are becoming more apparent, there is a growing interest in innovations that will ensure that future computing systems continue to be exponentially-more-capable than the systems of today.
In particular, cognitive computing systems inspired by facets of the human brain such as unsupervised, autonomous and continuous learning, are emerging as a promising alternative. Research in this area often involves cross-disciplinary exploration at multiple scales, combining new materials and devices with novel architectural concepts and integration schemes. Targeting the broad device, circuit, and architecture, as well as nanotechnology research communities, this special issue seeks papers on innovative new concepts for such systems. High-risk high-reward type of ideas, rethinking system design at multiple scales, will be preferred to incremental research. While many of these systems will not rely on non-Von Neumann architectures, the call does not preclude massively parallel systems with conventional hardware components, where novel integration and/or packaging could enable new capabilities such as the high degree of connectivity and collective functions reminiscent of the neocortex and other natural systems.
Special Issue on Emerging Technologies and Architectures for Manycore Computing
The pursuit of Moore's Law is slowing and the exploration of alternative devices is underway to replace the CMOS transistor and traditional architectures at the heart of data processing. Moreover, the emergence of stringent application constraints, particularly those linked to energy consumption, require new system architectural strategies (e.g. manycore) and real-time operational adaptability approaches. Such complex systems require new and powerful design and programming methods to ensure optimal and reliable operation. This special issue aims at collating new research along all the dimensions of emerging technologies and architectures for computing in manycores.
The IEEE Transactions on Multi-Scale Computing Systems (TMSCS) is a peer-reviewed publication devoted to computing systems that exploit multi-scale and multi-functionality. These systems consist of computational modules that utilize diverse implementation scales (from micro down to the nano scale) and heterogeneous hardware and software functionalities; moreover, these modules can be based on operating principles and models that are valid within but not necessarily across their respective scales and computational domains. Contributions to TMSCS must address computation of information and data at higher system-levels for processing by digital and emerging domains. These computing systems can also rely on diverse frameworks based on paradigms at molecular, quantum and other physical, chemical and biological levels. Innovative techniques such as inexact computing, management/optimization of smart infrastructures and neuromorphic modules are also considered within scope.
This publication covers pure research and applications within novel topics related to high performance computing, computational sustainability, storage organization and efficient algorithmic information distribution/processing; articles dealing with hardware/software implementations (functional units, architectures and algorithms), multi-scale modeling and simulation, mathematical models and designs across multiple scaling domains and functions are encouraged. Novel solutions based on digital and non-traditional emerging paradigms are sought for improving performance and efficiency in computation. Contributions on related topics would also be considered for publication.
IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.
IEEE Transactions on Parallel and Distributed Systems (TPDS), a monthly archival publication, is seeking submissions that deal with the parallel and distributed systems research areas of current importance to our readers. Particular areas of interest in parallel systems include, but are not limited to, architectures, software, and algorithms and applications. Particular areas of interest in distributed systems include, but are not limited to, algorithms and foundation, distributed operating systems, and Internet computing and distributed applications.
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), a monthly archival publication, is seeking submissions that discuss the most important research results in all traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence. Other areas of interest are machine learning, search techniques, document and handwriting analysis, medical image analysis, video and image sequence analysis, content-based retrieval of image and video, face and gesture recognition, and relevant specialized hardware and/or software architectures.
Special Issue on Fog Computing and Services
The emerging Internet of Things (IoT) and rich cloud services have helped create the need for fog computing (also known as edge computing), in which data processing occurs in part at the network edge or anywhere along the cloud-to-endpoint continuum that can best meet user requirements, rather than completely in a relatively small number of massive clouds. Fog computing could address latency concerns, devices’ limited processing and storage capabilities and battery life, network bandwidth constraints and costs, and many security and privacy concerns that arise from the emerging IoT.
The new Fog/Edge computing paradigm will enable the resources and services of computing, storage, networking, and control to be distributed closer to the users. Software distributions for various applications can now be hosted by fog servers, e.g., image processing packages for preprocessing images in video surveillance applications. Operating systems and the associated services can be offered through nearby fog servers to reduce round trip latency. Equipment outsourcing, such as storage, hardware, servers, and networking components can also be provisioned through fog servers. Fog computing is an extension to cloud services – it complements the clouds to enable computing where it makes the most sense.
Many new problems arise in enabling fog computing and services, creating a fertile ground for research and innovation. We are prompted to design new algorithmic, mathematical, statistical and computational methods to solve services computing problems on this new architecture. Service creation, development, and management, web services, business processes, and so on, need to be carefully redesigned. In addition, the new fog computing architecture can further provide new solutions to hard problems in the existing architectural framework, e.g., IoT services, security and privacy.
IEEE Transactions on Services Computing (TSC), is a quarterly archival online-only publication, is seeking submissions that emphasize the algorithmic, mathematical, statistical and computational methods that are central in services computing: the emerging field of service-oriented architecture, Web services, business process integration, solution performance management, services operations, and management.
IEEE Transactions on Software Engineering (TSE), a bimonthly archival publication, is seeking submissions of well-defined theoretical results and empirical studies that have a potential impact on the construction, analysis, or management of software. The scope of this Transactions ranges from the mechanisms through the development of principles to the application of those principles to specific environments. Since the journal is archival, it is assumed that the ideas presented are important, have been well analyzed, and/or empirically validated, and are of value to the software engineering research or practitioner community.
Special Issue on Orchestrating Sustainable Smart Cities: Methods and Techniques for Intelligence from clouds to edges
The staggering exponential increase in urbanization is posing unprecedented challenges to cities. Every day, urban areas grow by almost 150 000 people, either due to migration or births. In addition, due to factors of climate changes and other environmental pressures, cities are required to become "smart" to promote a thriving culture and achieve economical, social and environmental sustainability. Smart cities can be seen as wide-scale concord of internet of things, with sensors monitoring cyber and physical indicators and with actuators dynamically changing the complex urban environment in some way and cloud computing offerings the affordably to tap into enormous computing power. Historically, cities have viewed and addressed their challenges in siloes, by industry or region, for instance. The technological barriers so far have rendered cities unable to manage and scale urban services holistically, digitally and across departments. But that’s all changing. Motivated by economic, social, environmental and technological changes, Smart Cities are being constructed upon intelligent infrastructures spanning many application domains such as energy, healthcare, and transportation. Disaster Management, Security & Surveillance, Asset Management, Building Management, Emergency Alert Management, Smart Parking, Meteorological Data Management, Water Quality Management, Solid Waste Management, Early Health Warning System, Real Time Incident Notification, Irrigation Telemanagement, Smart Lighting, Property Information Management, Biometrics system and Compliant Registration System are some examples of such applications.
The advent of these societal-scale infrastructures brings with it new opportunities for improving efficiency while simultaneously exposing novel vulnerabilities. For example, smart metering technologies enables real-time capture of streaming data that could potentially be used to customize offerings to consumers by employing machine learning algorithms. On the other hand, the availability of this fine-grained consumer/system data and the increased number of access points to the broader system expose new privacy and security risks. In order to develop sustainable smart city solutions, Smart cities must have an open, flexible and secure platform on which consolidate siloes and services at the edge connect intelligently with the cloud and vice-versa. As connected things grow, we will witness a significant increase in data produced at the edge that will require new computer processing methods and techniques. These techniques needs to deluge in a distributed way across a citywide network transferring intelligence between cloud and things and connect people, processes, data, things and infrastructure.
These challenges represent a huge opportunity for a paradigm shift that will require the need for data processing, analysis, and security close to the connected "things" i.e. at the edge of the network. The paradigm shift will lead to an explosive growth of independent gateways, repeaters, and systems that will benefit from being positioned above the fray at the street level to avoid vandalism and provide a clear vantage point for data capture and transmission, so fastening them to lamp posts, poles or walls is advantageous and also allows them to receive power and city maintenance. This paradigm needs to be architected in a way that is easy to operate and dramatically simplifies the management of city services through scalable orchestration and proper automation. Such a platform must allow management of the different tenants within the smart city ecosystem in a uniform way. It should also have a suitable policy framework, letting specific stakeholders access data produced by other tenants, and analyze and extract value from the data. In order to address these challenges, this special issue solicits high quality original research papers (including smart city experience papers) that make significant contributions to the state-of-the-art in "method and techniques to build sustainable smart city solutions" research area.
Special Issue on Algorithms and Computational Models for Sustainable Computing in Cloud and Data Centers
Cloud Computing and Data Centers offer computing and data storage services and solutions at very large scale. These solutions however come with high costs and environmental impacts due to high energy consumptions at various levels of the computational and data storage processes. Therefore, energy consumption has become a key issue for the normal operation and maintenance of cloud computing platforms and datacenters, raising serious concerns from Cloud providers. Research trends such as Green Cloud Computing (GCC), Sustainable Cloud Computing (SSC) and alike aim to minimize energy consumption and therefore minimize costs and environmental impact.
Special Issue on Sustainable Cyber-Physical Systems
Cyber-physical system (CPS) addresses the close interactions and feedback controls between cyber components and physical components, where cyber components refer to the sensing and communication systems, while the physical components comprise of a wide range of systems in practice. CPS is expected to play a major role in the development of next-generation smart energy systems and data centers. Innovative computational methodologies such as green and energy efficient cyber-physical system design have become critical to enable the sustainable development of such systems. These technologies can be used to tackle various sustainability challenges, such as the reduction of energy induced from the large scale data center computing infrastructures, the improvement of computational efficiency in smart energy systems and connected vehicle systems, and the exploration of the renewable energy resources to mitigate classical energy usages. This special issue will present the state-of-the-art research results on the topic of sustainable computing for CPS, and stimulate researchers to participate in the related interdisciplinary research.
Special Issue on Low-Power Dependable Computing (LPDC)
With the continuous technology scaling and miniaturization of computing systems, faults become more common and it is imperative for most modern computing systems to deploy various fault-tolerance techniques. Traditionally, fault tolerance is achieved in general through various error reduction, detection and recovery techniques at different levels (for instance, circuit, architecture, operating systems, compiler and application software) in the systems. On the other hand, fault-tolerance does not come for free, and generally has power/energy/temperature overheads, which warrants careful consideration since power/energy is a first-class system resource and has been emerging as a significant limiting factor for multicore scaling. In particular, understanding the interdependencies between reliability and power are important to consider, e.g., high power consumption may lead to elevated temperature that can further aggravate reliability. In response to these challenges, this special issue seeks original contributions on novel and bold ideas to achieve low-power dependable computing (LPDC).
IEEE Transactions on Sustainable Computing (TSUSC) is a peer-reviewed journal devoted to publishing high-quality papers that explore the different aspects of sustainable computing, over a wide range of problem domains and technologies from software and hardware designs to applications. Sustainability includes energy efficiency, natural resources preservation, and use of multiple energy sources as needed in computing devices and infrastructure.
IEEE Transactions on Visualization and Computer Graphics (TVCG), a monthly archival publication, is seeking submissions that present important research results and state-of-the-art seminal papers related to computer graphics and visualization techniques, systems, software, hardware, and user interface issues. Specific topics in computer graphics and visualization include, but are not limited, algorithms, techniques and methodologies; systems and software; user studies and evaluation; rendering techniques and methodologies, including real-time rendering, graphics hardware, point-based rendering, and image-based rendering; and animation and simulation, including character animation, facial animation, motion-capture, physics-based simulation and animation.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), a bimonthly archival publication, is seeking submissions that discuss research results related to the algorithmic, mathematical, statistical, and computational methods that are central in bioinformatics and computational biology. This includes, but is not limited to, the development and testing of effective computer programs in bioinformatics; the development and optimization of biological databases; and important biological results that are obtained from the use of these methods, programs, and databases.