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 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.
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.
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 Issue on Transparent Computing
At 2012 Intel Developer Forum, San Francisco, Renee James, senior Vice President and General Manager of Intels Software Services Group, delivered a keynote speech "Next Era of Computing: Transparent Computing", in which she pointed out that "(transparent computing) represents for us the direction that we believe we need to go as an industry. And it's the next step really beyond ubiquitous computing."
The basic idea behind transparent computing is simple: give developers just one basic platform on which to develop their applications, and make it possible for these applications to run on any other platform. A formal model of transparent computing has been proposed, which is a cloud-style paradigm. As described by James, transparent computing "is really about allowing experiences to seamlessly cross across different platforms, both architectures and operating system platform boundaries". The key idea of transparent computing is to logically separate hardware and software (including operating systems) and to separate computation and memory. Specifically, all the required software and data are centralized on central servers, and streamed to the clients on demand to carry out the computing tasks leveraging the local CPU and memory resources. Compared with other cloud computing models, transparent computing has the following desired features: (1) user and application transparency; (2) heterogeneous OS support; (3) streaming delivery; (4) supports of various devices; and (5) enhanced security.
Joint Special Section on Defect and Fault Tolerance in VLSI and Nanotechnology Systems
With increasing defect rates in highly scaled CMOS and emergence of alternative nanotechnology devices, defect and fault tolerance in VLSI and nanotechnology systems is of growing importance. The IEEE Transactions on Computers and IEEE Transaction on Nanotechnology seek original manuscripts for a Special Section on Defect and Fault Tolerance in VLSI Systems scheduled to appear in the issue of March 2016.
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.
Special Issue on Security and Privacy Protection on Clouds
The emerging paradigm of cloud computing provides a new way to address the constraints of limited energy, capabilities, and resources. Researchers and practitioners have embraced cloud computing as a new approach that has the potential for a profound impact in our daily life and world economy. However, security and privacy protection is a critical concern in the development and adoption of cloud computing. To avoid system fragility and defend against vulnerabilities exploration from cyber attacker, various cyber security techniques and tools have been developed for cloud systems. This special issue will focus on the challenging topic—"Security and Privacy Protection on Clouds" and invites the state-of-the-art research results to be submitted here.
Special Issue on Cloud Networking
Cloud computing is entering our lives and changing the way people consume information dramatically. Clouds transform IT infrastructures with an emphasis on making them flexible, affordable, and capable of serving millions of users, satisfying their computing or storage demands. The design of early cloud computing systems has evolved from, and was dominated by, the concepts of cluster and grid computing. Currently, as the concepts of the cloud become advanced and mature, cloud networking and communication processes begin playing a central role. Cloud Networking has emerged as a promising direction for cost-efficient and reliable service delivery across data communication networks. The dynamic location of service facilities and the virtualization of hardware and software elements are stressing the communication network and protocols, especially when datacenters are interconnected through the Internet.
The optimization of cloud networking can significantly increase system performance, reducing energy consumption and save costs not only inside individual data centers, but also globally, on the Internet scale. Developing novel network architectures would facilitate adoption of modular container-based data centers. Advancements in internetworking become key enabler for building hybrid clouds and federations of clouds. Service provisioning over heterogeneous connections and wireless links can enhance computational capacity and enrich application experience of mobile users. Efficient resource management and scheduling in data centers and cloud infrastructures is open research challenge that has to be addressed and novel architectures, telecommunication technologies, and protocols must be developed to ensure efficiency of future cloud computing systems.
Special Issue on Big Data Computing on Clouds
Big data is an emerging paradigm applied to datasets whose size or complexity is beyond the ability of commonly used computer software and hardware tools. Such datasets are often from various sources (Variety) yet unstructured such as social media, sensors, scientific applications, surveillance, video and image archives, Internet texts and documents, Internet search indexing, medical records, business transactions and web logs; and are of large size (Volume) with fast data in/out (Velocity). More importantly, big data has to be of high value (Value) and establish trust in it for business decision making (Veracity). Various technologies are being discussed to support the handling of big data such as massively parallel processing databases, scalable storage systems, cloud computing platforms, and MapReduce. As estimated by IDC, by 2020, about 40% data globally would be touched with Cloud Computing. Besides, Cloud Computing provides strong storage, computation and distributed capability in support of Big Data processing. Therefore, there is a strong demand to investigate various challenges about how to support Big Data processing by facilitating Cloud Computing potential. This special issue will focus on this challenging topic.
Special Issue on Green and Energy-Efficient Cloud Computing
Cloud Computing has had a huge commercial impact and has attracted the interest of the research community. Public clouds allow their customers to outsource the management of physical resources, and rent a variable amount of resources in accordance to their specific needs. Private clouds allow companies to manage on-premises resources, exploiting the capabilities offered by the cloud technologies, such as using virtualization to improve resource utilization and cloud software for resource management automation. Hybrid clouds, where private infrastructures are integrated and complemented by external resources, are becoming a common scenario as well, for example to manage load peaks.
This special issue will provide the scientific and industrial communities a dedicated forum to present new research, development, and deployment efforts in the field of green and energy-efficient Cloud Computing. For example, while significant advancements have been made to increase the physical efficiency of power supplies and cooling components that improve the PUE index, such improvements are often circumscribed to the huge data centers run by large cloud companies. Even stronger effort is needed to improve the data center computational efficiency, as servers are today highly underutilized, with typical operating range between 10% and 30%. In this respect, advancements are needed both to improve the energy-efficiency of servers and to dynamically consolidate the workload on fewer, and better utilized, servers.
Special Issue on Cloud Service for Health Care
Health care service, in order to improve the quality and reduce the cost of medical services, has welcomed the modern information and computing technology involved. In the past two decades, the modern medical equipment, as advanced the medical information acquisition and the produced big data can be analyzed to aid the decision makings. The medical professionals have appreciated the extensive employments of data storage, data management and communication which enhance the medical services. With the development of big data, supercomputing, virtualization, cloud computing are recently more available, moderate, and secure. For example, if wireless sensor networks are related, the information becomes available in the "cloud" from where it can be produced by a doctor and analyzed by an expert or even a computer. Nevertheless, the traditional cloud computing techniques cannot meet our daily increasing requirements and we can do more for the future and tailor the cloud computing for health care service. The cloud computing for health care is to enhance the acquisition and computing of big health data which will be the topic of this special issue.
Cloud computing for health care is to improve the time and space efficiency and reduce the cost of health care by advanced cloud computing technology on storage, management and sharing techniques of big health data. The popularity of the cloud computing for health care can be displayed by its use in marketing to sell hosted services that run client servers of ware on a remote location. In this way, cloud for health care designs to integrate every available resource into individuals' health care, analyzing data, modeling, filtering and showing useful messages and giving final health care suggestions. While it is exciting to have health care services in the cloud for everyone, there are many security and privacy risks that may impede its wide adoption. Cloud service for health care can possibly be defined as devices and services for patients and health service providers and implementations of interoperable standards used with the aim of improving health of a given population (globally, nationally etc. or individually).
Special Issue on Many-Task Computing in the Cloud
The Special Issue on Many-Task Computing (MTC) in the Cloud will provide the scientific community a dedicated forum, within the prestigious IEEE Transactions on Cloud Computing journal, for presenting new research, development, and deployment efforts of loosely coupled large scale applications on Cloud Computing infrastructure. MTC, the theme of this special issue, encompasses loosely coupled applications, which are generally composed of many tasks to achieve some larger application goal. This special issue will cover challenges that can hamper efficiency and utilization in running applications on large-scale systems, such as local resource manager scalability and granularity, efficient utilization of raw hardware, parallel file-system contention and scalability, data management, I/O management, reliability at scale, and application scalability. We welcome paper submissions in theoretical, simulations, and systems topics with special consideration to papers addressing the intersection of petascale/exascale challenges with large-scale cloud computing. We seek submission of papers that present new, original and innovative ideas for the "first" time in TCC (Transactions on Cloud Computing). That means, submission of "extended versions" of already published works (e.g., conference/workshop papers) is not encouraged unless they contain significant number of "new and original" ideas/contributions along with more than 49% brand "new" material. For more information on this special issue, please see http://datasys.cs.iit.edu/events/TCC-MTC15/.
Special Issue on Mobile Clouds
Mobile cloud computing represents one of the latest developments in cloud computing advancement. In particular, mobile cloud computing extends cloud computing services to the mobile domain by enabling mobile applications to access external computing and storage resources available in the cloud. Not only mobile applications are no longer limited by the computing and data storage limitations within mobile devices, nevertheless adequate offloading of computation intensive processes also has the potential to prolong the battery life.
Besides, there is also an incentive for mobile devices to host foreign processes. This represents a new type of mobile cloud computing services. Ad-hoc mobile cloud is one instance that mobile users sharing common interest in a particular task such as image processing of a local happening can seek collaborative effort to share processing and outcomes. Vehicular cloud computing is another instance of mobile cloud computing that exploits local sensing data and processing of vehicles to enhance Intelligent Transportation Systems.
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 Cyber Crime
Cyber crimes reflect the evolution of criminal practices that have adapted to the world of information and communication technologies. Cybercriminality has become a curse of the modern world with the potential to affect every one nationally and/or internationally. Individuals, companies, governments and institutions may become victims as well as (involuntary) helpers of cyber criminals. The inability to provide cyber-security can potentially have a tremendous socio-economic impact on global enterprises as well as individuals. The aim of this special issue is to bring together the research accomplishments provided by the researchers from academia and the industry. The other goal is to show the latest research results in the field of cyber crime. Prospective authors will be encouraged to submit related distinguished research papers on the subject of both: theoretical approaches and practical case reviews.
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.
Special Issue on Emerging Topics in the Design of High Performance Internet Routers
Internet traffic growth is very rapid due to many popular internet applications such as real-time entertainment and P2P file-sharing. These applications involve a great deal amount of data for transferring through the Internet. Therefore, to maintain good quality of service, the internet routers resolve issues such as link speed, data throughput, and packet forwarding rate. Internet routers consult the destination address of each packet received and perform IP lookups in their router tables to determine the next hop for packets. High-performance routers require high-speed IP address lookup to achieve wire-speed packet forwarding. Then, using information in its routing table or routing algorithm, it directs the packet to the next network on its journey. Routers perform the "traffic directing" functions on the Internet. A data packet is typically forwarded from one router to another through the networks that constitute the internetwork until it reaches its destination node. When multiple routers are used in interconnected networks, the routers exchange information about destination addresses using a dynamic routing protocol. Each router builds up a table listing the preferred routes between any two systems on the interconnected networks. A router has interfaces for different physical types of network connections. It also contains firmware for different networking communications protocol standards. Each network interface uses this specialized computer software to enable data packets to be forwarded from one protocol transmission system to another. The focus of this special issue will be on routing algorithms, routing table design, routing protocol specifying, security strategy, and IPv6 deployment.
Special Issue on Parallel Programming and Architecture Support for Many-core Embedded Systems
Embedded system designs have evolved over time from fairly simple unicore single memory based designs to small homogeneous processing units connected by an on-chip network on the same silicon. The number of cores to be integrated in a single chip is expected to rapidly increase in the coming years, moving from multi-core to many-core architectures. This requires a global rethinking of software and hardware design approaches. The purpose of this special issue is to solicit papers discussing the latest advancements in embedded many-core system designs with a focus on parallel programming and architectures support issues. It is intended to provide an opportunity to exchange the most recent research ideas and results, initiating constructive discussion between international researchers from industry and academia.
Special Issue on Emerging Security Trends for Deeply-Embedded Computing Systems
The demand for ever smaller, portable, low-power and high-performance electronic systems has been the primary driver for CMOS technology scaling. As CMOS scaling approaches physical limits, it has been fraught with challenges that required introduction of newer processes and materials. High-κ oxide and metal-gate stack was introduced to mitigate oxide leakage. Thin body, undoped channels were introduced mitigate subthreshold leakage. 3D transistors such as FinFET and trigates were introduced to improve ON current while maintaining layout efficiency. While these incremental adjustments have allowed CMOS technology to scale, a number of alternative devices have been proposed to replace CMOS transistors such as graphene transistors (GFET), tunnel transistors, graphene nanoribbon tunnel transistors, quantum-dots and single-electron devices (SET). Newer memory technologies such as resistive RAMs, memristors, STT-RAMs similarly promise to revolutionize the design landscape. However for these alternative technologies to become practical, design methodologies that allow efficient modeling, design space exploration, and trade-off analysis is crucial. This is the driving motivation for this special issue.
Special Issue on Emerging Security Trends for Deeply-Embedded Computing Systems
Unlike traditional embedded systems, nowadays, emerging computing systems are embedded in every aspect of human lives. These deeply-embedded computing systems often perform extremely sensitive tasks, and in some cases, such as health-care IT, these are life-saving. Thus, in addition to the security threats to traditional embedded systems, emerging deeply-embedded computing systems exhibit a larger attack surface, prone to more serious or life-threatening malicious attacks. These call for revisiting traditional security mechanisms not only because of the new facets of threats and more adverse effects of breaches, but also due to the resource limitations of these often-battery-powered and extremely-constrained computing systems. As such, new trends for providing security for deeply embedded systems are emerging; many of which abandoning use of cryptographic computations or make use of lightweight crypto-systems, feasible for these computing platforms. Indeed, there exists paramount potential for applying these emerging security approaches to sensitive applications such as health-care IT for implantable medical devices, big data analytics and machine learning in deeply embedded systems, smart buildings, and smart fabrics. The focus of this special issue will be on novel security methods for deeply-embedded computing systems, emerging cryptographic solutions applicable to extremely-constrained applications such as green cryptography, and advancements in feasible security measures for evolving interdisciplinary research trends such as computing for: health-care IT, cyber-physical embedded systems, big data, and smart buildings/fabrics.
Special Issue on Advances in Mobile Cloud Computing
There is a phenomenal burst of research activities in mobile cloud computing, which extends cloud computing functions, services, and results to the world of future mobile communications applications, and the paradigm of cloud computing and virtualization to mobile networks. Mobile applications demand greater resources and improved interactivity for better user experience. Resources in cloud computing platforms such as Amazon, Google AppEngine and Microsoft Azure are a natural fit to remedy the lack of local resources in mobile devices. The availability of cloud computing resources on a pay-as-you-go basis, the advances in network virtualization, software defined networks, and the emergence of advanced wireless networks such as cloud-based radio access networks (C-RANs) create a new space of rich research problems. The objective of this special section is to cover the most recent research and development on the technologies for mobile cloud computing. This special section is to offer a venue for industry and academia to show case their recent progresses and potential research directions on the mobile cloud computing technologies.
Special Issue on Methods and Techniques for Processing Streaming Big Data in Datacentre Clouds
Internet of Things (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) as well as lab instruments (e.g., high energy physics synchrotron), and smart consumer appliances (smart TV, smart phone, etc.). The IoT vision has recently given rise to IoT big data applications that are capable of producing billions of data stream and tens of years of historical data 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.
Special Issue on Approximate and Stochastic Computing Circuits, Systems and Algorithms
The last decade has seen renewed interest in non-traditional computing paradigms. Several (re-)emerging paradigms are aimed at leveraging the error resiliency of many systems by releasing the strict requirement of exactness in computing. This special issue of TETC focuses on two specific lines of research, known as approximate and stochastic computing.
Approximate computing is driven by considerations of energy efficiency. Applications such as multimedia, recognition, and data mining are inherently error-tolerant and do not require perfect accuracy in computation. The results of signal processing algorithms used in image and video processing are ultimately left to human perception. Therefore, strict exactness may not be required and an imprecise result may suffice. In these applications, approximate circuits aim to improve energy-efficiency by maximally exploiting the tolerable loss of accuracy and trading it for energy and area savings.
Stochastic computing is a paradigm that achieves fault-tolerance and area savings through randomness. Information is represented by random binary bit streams, where the signal value is encoded by the probability of obtaining a one versus a zero. The approach is applicable for data intensive applications such as signal processing where small fluctuations can be tolerated but large errors are catastrophic. In such contexts, it offers savings in computational resources and provides tolerance to errors. This fault tolerance scales gracefully to high error rates. The focus of this special issue will be on the novel design and analysis of approximate and stochastic computing circuits, systems, algorithms and applications.
Special Issue/Section on Low-Power Image Recognition
Digital images have become integral parts of everyday life. It is estimated that 10 million images are uploaded to social networks each hour and 100 hours of video uploaded for sharing each minute. Sophisticated image / video processing has fundamentally changed how people interact. For example, automatic classification or tagging can mediate how photographs are disseminated to friends. Many of today's images are captured using smartphones, and cameras in smartphones can be used for a wide range of imaging applications, from high-fidelity location estimation to posture analysis. Image processing is computationally intense and can consume significant amounts of energy on mobile systems. This special issue focuses on the intersection of image recognition and energy conservation. Papers should describe energy efficient systems that perform object detection and recognition in images.
This special issue aims to establish milestones of the state of the art. Thus, all papers are required to include results on a common core of datasets using the same metrics. Training images will be sampled from the data for ILSVRC 2014 (ImageNet Large Scale Visual Recognition Challenge). These images are already annotated with objects. The objects are classified into approximately 200 categories that are typically used in everyday lives, for example, flower, car, and dog. Authors will submit results on a separate test dataset set to a centralized server in order to evaluate detection accuracy.
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 email@example.com for further details.
Special Issue on Special Issue on Active Touch Sensing in Robots, Humans and Other Animals
This special issue addresses the challenges posed by active sensing and interacting with the world through the sense of touch, whether the latter is implemented through a technological or biological system. Active touch sensing is recovering information about the world by ‘touching' rather than ‘being touched' – by interpreting signals from sensors whose motion is deliberately controlled to facilitate information gain.
The scope of this issue includes both biological and technological systems for active touch sensing, and implications for haptics. This issue will consider electronic systems for active touch sensing that are biologically inspired systems, in addition to other inherently active approaches to touch sensing.
Biological systems for active touch sensing are highly capable, and, by comparison, the field of robotic touch sensing is in its infancy. The former demonstrate many valuable concepts for active touch sensing that are being intensively investigated. They have also illustrated ways that active touch sensing is enabled through specialized sensory transduction channels, biomechanics, structural morphology, behavioral, and control strategies that are implemented by biological systems, and through other advantages that they achieve, including robustness, adaptability, and power efficiency. Similar challenges must be overcome if technological systems are to one day achieve comparable levels of sensorimotor performance to biological systems.
Submission Deadline: March 1, 2015. View PDF
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.
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.
Special Issue on "Higher Order Graphical Models in Computer Vision: Modelling, Inference and Learning"
Analyzing human poses and behaviors from visual and non-visual sensor data is one of the most challenging topics in Computer Vision, Pattern Analysis and Machine Learning. Recently driven by the need of user friendly interfaces, the next challenge is to integrate and analyze sensor data coming from different modalities, including RGB cameras, 3D range sensors, infrared cameras, audio signals, or Inertial Measurement Unit data, among others.
Human Pose Recovery and Behavior Analysis (HuPBA) has been used for posterior analysis of gestures and context in both still images and image sequences. However, HuPBA requires dealing with the articulated nature of the human body, changes in appearance because of clothes, and the inherent difficulties of clutter scenes, such as background artifacts, occlusions and illumination changes. Given the inherent difficulties of human pose estimation and the requirement for accurate estimations in order to perform posterior human behavior analysis, alternative visual modalities from different input sensors have drawn a lot of attention. This includes Time-of-Flight (ToF) cameras, other active or passive 3D range images (e.g. Infrared-based Kinect© Microsoft device), camera networks, light field cameras, multispectral sensors, underwater vision, and other non-conventional visual sensors as the new generation of low cost Thermal wavelengths cameras. These and other visual modalities have shown to offer complementary information, so data fusion increases the accuracy of computer vision approaches.
In addition to the use of different visual modalities for HuPBA, behavior analysis can be potentially benefited from the use of other complementary sources of sensor data, such as audio signals, Inertial Measurement Unit data, Electrothermal activity responses, and Electroglottograph signals, among others. In this sense, some challenges that arise from the use of different modalities for behavior analysis essentially includes feature extraction, synchronization of data coming from different sensors, data fusion, and temporal series analysis.
Several areas have emerged that require accurate multi-modal HuPBA technologies, such as Affective Computing or Social Signal Processing. Moreover, the efforts involved in these fields of research will be compensated by its potential applications, including leisure (gaming, intelligent retrieval of video data, augmented reality, Human Computer Interaction, etc.), security (security surveillance and ambient intelligence), health care (greater autonomy for those suffering diseases, advanced assisted living, inpatient monitoring, supported diagnosis, etc.) and energy (smart rooms, buildings and cities), to name just a few. In addition to this broad range applications, some novel approaches are being explicitly designed to be implemented in graphical processor units, smart phones, and game consoles.
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 Emerging Web Services
From a technology foundation perspective, Services Computing has become the default discipline in the modern services industry. As a major implementation technology for modernizing the services industry, Web services are Internet-based application components that are published using standard interfaces and description languages and that are universally available via uniform communication protocols.
IEEE Transactions on Services Computing (TSC) proudly announces a special issue on Emerging Web Services. Some of the topics that might be addressed in this special issue are Web services specifications and enhancements, Web services discovery and integration, Web services QoS (e.g., performance, security, reliability, fault tolerance, etc.), Web services standards and formalizations, Web services modeling, Web services engineering, Web services testing, Web services applications, Web services realizations, Web services semantics, Web services to support Cloud Computing, Web services lifecycle management, and SOA infrastructure and middleware.
The IEEE International Conference on Web Services (ICWS) has been prime international forums for both researchers and industry practitioners to exchange the latest advances in the state of the art and practice of Web services, to identify emerging research topics, and to define the future of Web-based services. After merging with IEEE European Conference on Web Services (ECOWS) in 2012, in 2014, ICWS is celebrating its 21th anniversary in Anchorage, Alaska, USA. The IEEE Transactions on Services Computing (TSC) is planning to have a special issue based on the top papers from ICWS 2014. The authors of those papers will be invited to submit extended versions of their papers to TSC, and the papers will undergo a special review process of the TSC review board and the guest editors.
Special Issue on Cloud Computing and Services
In recent years, Cloud Computing has become a scalable services consumption and delivery platform in the field of Services Computing. The technical foundations of Cloud Computing include Service-Oriented Architecture (SOA) and virtualizations of hardware and software. The goal of Cloud Computing is to share resources among the cloud service consumers, the cloud service providers, and the cloud vendors in the cloud value chain. Resource sharing at various levels results in various cloud offerings such as infrastructure cloud (e.g., hardware, IT infrastructure management), software cloud (e.g., Software as a Service including middleware as a service, and traditional CRM as a service), application cloud (e.g., Application as a Service, UML modeling tools as a service, social networks as a service), and business cloud (e.g., business processes as a service).
IEEE International Conference on Cloud Computing (CLOUD) has been a prime international forum for both researchers and industry practitioners to exchange the latest advances in the state of the art and practice of cloud computing, to identify emerging research topics, and to define the future of cloud computing. The IEEE Transactions on Services Computing (TSC) is planning to have a special issue based on the Best Papers and Best Student Papers from CLOUD 2014. The authors of those papers will be invited to submit extended versions of their papers to TSC, and the papers will undergo a special review process of the TSC review board and the guest editors.
Special Issue on Big Data Analytics, Infrastructure, and Applications
The pervasive nature of digital technologies as witnessed in industry, services and everyday life has given rise to an emergent, data-focused economy stemming from many aspects of human individual and commercial activity. The richness and vastness of these data are creating unprecedented research opportunities in a number of fields including urban studies, geography, economics, finance, and social science, as well as physics, biology and genetics, public health and many others.
In addition to Big Data-inspired research, businesses have seized on big data technologies to support and propel growing business intelligence needs. As businesses build out Big Data hardware and software infrastructure, it becomes increasingly important to anticipate technical and practical challenges and to identify best practices learned through experience.
Big Data analytics employ software tools from advanced analytics disciplines such as data mining, predictive analytics, and machine learning. At the same time, the processing and analysis of big data presents methodological and technological challenges. The goal of this special issue is to present both novel solutions to challenging technical issues as well as compelling Big Data use cases. This special issue will share related practical experiences to benefit the reader, and will provide clear proof that big data analytics technologies are playing an ever-increasing important and critical role in supporting business intelligence - a new cross-discipline research topic in computer science and business.
Special Issue on Processes meet Big Data
The aim of process mining is to discover, monitor and improve business processes by extracting knowledge from event logs readily available in today's information systems. Process monitoring and analysis has enjoyed a tremendous growth and a rapid development at both conceptual and algorithmic levels. In particular, there have been successful realizations of process monitoring systems in many application areas, including manufacturing, e‐health and e‐government. Today, the current trend toward large‐scale collaborative processes featuring thousands of elementary activities per minute is generating new research challenges. When large‐scale processes are executed on (cloud‐based) serviceoriented environments or even on the global Net, elementary activities can be mapped to fine or coarse‐grained protocol events and process logs increasingly come to show all typical properties of "big data": wide physical distribution, diversity of formats, non‐standard data models, heterogeneous semantics. Computing metrics over such "big logs" also requires to handle security and privacy concerns of many participants, and even to deal with nonuniform trustworthiness of log entries. New techniques are therefore required for designing, validating and deploying process metrics in this scenario, as well as for effectively dashboarding the processes' performance indicators.
This special issue of IEEE Transaction on Service‐Oriented Computing is intended to present innovative developments of process monitoring and analysis over service‐oriented architectures, aimed at handling "big logs" and use them effectively for discovery, dashboarding and mining. The ultimate objective is to identify the most promising research avenues, report the main results and promote the visibility and relevance of this new area.
Special Issue on Special Issue on Cyber-Physical Systems and Services
The cyber-physical space integrates a vast variety of static and mobile resources, including computing/medical/engineering devices, swarms of robots, remote-controlled vehicles, critical infrastructures, sensor/actuator networks, control and decision software, static data and just-in-time information from sensors, knowledge, data analytics and fusion software, event-driven supply chains, and humans, and offers a great potential of achieving tasks that are far beyond the capabilities of existing systems. Individual users, organizations, and various communities can transform the vast space of cyber-physical resources into capabilities that no single entity can achieve alone. However, these capabilities do not come easily. Intelligence is needed for just-in-time composition of resources into capabilities. For example, how to discover and manage the vast and dynamic resources, how to describe the capabilities of the resources, how to achieve intelligent coordination among the cyber-physical entities, how to manage the information flow, how to predict the collective capabilities of the composed resources - that may consist of physical subsystems, intelligent software, vast amounts of data and knowledge, and humans, etc. are pressing issues to be investigated. Dependability and security in such cyber-physical systems can be extremely complex, while also being absolutely essential. Human resources constitute a class of physical entities in the cyber-physical world and influence the operation of cyber entities. As such integrating humans into the loop to achieve effective and dependable operation has long been a challenge. Capturing the effect of the human operator in modeling and predicting the operation of cyber-physical systems and services is equally challenging.
Many problems remain unresolved; however, existing technologies in service-oriented systems may be leveraged to provide partial solutions. Services can be positioned as a higher-level abstraction for the cyber-physical systems to mediate the interactions among devices, software, information, humans, and applications. Rapidly developing service-related technologies, such as service discovery, service composition, service adaptation, dynamic service reconfiguration, etc., can be applied with relative ease to integration tasks in cyber-physical applications. Furthermore, grids of data and services and information sharing technologies are research directions that can be leveraged to help manage and process information flow in the cyber physical space. Intelligent agents and coordination technologies can also be integrated and leveraged to attain smart collaborations. However, existing service paradigms, grid infrastructures, and intelligent collaboration techniques are not up to the challenge, and new models and techniques that extend existing paradigms need to be investigated to maximize the utilization of the vast amount of resources and capabilities in the cyber-physical world.
This special issue will present novel research results on cyber-physical systems and services (CPSS), including advances in modeling and related technologies, intelligence-assisted discovery, composition, collaboration, and adaptation of cyber-physical services, dependability and security for cyber-physical systems and services, as well as the identification of new research challenges and directions that can facilitate the formation of a truly intelligent and dependable cyber-physical world.
Special Issue on Special Issue on Cloud Services Meet Big Data
The concept of cloud services represents a prime facility and feature of cloud computing services made available to users on demand, when and where needed. Because cloud computing provides flexibility in scaling IT resources up and down according to dynamically changing business requirements, it makes cloud services so valuable to attract the gaze of people from both academia and industry. Consumers, providers, operators, etc. are generating a large amount of data on such services per minute on the Internet, which increasingly comes to show all typical properties of big data. New methodologies and techniques are therefore required for designing, validating, developing, testing and deploying cloud services on demand in this scenario, as well as for being effectively adaptive to business dynamics and users' explicit and implicit requirements.
The objective of this special issue is to identify the most promising research fields, report the main recent innovative results and promote the visibility and relevance of this noteworthy direction in the interdisciplinary field between services computing and other emerging disciplines. It will cover all the aspects about cloud services in the era of Big Data.
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.
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.
Special section/section on Complex Systems Biology and Translational Bioinformatics
This Special Section aims to publish top 10% selected papers from the 8th International Conference on Systems Biology and the 4th Translational Bioinformatics Conference (ISB/TBC 2014), organized by Chinese Academy of Sciences and Qingdao University will be held in Qingdao, China, October 25-26, 2014. This conference is sponsored by National Natural Science Foundation of China (NSFC), Academy of Mathematics and Systems Sciences of CAS (AMSS), Shanghai Institutes for Biological Sciences of CAS (SIBS), Qingdao Institute of Bioenergy and Bioprocess Technology of CAS (QIBEBT), Qingdao University, Computational Systems Biology Society of ORSC, Functional Genome Informatics and Systems Biology Society of CSCB, Systems Biology Technical Committee of IEEE SMC Society, Korean Society for Bioinformatics and Systems Biology (KSBSB), The Korean Society of Medical Informatics (KOSMI), Korean Genome Organization (KOGO).
Systems Biology and Bioinformatics have become intensive research topics in the recent past decade and attracted great many leading scientists working in Biology, Physics, Mathematics and Computer Science. Optimization, Statistics, and many other mathematical methods have been widely used in the field. The ISB has been organized for seven years and made great impact in bioinformatics community and published several special issues in related journal including BMC Systems Biology, Methods, IET Systems Biology and so on.
Following the successful ISB conferences series from 2007, the purpose of ISB/TBC 2014 is to extend the international forum for scientists, researchers, educators, and practitioners to exchange ideas and approaches, to present research findings and state-of-the-art solutions in this interdisciplinary field, including mathematical methods and its applications in biosciences and researches on various aspects of Systems Biology and Translational Bioinformatics, such as integration of genome-wide microarray, proteomic, and metabolomic data, inference and comparison of biological networks, and model testing through design of experiments.
This conference has been developed into an important international conference in Asia region. According to the history of ISB conference and joint with TBC, there will about 100 submissions. Finally, we hope to publish 5 to 8 high-quality papers from this event.
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.