Journal Information
Future Generation Computer Systems
http://www.journals.elsevier.com/future-generation-computer-systems/
Impact Factor:
3.997
Publisher:
ELSEVIER
ISSN:
0167-739X
Viewed:
17191
Tracked:
60

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Call For Papers
The Grid is a rapidly developing computing structure that allows components of our information technology infrastructure, computational capabilities, databases, sensors, and people to be shared flexibly as true collaborative tools. Over the last 3 years there has been a real explosion of new theory and technological progress supporting a better understanding of these wide-area, fully distributed computing systems. After the advances made in distributed system design, collaborative environments, high performance computing and high throughput computing, the Grid is the logical next step.

The new Aims and Scope of FGCS will cover new developments in:

[1] Grid Applications and application support:

    Novel applications
    eScience and eBusiness applications
    Problem solving environments and virtual laboratories
    Grid economy
    Semantic and knowledge based grids
    Collaborative Grids and virtual organizations
    High Performance and high throughput computing on grids
    Complex application workflows
    Scientific, industrial and social implications
    Grids in education

[2] Grid methods and middleware:

    Tools for grid development: monitoring and scheduling
    Distributed dynamic resource management
    Grid- and web-services
    Information management
    Protocols and emerging standards
    Peer to peer and internet computing
    Pervasive computing
    Grid Security

[3] Grid Theory:

    Process specification; program and algorithm design
    Theoretical aspects of wide area communication and computation
    Scaling and performance theory
    Protocol verification


Last updated by Xin Yao in 2017-11-12
Special Issues
Special Issue on Cognitive Internet of Things Assisted by Cloud Computing and Big Data
Submission Date: 2018-03-01

Cognitive Internet of Things (CIoT) is the use of cognitive computing technologies, which is derived from cognitive science and artificial intelligence, in combination with data generated by connected devices and the actions those devices can perform. CIoT is viewed as the current IoT integrated with cognitive and cooperative mechanisms to promote performance and achieve intelligence. Furthermore, assisted by cloud computing and big data, CIoT is expected to provide deeper insights and high-level intelligence from the vast amount of data being created by IoT to create value for people, cities, and industry. Therefore, CIoT is considered to drive the next generation of data analytics and technical capabilities, and infuse intelligence and decision making into the physical world to continually transform businesses and enhance the human experience in real-time. CIoT is the next leap in improving the accuracy and efficiency of complex, sensor-driven systems through learning and infusing more human awareness into the devices and environments we interact with. In particular, cloud computing and big data are essential to upgrade the IoT ecosystems with new capabilities such as machine learning, cognitive sensing, data mining, pattern recognition and natural language processing that can mimic or augment human intelligence. This special issue aims to explore recent advances and disseminate state-of-the-art research related to CIoT on designing, building, and deploying novel cognitive computing, services and technologies, to enable smart IoT applications. Both hardware and software (i.e., application level) solutions are solicited within the scope of call. The relevant topics of this special issue include but are not limited to: - Innovative architecture, infrastructure, techniques and testbeds for CIoT - Cognitive sensors and other novel sensor systems - Novel computational/intelligent models and applications for CIoT - Individual and social behavior analysis through CIoT - Adaptive cloud computing in CIoT resource management - Cloud computing for context aware data management in CIoT - Tools, services, technologies, algorithms and methods for data analysis in CIoT - Novel intelligent systems for information fusion in CIoT - Privacy protected discovery and adaptation in CIoT - CIoT standardization and implementation challenges
Last updated by Dou Sun in 2017-12-16
Special Issue on Cloud and Fog Computing for Smart Cities Data Analytics and Visualisation
Submission Date: 2018-03-01

Information and Communication Technologies are becoming the prime enabler for smart and sustainable cities in recent years. This is mainly due to realising and making effective use of the ever-increasing data generated in urban environments. Sensors, smart phones, geo-tagged devices, RFIDs, smart gadgets and Internet of Things are major source of collecting ever increasing temporal and geo-coded land-use, built-environment, transport, energy, health, socio-economic and environmental Big Data. Often data is kept in different repositories and managed by different departments, which raise data access, harmonisation, processing and information visualisation challenges for generating new insights and knowledge. Cloud and Fog/Edge are becoming enablers for managing cross-departmental temporal and geocoded Big Data, developing cross-thematic applications and providing necessary computation power to perform data analytics and present new knowledge to city stakeholders for awareness raising, city planning, policy development and decision making. High-performance visual processing techniques provide opportunity to intuitively present temporal and geo-coded information from neighbourhood scale to city or city-region scale and fosters innovation, co-creation and co-designing sustainable future cities. In the above context, the real value of smart city big data is gained by applying data mining, machine learning or new statistical methods for data analytics, visualisation and decision making. This becomes challenging when applied to large scale or real time data and hence requires appropriate tools and techniques to be applied using Cloud and Fog/Edge computing. These applications also require dealing with privacy and data security issues to avoid sharing intrusive details of citizens or other stakeholders. Topics of interest include use of cloud and fog computing in smart cities but are not limited to: - Smart city data analytics - Geo-processing and innovative visualisation techniques - Spatial data techniques and tools for analytics - City data quality, harmonisation, integration and processing - Real-time city data processing and visualisation - Predictive analytics, visualisation and simulation for future city models - Visual computing and analytics for city applications - Interactive data analysis and visualisation - Smart city services and applications platforms - Security and privacy solutions for smart city applications - Crowd sourcing and establishing trust on data sources - Internet of Things for cross-thematic city applications - Methods and techniques for city data collection and curation - Automated and intelligent city data processing methods - Design patterns and computing models for smart city applications - Open government data for automated processing and knowledge generation - Decision support systems for smart cities - Data provenance techniques for city applications, decision making and policy making - Smart city applications: mobility, energy, public administration & governance, economy, health, security and environment.
Last updated by Dou Sun in 2017-08-05
Special Issue on Computation Intelligence for Energy Internet
Submission Date: 2018-05-01

Energy crisis and carbon emission have become two global concerns. As a very promising solution, Energy Internet recently emerges to be able to tackle these challenges. Energy Internet is a radically new power generation and usage paradigm by exploiting the Internet principle to develop a revolutionary vision of smart grid. In Energy Internet, intelligent computation and communications are crucial in both operating and maintaining smart energy systems. In this sense, incorporating computation intelligence becomes the natural feature in all components as well as the whole energy system. Energy Internet applications using intelligent platforms typically need to be connected with users located remotely by using Internet of Things (IoT) and Cloud. This will transform energy system into intelligent designs and systems. New intelligent models, architectures, approaches, algorithms and solutions are needed to cope with the ever-increasing complexity of problems in energy systems, such as sensing intelligence, communications intelligence, machine learning, deep learning, and data mining. Specifically, real-time monitoring and controlling are faced with great challenges in order to collect precise energy management data. New machine learning and knowledge discovery methods are imperative to integrate, process and analyze sensing data from computation sensors for intelligent control and real-time decision making. Further, safeguards are needed to build trust in the data, which is instrumental for making critical decisions for the development of Energy Internet. This special issue will be dedicated to research and advances on the issues in Computation Intelligence for Energy Internet. Original papers describing new and previously unpublished works will be selected addressing all aspects of computation intelligence in Energy Internet. The papers will go through the usual review process, and then further reviewed by the editorial team to ensure quality of publication. The topics of interest in this special issue include, but are not limited to: - Energy Internet system and architecture with computation intelligence - Computation intelligence for Energy Internet applications, e.g., power grid, Vehicle-to-Grid, PV systems, wind farm, buildings, and energy storage - Design and analysis of real-time systems in Energy Internet - Intelligent M2M communications in Energy Internet - Cloud/Fog based intelligence for Energy Internet - Computation security and privacy in Energy Internet - Intelligent algorithms and optimization for Energy Internet - Machine Learning and deep learning for Energy Internet - Big data analysis intelligence for Energy Internet - Data mining and knowledge discovery for Energy Internet - Innovative forecasting methods in Energy Internet
Last updated by Dou Sun in 2017-08-05
Special Issue on Smart Data in Future Internet Technologies and Cloud Computing
Submission Date: 2018-05-15

The fast growing data volume has enabled multiple application to become “smart” in implementations. The Internet technologies combining distributed computing settings such as cloud computing have further increased the performance of the system. The benefits of using data-driven applications have a strong impact on various industries, including the financial industry, manufacturing, consulting agency, and healthcare. One of the vital issues in data-driven applications is to find out efficient methods of optimizations in both executions and outputs sides. The challenges are varied, which could include but are limited to speeding up the data mining efficiency in big data, secure data transmissions among multiple stakeholders, adoptable network designs for multi-channel communications, etc. Using data wisely is considered one of the potential solutions to the potential risks or restrictions in the field. This special issue aims to gather recent quality work in the topic of smart data in future Internet technologies as well as cloud computing and provide the work with a discussion and evaluation forum. The principal focus of this special issue will address new techniques in the field of data mining in the network and cloud context. Scope: Topics of particular interest include, but are not limited to: - Cloud workload profiling and centralized control solution - Self-service cloudlet and clustered edge servers - Analytics applications - Scientific computing and data management - Cloud metering, implementation, and monitoring - Network-based big data management and analytics - Smart storage and data analytics in clouds - Cyber threat intelligence and defense - Data-driven service management automation - Security and fault tolerance for embedded or ubiquitous systems - Cloud security and privacy issues - Sensor network security issues in mobile cloud computing - Embedded networks and sensor network optimizations - Cloud computing and networking models - Ambient intelligence and intelligent service systems in cloud system
Last updated by Dou Sun in 2017-10-29
Special Issue on Technological innovations in Digital transformation
Submission Date: 2018-05-31

It is widely acknowledged that organizations have suffered a large evolution at the social, economic and technological levels where the traditional barriers of transferring information and knowledge have been progressively eliminated. This evolution allowed the elimination of silos, the breaking down of hierarchies, the connection of internal and external stakeholders and the empowering of employees. In this context, the integration of technological innovations, such as Big Data – Analytics, Cloud Computing, Mobile Connectivity, and Social, the four pillars of digital transformation, in business practice can enable significant competitive advantage. According to Earley Information Science digital transformation (DT), is today a top priority for executives, being that (1) 125000 enterprises expect revenue from their digital initiatives to increase by 80% by 2020; (2) DT initiatives will more than double by 2020, from 22% to almost 50% and, (3) only 27% of businesses have a coherent digital strategy for creating customer value in place. The main purpose of digital transformation is to obtain benefits of digital technologies, such as productivity improvements, cost reductions and innovation. Nevertheless, for these results to be achieved, a total organizational commitment is required. From the organizations’ point of view, DT can be seen as a deep and accelerating transformation with regard to processes, activities, competencies and models, in order to take advantage of the changes and opportunities offered by the inclusion of digital technologies into an organization. However, this advantage is only possible if the information systems of the organizations are aligned with these new technologies. Thus, the Future Generation Computer Systems journal is seeking manuscripts for a special issue entitled “Big Data, Cloud, Mobile and Social in Digital transformation”. This issue will have as broad a scope as possible with respect how DT can be used to attain this goal. We also would like to attract papers that discuss the impact of the DT in the everyday life citizens, enterprises and governments. This special issue will include full-papers resulting from: - Extended papers presented at the WorldCist'18 - 6th World Conference on Information Systems and Technologies (http://www.worldcist.org) to be held at Naples, Italy, 27 - 29 March 2018. For this special issue will be selected some best papers from the tracks “A) Information and Knowledge Management (IKM)”; “D) Software Systems, Architectures, Applications and Tools (SSAAT)”; “H) Big Data Analytics and Applications (BDAA)”. - Other original research contributions focusing on the aims and scope of this special issue.
Last updated by Dou Sun in 2017-10-29
Special Issue on CyberSecurity & Biometrics for a better Cyberworld
Submission Date: 2018-11-30

Cybersecurity is an essential requirement when living in a digital world. Should one user trust a service on internet? How well secured are my personal data in the digital world? All these questions request new technical and methodological solutions involving many aspects among cryptography, information theory, protocols… In order to establish a secure link between users and cyber services, biometrics becomes a key technology. However, it has also many drawbacks such as possible false rejection of legitimate users and false acceptance of impostors, privacy concerns and possible attacks (spoofing, replay). In this special issue, we expect high-level research contributions in this area in order to propose useful solutions to secure our Cyberworld. The topics include but are not limited the following research areas: - Security protocols - Authentication protocols - Privacy protocols - Password security - Security of personal data - Content protection and digital rights management - Risk and reputation management - Identity and trust management - Information hiding and anonymity - Privacy, security and trust in social media - Security of embedded systems - Behavioral biometrics - Performance evaluation of biometric systems - Multi-biometrics - Quality of biometric data - Biometric template protection - Presentation attack detection - Emerging biometrics
Last updated by Dou Sun in 2017-12-16
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